chore: remove .gsd/ from tracking, add to .gitignore

.gitignore

@@ -1,4 +1,5 @@
 
+.gsd/
 # ── GSD baseline (auto-generated) ──
 .DS_Store
 Thumbs.db

.gsd/DECISIONS.md

@@ -1,18 +0,0 @@
-# Decisions Register
-
-<!-- Append-only. Never edit or remove existing rows.
-     To reverse a decision, add a new row that supersedes it.
-     Read this file at the start of any planning or research phase. -->
-
-| # | When | Scope | Decision | Choice | Rationale | Revisable? | Made By |
-|---|------|-------|----------|--------|-----------|------------|---------|
-| D001 |  | architecture | Engine/App architectural relationship | Engine is standalone module, App is a consumer. Zero coupling — App calls Engine only via HTTP API. | Engine is proprietary IP that must be embeddable into future applications independently. Clean input/output contracts enable this. | No | human |
-| D002 |  | architecture | Build order and gating strategy | Build Engine first (M001), then App canvas (M002), then Export+Deploy+Embed (M003). Human checkpoints gate each transition. | Brief explicitly mandates: validate engine output quality before building canvas UI, validate canvas before export/deploy. Engine is the hardest and most valuable piece. | No | human |
-| D003 |  | engine | Post-processing replaces regex metadata extraction | postprocess_svg() pipeline replaces old _extract_svg_metadata() regex approach; all SVG paths are parsed into structured PathInfo objects with coordinates, area, island status | Structured path data is needed for DXF/JSON output generation, RDP simplification, and island detection. XML parsing is now necessary since we need actual coordinate data, not just counts. This supersedes D003's regex approach. | No | agent |
-| D004 |  | architecture | Engine Docker image build strategy | Multi-stage build: builder stage compiles pypotrace with build-essential/libagg-dev/libpotrace-dev, runtime stage uses python:3.11-slim with only runtime libs (libpotrace0, libagg2, curl). Only engine source is copied — no App code. | Multi-stage keeps the runtime image small by excluding build tools. Copying only engine source enforces the Engine/App separation (D001). curl is included for Docker HEALTHCHECK. | Yes | agent |
-| D005 |  | architecture | Frontend technology stack for Kerf App | Vite + React + TypeScript with plain CSS modules, Vitest for testing, raw fetch + FormData for engine API calls, no UI framework for V1 | Minimal dependency surface for a tool that needs fast iteration. The engine API uses multipart/form-data which works naturally with native fetch + FormData. CSS modules avoid global style conflicts without adding a framework. Vitest integrates natively with Vite's transform pipeline. No UI library needed — the app has a focused interface with ~8 components. | Yes | agent |
-| D006 |  | frontend | React hook params stabilization strategy for useDebouncedTrace | JSON.stringify params in useEffect deps array, single-effect architecture | useCallback-based triggerTrace with object params caused infinite re-render loops because React creates new object references each render. JSON.stringify converts params to a stable string for dependency comparison, eliminating the need for callers to useMemo their params objects. Simpler API surface and no re-render bugs. | Yes | agent |
-| D007 |  | architecture | Canvas object type system design | Discriminated union on `type` field: 'rect' \| 'circle' \| 'ellipse' \| 'line' \| 'image'. All objects share BaseCanvasObject (id, name, x, y, visible, locked, stroke, fill, opacity). Type-specific fields via intersection types. | TypeScript discriminated unions enable exhaustive type narrowing in switch/if statements, catching missing cases at compile time. Shared base keeps CRUD operations generic while type-specific panels (ShapeProperties) safely narrow to access unique fields. 'text' type will be added in S03. | Yes | agent |
-| D008 |  | frontend | opentype.js integration strategy for font loading and text-to-path conversion | opentype.js v1.3.4 with dynamic import(), local type declarations, per-character glyph positioning for letter spacing, and Y-axis flip (canvas_y = ascender - font_y * scale) for canvas-compatible SVG path coordinates | opentype.js has no @types package, so local declarations are needed. The library's getPath() doesn't support letter spacing natively — manual per-character positioning with x-advance accumulation is required. Font coordinate system is Y-up while canvas is Y-down, requiring the ascender-based flip formula. Dynamic import() avoids bundling issues with the library's CommonJS/ESM dual packaging. | Yes | agent |
-| D009 |  | frontend | Text-to-paths conversion strategy | Convert-to-paths uses a single onConvertToPath(textObjectId, imageObject) callback that generates an SVG Blob URL and creates an ImageObject replacement, reusing the existing image rendering pipeline | Reusing the ImageObject type and its existing Konva rendering avoids adding a new 'path' object type. A single callback keeps the prop interface simpler than separate onAddObject + onRemoveObject and makes the replacement atomic. The SVG Blob URL contains the path data with fill/stroke matching the original text object. | Yes | agent |
-| D010 |  | architecture | Embed mode delivery strategy for <kerf-embed> Web Component | Separate Vite library mode build (vite.embed.config.ts) producing self-contained ES+IIFE bundle in dist-embed/. Shadow DOM for style isolation. setEngineBaseUrl() module-level setter for API URL configuration (not React context). @font-face injected into document.head from connectedCallback(). :root rewritten to :host in shadow root styles. | Vite library mode is the most natural fit for the existing Vite-based build. Shadow DOM provides real CSS isolation without iframe overhead. Module-level setter for engine URL avoids threading a React context through every API-calling component (simpler than context approach with minimal app code changes). @font-face must be in document scope per browser spec — Shadow DOM @font-face doesn't trigger font downloads. :host is more reliable than :root inside shadow trees across browsers. | Yes | agent |

.gsd/KNOWLEDGE.md

@@ -1,50 +0,0 @@
-# Project Knowledge
-
-Append-only register of project-specific rules, patterns, and lessons learned.
-Agents read this before every unit. Add entries when you discover something worth remembering.
-
-## Rules
-
-| # | Scope | Rule | Why | Added |
-|---|-------|------|-----|-------|
-
-## Patterns
-
-| # | Pattern | Where | Notes |
-|---|---------|-------|-------|
-| P001 | Test images generated programmatically via numpy | engine/tests/ | No fixture image files checked in. Tests create shapes (rectangles, circles) with numpy + cv2. Continue this pattern in S02/S03. |
-| P002 | Tests must use .venv/bin/python -m pytest | engine/ | No system-wide `python` on PATH. Bare `python -m pytest` fails with exit 127. Always use the venv binary. |
-| P003 | PostProcessResult is the universal intermediate representation | engine/pipeline/postprocess.py → engine/output/ | All output generators (DXF, JSON, SVG) consume PostProcessResult. Never generate output directly from raw SVG strings. |
-| P004 | _format_response() for consistent multi-format API responses | engine/api/routes.py | DXF returns binary Response with X-Kerf-Metadata header; SVG/JSON return JSON envelopes. Use _format_response() for both /engine/trace and /engine/simplify. |
-| P005 | Preset-driven pipeline: resolve_params() merges preset → user | engine/presets/loader.py, engine/api/routes.py | Presets define defaults for all pipeline stages. User params override. Mode comes from preset unless user explicitly sets it. |
-| P006 | JSON.stringify for React hook dependency stabilization | app/src/hooks/useDebouncedTrace.ts | Object params in useEffect deps cause infinite loops (new ref each render). Stringify the params object and use the string in the deps array. Avoids requiring callers to useMemo. |
-| P007 | Vite dev proxy for engine API calls | app/vite.config.ts | `/engine/*` requests proxy to `http://localhost:8000`. API client uses relative URLs (`/engine/presets`). No CORS issues in dev because same-origin via proxy. |
-| P008 | CSS modules for views, global App.css for shared component styles | app/src/views/*.module.css, app/src/App.css | View-specific layout in CSS modules avoids conflicts. Shared styles (upload zone, preset cards, buttons) in App.css for cross-component reuse. |
-| P009 | opentype.js needs dynamic import() and local type declarations | app/src/utils/fontService.ts | No @types/opentype.js package exists. Use `const opentype = await import('opentype.js')` with `type OpentypeFont = any` for the Font object. Variable .ttf fonts work fine for glyph extraction. |
-| P010 | Font Y-axis flip: canvas_y = ascender - font_y * scale | app/src/utils/fontService.ts | opentype.js uses font coordinate system (Y-up) while canvas uses screen coordinates (Y-down). Apply `ascender * scale - font_y` to all Y values in path data. Without this, text renders upside-down. |
-| P011 | Letter spacing requires manual per-character glyph positioning | app/src/utils/fontService.ts | opentype.js getPath() doesn't support letter spacing. Must iterate characters, get individual glyph paths, accumulate x-advance + spacing per character, and compose the final SVG d-attribute manually. |
-| P012 | Adding new CanvasObject types requires exhaustive switch updates in 6 files | app/src/types/canvas.ts, KonvaStage, CanvasToolbar, ObjectPanel, ShapeProperties, AlignmentBar | TypeScript noFallthroughCasesInSwitch enforces exhaustive handling. When adding a new type to the CanvasObject union, all switch statements across these 6 files must be updated or compilation fails. |
-| P013 | Export service: compose → validate → download is pure-function pipeline | app/src/utils/exportService.ts | composeCanvasSVG() builds SVG string, validateForExport() checks for errors/warnings, triggerDownload() creates blob + hidden anchor. All pure functions, no React deps. ExportView orchestrates them. |
-| P014 | Canvas state lifted to App.tsx for cross-view sharing | app/src/App.tsx | useCanvasState() called in App.tsx, all 14 return values spread as props to DesignCanvas via UseCanvasStateReturn interface. ExportView receives objects + artboard. PNG captured via stageRef before view transition since Konva stage unmounts. |
-| P015 | Vite `?inline` CSS imports for Shadow DOM injection | app/src/embed.tsx | `import css from './index.css?inline'` returns CSS as a string instead of injecting into `<head>`. Required for Shadow DOM components where styles must be injected into shadow root, not document head. Extract `@font-face` rules to document.head separately — fonts declared inside Shadow DOM don't reliably trigger downloads cross-browser. |
-| P016 | Module-level setEngineBaseUrl() for embed API configuration | app/src/api/engine.ts | Mutable `_baseUrl` with setter function avoids threading React context through every API-calling component. Simpler than context approach — embed.tsx calls `setEngineBaseUrl()` once in `connectedCallback()` before React renders. |
-
-## Lessons Learned
-
-| # | What Happened | Root Cause | Fix | Scope |
-|---|--------------|------------|-----|-------|
-| L001 | pypotrace fails to build from pip | Requires system packages: `libpotrace-dev`, `libagg-dev`, `pkg-config` | `apt-get install -y libpotrace-dev libagg-dev pkg-config` before `pip install pypotrace` | engine build, Docker |
-| L002 | VTracer Python bindings work directly — no subprocess needed | vtracer pip package exposes `convert_raw_image_to_svg()` that accepts PNG bytes | Use `vtracer.convert_raw_image_to_svg(png_bytes, img_format="png", ...)` | engine vectorize |
-| L003 | pypotrace Bitmap requires uint32 data | Passing other dtypes (uint8, float) can cause segfaults | Always cast: `(img > 0).astype(np.uint32)` before `potrace.Bitmap(data)` | engine vectorize |
-| L004 | ezdxf emits pyparsing deprecation warnings in tests | ezdxf uses deprecated pyparsing method names (`addParseAction`, `oneOf`, etc.) | These are harmless library warnings — don't try to fix them. Filter with `pytest -W ignore::DeprecationWarning` if noisy. | engine tests |
-| L005 | DXF output format needs binary response, not JSON envelope | DXF files are binary/text data not suitable for JSON embedding | Use FastAPI `Response(content=bytes, media_type="application/dxf")` with metadata in `X-Kerf-Metadata` header | engine API |
-| L006 | postprocess_svg() fully parses SVG paths into coordinates | XML parsing + path d-attribute parsing gives structured PathInfo objects | This replaces the old regex-based SVG metadata extraction (D003). All output generators (DXF, JSON, SVG) consume PostProcessResult. | engine pipeline |
-| L007 | Docker build context must be project root, not engine/ | Dockerfile.engine uses `COPY engine/...` paths relative to project root | Always build with `docker build -f docker/Dockerfile.engine -t kerf-engine:dev .` from project root | Docker |
-| L008 | Engine container has dual health endpoints | /health on root (main.py) and /engine/health on router (routes.py) both exist | Use /engine/health for Docker HEALTHCHECK and external probes for namespace consistency | engine API, Docker |
-| L009 | useCallback-based triggerTrace caused infinite re-render loops | Object params create new references each render, retriggering useEffect even when values are unchanged | Restructure hook to use single useEffect with JSON.stringify(params) in dependency array instead of useCallback-based approach | app hooks, React |
-| L010 | jest-canvas-mock crashes in Vitest with "ReferenceError: jest is not defined" | jest-canvas-mock internally calls jest.fn() in createImageBitmap.js — Jest globals don't exist in Vitest | Use vitest-canvas-mock (a Vitest-compatible fork) instead. Import it in test-setup.ts. | app tests, canvas |
-| L011 | `npx tsc -b --noEmit` and `npx vitest run` fail from project root | Root has no node_modules with tsc/vitest, and vitest doesn't pick up app/vite.config.ts jsdom environment | Root package.json with `"workspaces": ["app"]` + `npm install` hoists deps. Root tsconfig.json references `./app`. Root vitest.config.ts uses `test.projects: ['app/vite.config.ts']` to delegate. | monorepo, testing |
-| L012 | DXF scale_factor is caller-computed: 1/96 for inches, 25.4/96 for mm (assuming 96 PPI artboard) | Engine generate_dxf() applies scale_factor uniformly to all coordinates but doesn't know PPI — caller must compute | App exportService computes scaleFactor based on artboard unit. Engine API `/engine/simplify` accepts `units` and `scale_factor` as form params. | engine-app contract |
-| L013 | nginx:alpine healthcheck with `wget -qO- http://localhost:80/` fails | `localhost` resolves to `::1` (IPv6) in Alpine containers, but nginx default listens on `0.0.0.0` (IPv4 only) | Use `127.0.0.1` explicitly: `wget -qO- http://127.0.0.1:80/` | Docker, healthcheck |
-| L014 | Embed vite build fails from project root — only app-level config exists | Root `npx vite build --config vite.embed.config.ts` needs a root-level config that sets `root: 'app'` and resolves paths relative to project root | Created root-level `vite.embed.config.ts` that mirrors `app/vite.embed.config.ts` with correct path resolution. Both configs must be kept in sync. | embed, monorepo |
-| L015 | Aspirational success criteria that aren't refined into requirements or slice plans get silently dropped | postMessage events were listed in M003 success criteria but never scoped into any slice, requirement, or task | Success criteria must trace to at least one requirement and one slice. If a criterion has no slice owner, it won't be built. Catch this during milestone planning review. | project management |

.gsd/PROJECT.md

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-# Kerf Engine — Project Status
-
-## Overview
-Kerf Engine is a raster-to-vector conversion tool with a React design canvas, purpose-built for producing laser/CNC-ready SVG and DXF output from raster images.
-
-## Completed Milestones
-
-### ✅ M001: Kerf Engine — Raster-to-Vector Pipeline & API
-OpenCV preprocessing → potrace/vtracer vectorization → post-processing → multi-format output (SVG/DXF/JSON) exposed via FastAPI REST API with preset-driven pipeline configuration. Dockerized with multi-stage build.
-
-### ✅ M002: React Frontend — Import & Convert UI + Design Canvas
-Built the complete React frontend:
-- **View 1 (Import & Convert):** File upload, preset selection, debounced live vectorization preview with parameter sliders, output stats bar, Use This button
-- **View 2 (Design Canvas):** Konva.js-powered 2D environment with artboard shapes (rect, circle, ellipse, shield, pennant), basic shapes, text objects with opentype.js font loading and text-to-path conversion, layers panel, alignment tools, property editing, keyboard shortcuts, undo/redo
-- **95 tests, zero TypeScript errors**, 54 source files, 10,721 lines of code
-
-### ✅ M003: Export, Deployment & Embedding
-Delivered the complete end-to-end experience: upload → design → export → download.
-- **S01 — Export Flow (View 3) + DXF Generation:** ExportView with DXF/SVG/PNG format selection, unit selector (inches/mm), pre-export validation panel (text blocking, raster warnings), download wiring. Engine DXF generation with $INSUNITS headers and real-world scale conversion. Pure-function export pipeline: compose → validate → download.
-- **S02 — Docker Packaging + README:** Full-stack Docker Compose (engine + app behind nginx reverse-proxy) with healthchecks. Comprehensive 253-line README with 4-endpoint API reference, preset table, and curl examples.
-- **S03 — Embed Mode:** `<kerf-embed>` Web Component with Shadow DOM for CSS isolation. Vite library-mode ES + IIFE bundles in dist-embed/. Configurable engine URL via `setEngineBaseUrl()`. Demo page proves style isolation.
-- **126 app tests + 36 engine output tests, zero TypeScript errors**
-
-## In-Progress Milestones
-
-None.
-
-## Tech Stack
-- **Engine:** Python 3.11, FastAPI, OpenCV, pypotrace, vtracer, ezdxf
-- **App:** Vite, React 19, TypeScript (strict), Konva.js, opentype.js
-- **Testing:** pytest (engine), Vitest + testing-library (app)
-- **Infrastructure:** Docker multi-stage build, nginx reverse-proxy, npm workspaces monorepo
-
-## Key Architecture Decisions
-- D001: Engine is standalone module, App consumes via HTTP API only
-- D005: Vite + React + TS with plain CSS modules, minimal dependency surface
-- D007: Canvas state uses useReducer + useRef pattern for undo/redo
-- D008: Canvas objects use TypeScript discriminated union on `type` field
-- D010: Embed mode via Shadow DOM Web Component with separate Vite library-mode build
-
-## Test Summary
-- **Engine:** 36 output tests (pytest) covering SVG, JSON, DXF formats with scale conversion
-- **App:** 126 tests (Vitest) across 8 test suites covering hooks, utils, API client, components
-- **TypeScript:** Zero errors across all app source files

.gsd/STATE.md

@@ -1,21 +0,0 @@
-# GSD State
-
-**Active Milestone:** M004: M004
-**Active Slice:** S01: Conversion Modes + Invert + Expanded Sliders
-**Phase:** summarizing
-**Requirements Status:** 0 active · 0 validated · 0 deferred · 0 out of scope
-
-## Milestone Registry
-- ✅ **M001:** Kerf Engine — Raster-to-Vector Pipeline & API
-- ✅ **M002:** M002: React Frontend — Import & Convert UI + Design Canvas
-- ✅ **M003:** M003: Export, Deployment & Embedding
-- 🔄 **M004:** M004
-
-## Recent Decisions
-- None recorded
-
-## Blockers
-- None
-
-## Next Action
-All tasks done in S01. Write slice summary and complete slice.

.gsd/completed-units-M002.json

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-[]

.gsd/completed-units.json

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-[]

.gsd/event-log.jsonl

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.gsd/milestones/M001/M001-ROADMAP.md

@@ -1,11 +0,0 @@
-# M001: Kerf Engine — Raster-to-Vector Pipeline & API
-
-## Vision
-Build and validate the standalone Kerf Engine: a stateless HTTP API that accepts raster images (or existing SVGs) and returns clean, production-quality vector output (SVG, DXF, JSON) through a multi-stage pipeline of preprocessing, vectorization, post-processing, and format conversion. This is the proprietary IP core — it must work flawlessly before anything else is built.
-
-## Slice Overview
-| ID | Slice | Risk | Depends | Done | After this |
-|----|-------|------|---------|------|------------|
-| S01 | Core Pipeline — Preprocessing + Vectorization | high — dependency installation, opencv+potrace+vtracer integration | — | ✅ | POST /engine/trace with a PNG logo returns valid SVG using both Potrace and VTracer modes |
-| S02 | Post-Processing + Output Formats (SVG, DXF, JSON) | high — dxf generation quality is hard to validate programmatically | S01 | ✅ | /engine/trace returns valid DXF and JSON output; /engine/simplify reduces node count on complex SVG |
-| S03 | Preset System + Engine Docker Packaging | low — presets are config files; docker packaging is well-understood | S02 | ✅ | GET /engine/presets returns all presets; each preset produces distinct output from same input; engine runs in Docker |

.gsd/milestones/M001/M001-SUMMARY.md

@@ -1,94 +0,0 @@
----
-id: M001
-title: "Kerf Engine — Raster-to-Vector Pipeline & API"
-status: complete
-completed_at: 2026-03-26T04:56:42.994Z
-key_decisions:
-  - D001: Engine is standalone module, App is consumer — zero coupling via HTTP API only
-  - D003: postprocess_svg() pipeline replaces regex-based SVG metadata extraction with full path parsing into structured PathInfo objects
-  - D004: Multi-stage Docker build — builder compiles pypotrace, runtime uses python:3.11-slim with only engine source
-  - Bilateral filter chosen over Gaussian for edge-preserving denoise in preprocessing
-  - DXF output as raw bytes with metadata in X-Kerf-Metadata header (not JSON envelope)
-  - Preset default is 'sign' — covers the most common use case
-  - Bezier curves linearized for RDP simplification and DXF polyline generation
-key_files:
-  - engine/main.py — FastAPI app entry point
-  - engine/api/routes.py — All API endpoints: /engine/trace, /engine/simplify, /engine/presets, /engine/health
-  - engine/pipeline/preprocessing.py — OpenCV preprocessing pipeline (grayscale, denoise, CLAHE, threshold, morphology)
-  - engine/pipeline/vectorize.py — Potrace + VTracer dual-mode vectorization
-  - engine/pipeline/postprocess.py — SVG path parsing, RDP simplification, island detection, open path repair (414 lines)
-  - engine/output/dxf.py — AC1015 DXF generator with LWPOLYLINE entities and island layer separation
-  - engine/output/json_output.py — Structured JSON output with path commands and properties
-  - engine/output/svg.py — SVG output generator from PostProcessResult
-  - engine/presets/loader.py — Preset loader with caching, listing, and merge-based param resolution
-  - engine/presets/sign.json — Sign preset (aggressive simplification for signage)
-  - engine/presets/patch.json — Patch preset (smooth curves, auto-close for embroidery)
-  - engine/presets/stencil.json — Stencil preset (heavy simplification, fixed threshold)
-  - engine/presets/detailed.json — Detailed preset (max fidelity for illustrations)
-  - engine/presets/custom.json — Custom preset (empty defaults, user controls everything)
-  - docker/Dockerfile.engine — Multi-stage Docker build with HEALTHCHECK
-  - engine/tests/ — 196 tests across 6 test files
-lessons_learned:
-  - L001: pypotrace requires system packages (libpotrace-dev, libagg-dev, pkg-config) — must be installed before pip install
-  - L002: VTracer Python bindings work directly via convert_raw_image_to_svg() — no subprocess needed
-  - L003: pypotrace Bitmap requires uint32 data — cast with (img > 0).astype(np.uint32) to avoid segfaults
-  - L005: DXF output needs binary Response with X-Kerf-Metadata header, not JSON envelope
-  - L006: Full SVG path parsing into coordinates is necessary for DXF/JSON output — regex counting is insufficient
-  - L007: Docker build context must be project root, not engine/ — Dockerfile uses COPY engine/ paths
-  - Programmatic test images via numpy eliminate fixture file management and make tests self-contained
-  - Tests must use .venv/bin/python -m pytest — no system python on PATH
----
-
-# M001: Kerf Engine — Raster-to-Vector Pipeline & API
-
-**Shipped a stateless FastAPI raster-to-vector engine with OpenCV preprocessing, dual vectorization modes (Potrace + VTracer), RDP post-processing with island detection, three output formats (SVG, DXF, JSON), a 5-preset configuration system, and Docker packaging — 196 tests passing.**
-
-## What Happened
-
-M001 built the complete Kerf Engine — the proprietary raster-to-vector conversion core — across three slices.
-
-**S01 (Core Pipeline)** stood up the FastAPI project with an OpenCV preprocessing pipeline (grayscale, bilateral filter, CLAHE, Otsu thresholding, morphological ops) and dual vectorization: Potrace for binary bitmap tracing and VTracer for color/grayscale tracing. POST /engine/trace accepts PNG uploads and returns SVG output with metadata. 76 tests established the foundation and patterns (programmatic test images via numpy, .venv pytest runner).
-
-**S02 (Post-Processing + Output Formats)** added the post-processing layer that parses raw SVG paths into structured PathInfo objects, implements Ramer-Douglas-Peucker simplification, detects islands via signed-area calculation, and identifies open paths. Three output generators consume PostProcessResult: DXF (AC1015 with LWPOLYLINE entities, islands on separate layer), JSON (structured path commands with properties), and SVG (simplified output). A /engine/simplify endpoint was added for SVG-to-SVG/DXF/JSON conversion. The old regex-based metadata extraction was replaced entirely by full path parsing — a necessary evolution to support DXF coordinate output and island detection.
-
-**S03 (Presets + Docker)** wrapped the milestone with a preset system (5 tuned configs: sign, patch, stencil, detailed, custom) that drives the entire pipeline via merge-based param resolution (preset defaults + user overrides). GET /engine/presets exposes all configs. Docker packaging uses a multi-stage build — builder stage compiles pypotrace with C dependencies, runtime stage uses python:3.11-slim with only engine source (no App code), enforcing the Engine/App separation mandated by D001. Container includes HEALTHCHECK on /engine/health.
-
-The slices integrated cleanly: S01's vectorizer output feeds S02's postprocess_svg(), which produces PostProcessResult consumed by output generators; S03's preset system configures all three pipeline stages. routes.py evolved across all slices with no regressions — the final 196-test suite validates every endpoint and format combination.
-
-## Success Criteria Results
-
-### S01: "POST /engine/trace with a PNG logo returns valid SVG using both Potrace and VTracer modes"
-- ✅ **MET** — POST /engine/trace endpoint exists and works. Integration tests confirm both Potrace and VTracer modes produce valid SVG with metadata (path_count, node_count_total, open_paths, processing_ms). 6 mode-specific tests pass.
-
-### S02: "/engine/trace returns valid DXF and JSON output; /engine/simplify reduces node count on complex SVG"
-- ✅ **MET** — output_format parameter routes to SVG/DXF/JSON. DXF returns binary with X-Kerf-Metadata header. JSON returns structured path arrays. /engine/simplify accepts SVG + epsilon and returns simplified output in all formats. 22 format/simplify tests pass including test_simplify_reduces_nodes.
-
-### S03: "GET /engine/presets returns all presets; each preset produces distinct output from same input; engine runs in Docker"
-- ✅ **MET** — GET /engine/presets returns all 5 presets. test_presets_produce_different_node_counts confirms cross-preset differentiation. Docker image builds from multi-stage Dockerfile, starts healthy, serves /engine/health. 28 preset tests pass.
-
-## Definition of Done Results
-
-- ✅ All 3 slices marked complete (S01 ✅, S02 ✅, S03 ✅)
-- ✅ All slice summaries exist on disk (S01-SUMMARY.md, S02-SUMMARY.md, S03-SUMMARY.md)
-- ✅ 196 tests pass in 1.24s with exit 0
-- ✅ 31 non-GSD source files created (3,619 lines of code)
-- ✅ Cross-slice integration verified: S01→S02 pipeline path works, S02→S03 preset-driven flow works, all endpoints coexist in routes.py
-- ✅ Validation passed with verdict: pass (M001-VALIDATION.md)
-
-## Requirement Outcomes
-
-No formal requirements (REQUIREMENTS.md) were defined for this milestone. Governance was via architectural decisions (D001-D004) and per-slice success criteria.
-
-**Decision compliance:**
-- D001 (Engine/App separation): Validated — Docker image contains only engine source, zero App coupling.
-- D002 (Build order): Validated — Engine built first as mandated. M002/M003 deferred.
-- D003 (Post-processing replaces regex): Validated — postprocess_svg() fully supersedes regex extraction.
-- D004 (Multi-stage Docker build): Validated — builder compiles pypotrace, runtime uses slim image.
-
-## Deviations
-
-D003 (regex metadata extraction) was superseded mid-milestone — postprocess_svg() replaced it entirely with full XML path parsing, which was necessary for DXF/JSON output generation. Docker build context correction: plan referenced /vmPool/r/repos/xpltdco/kerf which doesn't exist — actual context is project root. Added /engine/health alongside /health for namespace consistency (not originally planned). Postprocessing params (auto_close, close_tolerance) exposed through preset system beyond original plan scope.
-
-## Follow-ups
-
-Consider adding preset validation on load (schema check). Consider documenting pipeline defaults in the custom preset for discoverability. Future M002 will consume the engine container as a service for the App canvas UI. Future M003 handles export, deployment, and embed functionality.

.gsd/milestones/M001/M001-VALIDATION.md

@@ -1,92 +0,0 @@
----
-verdict: pass
-remediation_round: 0
----
-
-# Milestone Validation: M001
-
-## Success Criteria Checklist
-## Success Criteria Checklist
-
-The M001 roadmap defines success via per-slice "After this" demo criteria (no separate success criteria section). Each is evaluated below:
-
-### S01: "POST /engine/trace with a PNG logo returns valid SVG using both Potrace and VTracer modes"
-- [x] **PASS** — `POST /engine/trace` endpoint exists in `engine/api/routes.py`. S01 summary confirms 14 integration tests covering both Potrace and VTracer modes. S01-UAT test case 7 verifies the response shape contract. 76 tests pass including mode-specific tests (`TestTraceEndpointPotrace`, `TestTraceEndpointVtracer`). Full test suite re-run confirms 196 tests pass (S01 tests still green).
-
-### S02: "/engine/trace returns valid DXF and JSON output; /engine/simplify reduces node count on complex SVG"
-- [x] **PASS** — `output_format` parameter routing confirmed in routes.py (svg/dxf/json). DXF generator (`engine/output/dxf.py`) produces AC1015 DXF with LWPOLYLINE entities. JSON generator (`engine/output/json_output.py`) outputs structured path arrays. `/engine/simplify` endpoint confirmed in routes.py. 35 API integration tests cover all format combinations for both endpoints. S02-UAT defines test cases for DXF binary response with X-Kerf-Metadata header, JSON path structure, and simplification node reduction.
-
-### S03: "GET /engine/presets returns all presets; each preset produces distinct output from same input; engine runs in Docker"
-- [x] **PASS** — `GET /engine/presets` endpoint confirmed in routes.py. All 5 preset JSON files verified on disk (sign, patch, stencil, detailed, custom) with correct structure (preprocessing/vectorization/postprocessing sections). 28 preset-specific tests include cross-preset output differentiation tests. `docker/Dockerfile.engine` implements multi-stage build with HEALTHCHECK. S03 summary confirms container builds, starts healthy, and serves all endpoints.
-
-## Slice Delivery Audit
-## Slice Delivery Audit
-
-| Slice | Claimed Deliverable | Delivered? | Evidence |
-|-------|-------------------|-----------|----------|
-| S01 | FastAPI server with /engine/trace, OpenCV preprocessing, Potrace + VTracer vectorization | ✅ Yes | `engine/main.py`, `engine/api/routes.py` (POST /engine/trace), `engine/pipeline/preprocessing.py` (OpenCV pipeline), `engine/pipeline/vectorize.py` (potrace_trace + vtracer_trace). 76 tests passing. |
-| S01 | 76 tests | ✅ Yes | All included in 196-test suite; original S01 tests still pass. |
-| S02 | postprocess_svg() with RDP simplification, island detection, node counting | ✅ Yes | `engine/pipeline/postprocess.py` (414 lines) with PathInfo objects, RDP, island detection via signed-area. |
-| S02 | Output generators: DXF, JSON, SVG | ✅ Yes | `engine/output/dxf.py` (66 lines, ezdxf AC1015), `engine/output/json_output.py` (76 lines), `engine/output/svg.py` (22 lines). |
-| S02 | /engine/simplify endpoint | ✅ Yes | Confirmed in routes.py — POST /engine/simplify with epsilon + output_format params. |
-| S02 | output_format routing on /engine/trace | ✅ Yes | Confirmed in routes.py — accepts svg/dxf/json. |
-| S02 | 169 tests | ✅ Yes | All included in 196-test suite. |
-| S03 | 5 presets (sign, patch, stencil, detailed, custom) | ✅ Yes | All 5 JSON files present in `engine/presets/` with correct structure verified. |
-| S03 | Preset loader with param merge/resolution | ✅ Yes | `engine/presets/loader.py` with resolve_params() — user overrides preset defaults. |
-| S03 | GET /engine/presets endpoint | ✅ Yes | Confirmed in routes.py. |
-| S03 | Docker image with healthcheck | ✅ Yes | `docker/Dockerfile.engine` — multi-stage build, HEALTHCHECK pings /engine/health. |
-| S03 | GET /engine/health endpoint | ✅ Yes | Confirmed in routes.py. |
-| S03 | 196 total tests | ✅ Yes | Full suite run: `196 passed, 21 warnings in 0.96s`. |
-
-## Cross-Slice Integration
-## Cross-Slice Integration
-
-### S01 → S02 Boundary
-- **Contract:** S01 produces raw SVG strings from potrace_trace() and vtracer_trace(). S02 consumes these via postprocess_svg().
-- **Status:** ✅ Aligned. S02 summary confirms postprocess_svg() replaced the old regex metadata extraction (D003). PostProcessResult is the universal intermediate representation. 169 tests pass including integration tests that exercise the full S01→S02 pipeline path.
-- **Response shape evolution:** S01 defined `{output, format, metadata: {path_count, node_count_total, open_paths, warnings, processing_ms}}`. S02 extended metadata to include `island_count`. This is additive — backward compatible.
-
-### S02 → S03 Boundary
-- **Contract:** S03 consumes the post-processing pipeline and output format generators. Presets configure the full pipeline (preprocessing + vectorization + postprocessing params).
-- **Status:** ✅ Aligned. S03 summary confirms resolve_params() merges preset defaults with user overrides. Presets contain preprocessing, vectorization, and postprocessing sections that feed directly into the pipeline stages built in S01/S02. 28 preset integration tests validate end-to-end preset→pipeline→output flow.
-
-### Cross-cutting: routes.py
-- The API router (routes.py) was modified by all three slices. Final state (7364 bytes) contains all endpoints from all slices: /engine/health, /engine/presets, /engine/trace, /engine/simplify. No regressions — 196 tests confirm all endpoints work together.
-
-### No boundary mismatches detected.
-
-## Requirement Coverage
-## Requirement Coverage
-
-No formal requirements (REQUIREMENTS.md) were defined for this milestone. The project uses decision records (D001–D004) and per-slice success criteria as the governing specification.
-
-**Decision compliance check:**
-- **D001** (Engine/App separation): ✅ Docker image copies only engine source — no App code. Engine is a standalone HTTP API with no App dependencies.
-- **D002** (Build order): ✅ M001 builds Engine first as specified. App canvas (M002) and Export/Deploy (M003) are deferred.
-- **D003** (Post-processing replaces regex): ✅ Superseded as documented. postprocess_svg() provides structured PathInfo objects.
-- **D004** (Multi-stage Docker build): ✅ Implemented exactly as specified — builder compiles pypotrace, runtime uses slim image with only runtime libs.
-
-No unaddressed requirements exist.
-
-## Verdict Rationale
-**Verdict: PASS**
-
-All three slices delivered exactly what the roadmap specified:
-
-1. **S01** — Core pipeline with preprocessing + dual vectorization modes (Potrace/VTracer) via POST /engine/trace. 76 tests established the foundation.
-
-2. **S02** — Full post-processing (RDP simplification, island detection, open path repair) with three output format generators (SVG, DXF, JSON). /engine/simplify endpoint added. Test suite grew to 169.
-
-3. **S03** — 5 tuned presets with merge-based param resolution, GET /engine/presets endpoint, and multi-stage Docker image with healthcheck. Final test suite: 196 tests, all passing in under 1 second.
-
-**Evidence is strong:**
-- 196 tests pass (verified by live test run, 0.96s, exit 0)
-- All source files exist on disk with expected structure
-- All 4 API endpoints confirmed in routes.py
-- All 5 preset configs verified with correct JSON structure
-- Dockerfile exists with multi-stage build and HEALTHCHECK
-- Cross-slice integration points align — no boundary mismatches
-- All 4 architectural decisions (D001–D004) are satisfied
-- UAT artifacts exist for all 3 slices with comprehensive test cases
-
-No gaps, regressions, or missing deliverables found. The milestone is ready for completion.

.gsd/milestones/M001/slices/S01/S01-PLAN.md

@@ -1,62 +0,0 @@
-# S01: Core Pipeline — Preprocessing + Vectorization
-
-**Goal:** Stand up FastAPI server with OpenCV preprocessing pipeline and dual-mode vectorization (Potrace + VTracer). Establish the repo structure, dependencies, and core /engine/trace endpoint.
-**Demo:** After this: POST /engine/trace with a PNG logo returns valid SVG using both Potrace and VTracer modes
-
-## Tasks
-- [x] **T01: Created engine/ Python project with FastAPI skeleton, all dependencies installed and verified** — 1. Create the repo directory structure at /vmPool/r/repos/xpltdco/kerf/
-2. Set up engine/ as a Python project with pyproject.toml
-3. Pin dependencies: fastapi, uvicorn, opencv-python-headless, pypotrace, vtracer, python-multipart, Pillow
-4. Create engine/main.py with FastAPI app skeleton
-5. Create engine/requirements.txt or use pyproject.toml deps
-6. Add .gitignore, initial README.md
-7. Verify: pip install works, uvicorn starts the empty app
-  - Estimate: 30min
-  - Files: engine/pyproject.toml, engine/main.py, engine/requirements.txt, .gitignore, README.md
-  - Verify: cd engine && pip install -e . && uvicorn main:app --host 0.0.0.0 --port 8000 & sleep 3 && curl -s http://localhost:8000/docs | head -20
-- [x] **T02: OpenCV preprocessing pipeline** — 1. Create engine/pipeline/preprocessing.py
-2. Implement preprocessing stages in order:
-   - Grayscale conversion
-   - Denoise (bilateral filter, tunable d/sigmaColor/sigmaSpace)
-   - Contrast enhancement (CLAHE, tunable clipLimit/tileGridSize)
-   - Threshold (Otsu auto-threshold default, manual override)
-   - Edge detection (optional Canny, tunable thresholds)
-   - Morphological ops (dilation/erosion, tunable kernel size/iterations)
-3. Each stage tunable via parameters dict
-4. Pipeline accepts raw image bytes, returns processed numpy array
-5. Add unit tests for each stage
-  - Estimate: 45min
-  - Files: engine/pipeline/__init__.py, engine/pipeline/preprocessing.py, engine/tests/test_preprocessing.py
-  - Verify: cd engine && python -m pytest tests/test_preprocessing.py -v
-- [x] **T03: Potrace vectorization (Mode A)** — 1. Create engine/pipeline/vectorize.py
-2. Implement potrace_trace() function:
-   - Accepts preprocessed numpy array (binary image)
-   - Calls pypotrace with tunable params: turdsize, alphamax, opticurve, opttolerance
-   - Returns SVG string
-3. Handle potrace bitmap creation from numpy array
-4. Test with a clean high-contrast test image
-5. Verify SVG output is well-formed
-  - Estimate: 45min
-  - Files: engine/pipeline/vectorize.py, engine/tests/test_vectorize.py, engine/tests/fixtures/
-  - Verify: cd engine && python -m pytest tests/test_vectorize.py -v -k potrace
-- [x] **T04: VTracer vectorization (Mode B)** — 1. Add VTracer tracing to engine/pipeline/vectorize.py
-2. Implement vtracer_trace() function:
-   - Accepts preprocessed image (can be color for VTracer)
-   - Calls vtracer with tunable params: colormode, hierarchical, filter_speckle, color_precision, layer_difference, corner_threshold, length_threshold, splice_threshold
-   - Returns SVG string
-3. Research vtracer Python bindings — may need vtracer pip package or subprocess
-4. Test with photographic/noisy input
-5. Compare Mode A vs Mode B output on same input
-  - Estimate: 45min
-  - Files: engine/pipeline/vectorize.py, engine/tests/test_vectorize.py
-  - Verify: cd engine && python -m pytest tests/test_vectorize.py -v -k vtracer
-- [x] **T05: Wired POST /engine/trace endpoint with preprocess + vectorize pipeline, SVG metadata, and 14 integration tests** — 1. Create engine/api/routes.py with trace endpoint
-2. POST /engine/trace accepts multipart/form-data:
-   - file (image), mode (potrace|vtracer), output_format (svg only for now), preset (ignored for now), params (JSON override)
-3. Wire pipeline: receive file → preprocess → vectorize (mode-dependent) → return SVG + metadata
-4. Response shape: {output: '<svg>...', format: 'svg', metadata: {path_count, node_count_total, open_paths, warnings, processing_ms}}
-5. Add basic metadata extraction from SVG output
-6. Integration test: upload PNG → get SVG back
-  - Estimate: 45min
-  - Files: engine/api/__init__.py, engine/api/routes.py, engine/main.py, engine/tests/test_api.py
-  - Verify: cd engine && python -m pytest tests/test_api.py -v

.gsd/milestones/M001/slices/S01/S01-SUMMARY.md

@@ -1,77 +0,0 @@
----
-id: S01
-milestone: M001
-status: complete
-tasks_completed: 5
-tasks_total: 5
-completed_at: 2026-03-26T04:30:00.000Z
----
-
-# S01: Core Pipeline — Preprocessing + Vectorization
-
-## Goal
-Stand up FastAPI server with OpenCV preprocessing pipeline and dual-mode vectorization (Potrace + VTracer). Establish the repo structure, dependencies, and core /engine/trace endpoint.
-
-## Outcome
-All 5 tasks completed successfully. The engine accepts PNG uploads via POST /engine/trace and returns SVG output with metadata using either Potrace or VTracer mode. Full test suite: 76 tests passing.
-
-## What Was Built
-
-### T01: Project Scaffold
-Created engine/ Python project with FastAPI skeleton, pyproject.toml, all dependencies (fastapi, uvicorn, opencv-python-headless, pypotrace, vtracer, python-multipart, Pillow). Verified uvicorn starts cleanly.
-
-### T02: OpenCV Preprocessing Pipeline
-Implemented `engine/pipeline/preprocessing.py` with full pipeline: grayscale conversion, bilateral filter denoise, CLAHE contrast enhancement, Otsu thresholding, optional Canny edge detection, morphological operations. All stages tunable via parameters dict.
-
-### T03: Potrace Vectorization (Mode A)
-Implemented `potrace_trace()` in `engine/pipeline/vectorize.py`. Converts preprocessed binary images to SVG via pypotrace with tunable params (turdsize, alphamax, opticurve, opttolerance).
-
-### T04: VTracer Vectorization (Mode B)
-Implemented `vtracer_trace()` in `engine/pipeline/vectorize.py`. Converts grayscale or color images to SVG via vtracer Python bindings with tunable params (colormode, filter_speckle, color_precision, etc.).
-
-### T05: API Endpoint + Integration Tests
-Created `engine/api/routes.py` with POST /engine/trace endpoint. Accepts multipart form-data (file, mode, output_format, preset, params). Returns JSON with SVG output and metadata (path_count, node_count_total, open_paths, processing_ms, warnings). 14 integration tests covering both modes, metadata shape, custom params, and validation errors.
-
-## Key Files
-- `engine/main.py` — FastAPI app entry point
-- `engine/api/routes.py` — /engine/trace endpoint
-- `engine/pipeline/preprocessing.py` — OpenCV preprocessing pipeline
-- `engine/pipeline/vectorize.py` — Potrace + VTracer vectorization
-- `engine/tests/` — 76 tests (unit + integration)
-
-## Key Decisions
-- SVG metadata extraction via regex (lightweight, no XML parser dependency)
-- Vectorize params filtered by known param names per mode
-- Bilateral filter chosen over Gaussian for edge-preserving denoise
-- CLAHE for contrast rather than simple histogram equalization
-
-## Verification
-Full test suite: `cd engine && .venv/bin/python -m pytest tests/ -v` — 76 passed
-
-## Demo
-POST /engine/trace with a PNG logo returns valid SVG using both Potrace and VTracer modes.
-
-## Known Limitations
-- Output format is SVG-only — DXF and JSON deferred to S02
-- `preset` parameter accepted but ignored — preset system deferred to S03
-- No Docker packaging yet — deferred to S03
-- Tests must run with `.venv/bin/python -m pytest`, not bare `python`
-
-## Forward Intelligence
-
-### What the next slice should know
-- Response shape: `{output: str, format: str, metadata: {path_count, node_count_total, open_paths, warnings, processing_ms}}`. S02 must extend for DXF/JSON without breaking this contract.
-- VTracer returns SVG with XML declaration + generator comment; Potrace's `_path_to_svg()` returns bare SVG. Post-processing must handle both.
-- User params are filtered by known names per mode in routes.py lines 80-91. New params for S02 post-processing stages must be added to these filter lists.
-
-### What's fragile
-- `_extract_svg_metadata()` regex assumes `<path d="...">` — if output format changes, metadata counts silently return 0.
-- pypotrace Bitmap requires uint32 data — feeding other dtypes directly will segfault (see L003 in KNOWLEDGE.md).
-
-### Authoritative diagnostics
-- `engine/.venv/bin/python -m pytest tests/ -v` — full pipeline health check, runs in <1s.
-- `GET /health` returns `{"status": "ok"}` — confirms FastAPI is running.
-
-### What assumptions changed
-- VTracer Python bindings work via `convert_raw_image_to_svg()` with PNG bytes — no subprocess needed (original plan suggested subprocess might be required).
-- Test images are generated programmatically via numpy, not loaded from fixture files.

.gsd/milestones/M001/slices/S01/S01-UAT.md

@@ -1,122 +0,0 @@
-# S01: Core Pipeline — Preprocessing + Vectorization — UAT
-
-**Milestone:** M001
-**Written:** 2026-03-26
-
-## UAT Type
-
-- UAT mode: artifact-driven
-- Why this mode is sufficient: All pipeline stages are pure functions with deterministic output from synthetic inputs. The 76 automated tests cover the full pipeline from raw bytes to SVG response. No live runtime or human-visual judgment is needed at this stage.
-
-## Preconditions
-
-- Python venv is set up: `engine/.venv/bin/python` exists
-- All dependencies installed: `cd engine && .venv/bin/python -c "import cv2, potrace, vtracer, fastapi"` exits 0
-- System C libraries present: `dpkg -l libpotrace-dev libagg-dev pkg-config` shows installed
-
-## Smoke Test
-
-```bash
-cd engine && .venv/bin/python -m pytest tests/ -v --tb=short
-```
-**Expected:** 76 passed, 0 failed, 0 errors. Exit code 0.
-
-## Test Cases
-
-### 1. Full test suite passes
-
-1. `cd engine && .venv/bin/python -m pytest tests/ -v`
-2. **Expected:** 76 tests pass — 24 preprocessing, 38 vectorize, 14 API integration
-
-### 2. Potrace mode produces valid SVG from PNG
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_api.py::TestTraceEndpointPotrace -v`
-2. **Expected:** 4 tests pass — basic trace returns SVG, metadata has correct shape, SVG contains `<path>` elements, custom params are accepted
-
-### 3. VTracer mode produces valid SVG from PNG
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_api.py::TestTraceEndpointVtracer -v`
-2. **Expected:** 3 tests pass — basic trace returns SVG, metadata present, custom params accepted
-
-### 4. Validation rejects bad input
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_api.py::TestTraceEndpointValidation -v`
-2. **Expected:** 7 tests pass — invalid mode (422), unsupported output format (422), invalid params JSON (422), empty file (422), corrupt image (422), defaults to potrace, preset ignored
-
-### 5. Preprocessing pipeline stages are individually testable
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_preprocessing.py -v`
-2. **Expected:** 24 tests pass covering decode, grayscale, denoise, CLAHE, threshold, edge detect, morphological ops, and full pipeline composition
-
-### 6. Potrace and VTracer produce different output from same input
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_vectorize.py::TestVtracerVsPotraceComparison -v`
-2. **Expected:** 2 tests pass — both produce valid SVG from same input, outputs differ
-
-### 7. API response shape matches contract
-
-1. `cd engine && .venv/bin/python -c "
-from fastapi.testclient import TestClient
-from main import app
-import numpy as np, cv2, json
-client = TestClient(app)
-img = np.zeros((100,100,3), dtype=np.uint8)
-cv2.rectangle(img, (20,20), (80,80), (255,255,255), -1)
-_, buf = cv2.imencode('.png', img)
-r = client.post('/engine/trace', files={'file': ('test.png', buf.tobytes(), 'image/png')})
-data = r.json()
-assert r.status_code == 200
-assert set(data.keys()) == {'output', 'format', 'metadata'}
-assert data['format'] == 'svg'
-assert set(data['metadata'].keys()) == {'path_count', 'node_count_total', 'open_paths', 'warnings', 'processing_ms'}
-assert isinstance(data['metadata']['processing_ms'], float)
-assert '<svg' in data['output']
-print('PASS: response shape matches contract')
-"
-2. **Expected:** Prints "PASS: response shape matches contract", exit code 0
-
-## Edge Cases
-
-### Empty file upload
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_api.py::TestTraceEndpointValidation::test_empty_file -v`
-2. **Expected:** Returns 422 with "Uploaded file is empty"
-
-### Corrupt image bytes
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_api.py::TestTraceEndpointValidation::test_corrupt_image -v`
-2. **Expected:** Returns 422 with "Preprocessing failed" message
-
-### All-black and all-white images
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_vectorize.py -v -k "all_black or all_white"`
-2. **Expected:** 4 tests pass — both Potrace and VTracer handle degenerate inputs without crashing
-
-### Potrace rejects 3D input
-
-1. `cd engine && .venv/bin/python -m pytest tests/test_vectorize.py::TestPotraceEdgeCases::test_rejects_3d_input -v`
-2. **Expected:** Passes — potrace_trace raises ValueError for non-2D input
-
-## Failure Signals
-
-- Any test failure in the 76-test suite indicates a regression
-- `import potrace` failing means system C libraries are missing (see L001 in KNOWLEDGE.md)
-- `import vtracer` failing means the vtracer pip package wasn't installed
-- API returning 500 on valid PNG input indicates a pipeline wiring issue
-- Metadata with all zeros (path_count=0) on a non-trivial image suggests SVG format changed
-
-## Not Proven By This UAT
-
-- Output visual quality — no human evaluation of SVG fidelity vs source image
-- Performance under load — no concurrency or stress testing
-- DXF/JSON output formats — deferred to S02
-- Preset system behavior — deferred to S03
-- Docker containerized deployment — deferred to S03
-- Real-world image quality (photos, logos with gradients, low-res scans)
-
-## Notes for Tester
-
-- All tests must be run with `.venv/bin/python -m pytest`, not bare `python` — there is no system-wide Python on PATH.
-- Working directory must be `engine/` for imports to resolve correctly.
-- Test images are generated programmatically (numpy arrays), no external fixture files needed.
-- Processing times in metadata will vary by machine but should be under 100ms for test images.

.gsd/milestones/M001/slices/S01/tasks/T01-PLAN.md

@@ -1,30 +0,0 @@
----
-estimated_steps: 7
-estimated_files: 5
-skills_used: []
----
-
-# T01: Repository scaffolding + Engine project setup
-
-1. Create the repo directory structure at /vmPool/r/repos/xpltdco/kerf/
-2. Set up engine/ as a Python project with pyproject.toml
-3. Pin dependencies: fastapi, uvicorn, opencv-python-headless, pypotrace, vtracer, python-multipart, Pillow
-4. Create engine/main.py with FastAPI app skeleton
-5. Create engine/requirements.txt or use pyproject.toml deps
-6. Add .gitignore, initial README.md
-7. Verify: pip install works, uvicorn starts the empty app
-
-## Inputs
-
-- `GSD-INITIATE.md`
-
-## Expected Output
-
-- `engine/pyproject.toml`
-- `engine/main.py`
-- `engine/.gitignore`
-- `README.md`
-
-## Verification
-
-cd engine && pip install -e . && uvicorn main:app --host 0.0.0.0 --port 8000 & sleep 3 && curl -s http://localhost:8000/docs | head -20

.gsd/milestones/M001/slices/S01/tasks/T01-SUMMARY.md

@@ -1,82 +0,0 @@
----
-id: T01
-parent: S01
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: ["engine/pyproject.toml", "engine/main.py", "engine/.gitignore", "README.md"]
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: "pip install -e .[dev] succeeded. uvicorn starts, /docs returns Swagger UI, /health returns ok."
-completed_at: 2026-03-26T04:07:03.124Z
-blocker_discovered: false
----
-
-# T01: Created engine/ Python project with FastAPI skeleton, all dependencies installed and verified
-
-> Created engine/ Python project with FastAPI skeleton, all dependencies installed and verified
-
-## What Happened
----
-id: T01
-parent: S01
-milestone: M001
-key_files:
-  - engine/pyproject.toml
-  - engine/main.py
-  - engine/.gitignore
-  - README.md
-key_decisions:
-  - (none)
-duration: ""
-verification_result: passed
-completed_at: 2026-03-26T04:07:03.137Z
-blocker_discovered: false
----
-
-# T01: Created engine/ Python project with FastAPI skeleton, all dependencies installed and verified
-
-**Created engine/ Python project with FastAPI skeleton, all dependencies installed and verified**
-
-## What Happened
-
-Created engine/ directory structure with subdirectories for pipeline/, api/, and tests/fixtures/. Set up pyproject.toml with setuptools build backend, all required dependencies pinned, and dev extras. Created main.py with a FastAPI app skeleton exposing /health and /docs. Installed system C libraries for pypotrace.
-
-## Verification
-
-pip install -e .[dev] succeeded. uvicorn starts, /docs returns Swagger UI, /health returns ok.
-
-## Verification Evidence
-
-| # | Command | Exit Code | Verdict | Duration |
-|---|---------|-----------|---------|----------|
-| 1 | `pip install -e .[dev]` | 0 | pass | 45000ms |
-| 2 | `curl http://localhost:8000/docs` | 0 | pass | 500ms |
-| 3 | `curl http://localhost:8000/health` | 0 | pass | 200ms |
-
-
-## Deviations
-
-Adapted repo path from /vmPool/r/repos/xpltdco/kerf/ to working directory. Installed system packages for pypotrace.
-
-## Known Issues
-
-pypotrace requires system C deps (libpotrace-dev, libagg-dev, pkg-config) — must be in Docker image.
-
-## Files Created/Modified
-
-- `engine/pyproject.toml`
-- `engine/main.py`
-- `engine/.gitignore`
-- `README.md`
-
-
-## Deviations
-Adapted repo path from /vmPool/r/repos/xpltdco/kerf/ to working directory. Installed system packages for pypotrace.
-
-## Known Issues
-pypotrace requires system C deps (libpotrace-dev, libagg-dev, pkg-config) — must be in Docker image.

.gsd/milestones/M001/slices/S01/tasks/T01-VERIFY.json

@@ -1,30 +0,0 @@
-{
-  "schemaVersion": 1,
-  "taskId": "T01",
-  "unitId": "M001/S01/T01",
-  "timestamp": 1774498036068,
-  "passed": false,
-  "discoverySource": "task-plan",
-  "checks": [
-    {
-      "command": "cd engine",
-      "exitCode": 0,
-      "durationMs": 5,
-      "verdict": "pass"
-    },
-    {
-      "command": "pip install -e .",
-      "exitCode": 1,
-      "durationMs": 344,
-      "verdict": "fail"
-    },
-    {
-      "command": "uvicorn main:app --host 0.0.0.0 --port 8000 & sleep 3",
-      "exitCode": 0,
-      "durationMs": 3006,
-      "verdict": "pass"
-    }
-  ],
-  "retryAttempt": 1,
-  "maxRetries": 2
-}

.gsd/milestones/M001/slices/S01/tasks/T02-PLAN.md

@@ -1,32 +0,0 @@
----
-estimated_steps: 11
-estimated_files: 3
-skills_used: []
----
-
-# T02: OpenCV preprocessing pipeline
-
-1. Create engine/pipeline/preprocessing.py
-2. Implement preprocessing stages in order:
-   - Grayscale conversion
-   - Denoise (bilateral filter, tunable d/sigmaColor/sigmaSpace)
-   - Contrast enhancement (CLAHE, tunable clipLimit/tileGridSize)
-   - Threshold (Otsu auto-threshold default, manual override)
-   - Edge detection (optional Canny, tunable thresholds)
-   - Morphological ops (dilation/erosion, tunable kernel size/iterations)
-3. Each stage tunable via parameters dict
-4. Pipeline accepts raw image bytes, returns processed numpy array
-5. Add unit tests for each stage
-
-## Inputs
-
-- `GSD-INITIATE.md`
-
-## Expected Output
-
-- `engine/pipeline/preprocessing.py`
-- `engine/tests/test_preprocessing.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_preprocessing.py -v

.gsd/milestones/M001/slices/S01/tasks/T02-SUMMARY.md

@@ -1,22 +0,0 @@
----
-id: T02
-parent: S01
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: []
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: ""
-completed_at: 
-blocker_discovered: false
----
-
-# T02: OpenCV preprocessing pipeline
-
-## What Happened
-No summary recorded.

.gsd/milestones/M001/slices/S01/tasks/T03-PLAN.md

@@ -1,29 +0,0 @@
----
-estimated_steps: 8
-estimated_files: 3
-skills_used: []
----
-
-# T03: Potrace vectorization (Mode A)
-
-1. Create engine/pipeline/vectorize.py
-2. Implement potrace_trace() function:
-   - Accepts preprocessed numpy array (binary image)
-   - Calls pypotrace with tunable params: turdsize, alphamax, opticurve, opttolerance
-   - Returns SVG string
-3. Handle potrace bitmap creation from numpy array
-4. Test with a clean high-contrast test image
-5. Verify SVG output is well-formed
-
-## Inputs
-
-- `engine/pipeline/preprocessing.py`
-
-## Expected Output
-
-- `engine/pipeline/vectorize.py`
-- `engine/tests/test_vectorize.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_vectorize.py -v -k potrace

.gsd/milestones/M001/slices/S01/tasks/T03-SUMMARY.md

@@ -1,22 +0,0 @@
----
-id: T03
-parent: S01
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: []
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: ""
-completed_at: 
-blocker_discovered: false
----
-
-# T03: Potrace vectorization (Mode A)
-
-## What Happened
-No summary recorded.

.gsd/milestones/M001/slices/S01/tasks/T04-PLAN.md

@@ -1,28 +0,0 @@
----
-estimated_steps: 8
-estimated_files: 2
-skills_used: []
----
-
-# T04: VTracer vectorization (Mode B)
-
-1. Add VTracer tracing to engine/pipeline/vectorize.py
-2. Implement vtracer_trace() function:
-   - Accepts preprocessed image (can be color for VTracer)
-   - Calls vtracer with tunable params: colormode, hierarchical, filter_speckle, color_precision, layer_difference, corner_threshold, length_threshold, splice_threshold
-   - Returns SVG string
-3. Research vtracer Python bindings — may need vtracer pip package or subprocess
-4. Test with photographic/noisy input
-5. Compare Mode A vs Mode B output on same input
-
-## Inputs
-
-- `engine/pipeline/preprocessing.py`
-
-## Expected Output
-
-- `engine/pipeline/vectorize.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_vectorize.py -v -k vtracer

.gsd/milestones/M001/slices/S01/tasks/T04-SUMMARY.md

@@ -1,22 +0,0 @@
----
-id: T04
-parent: S01
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: []
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: ""
-completed_at: 
-blocker_discovered: false
----
-
-# T04: VTracer vectorization (Mode B)
-
-## What Happened
-No summary recorded.

.gsd/milestones/M001/slices/S01/tasks/T05-PLAN.md

@@ -1,29 +0,0 @@
----
-estimated_steps: 7
-estimated_files: 4
-skills_used: []
----
-
-# T05: Wire up /engine/trace endpoint
-
-1. Create engine/api/routes.py with trace endpoint
-2. POST /engine/trace accepts multipart/form-data:
-   - file (image), mode (potrace|vtracer), output_format (svg only for now), preset (ignored for now), params (JSON override)
-3. Wire pipeline: receive file → preprocess → vectorize (mode-dependent) → return SVG + metadata
-4. Response shape: {output: '<svg>...', format: 'svg', metadata: {path_count, node_count_total, open_paths, warnings, processing_ms}}
-5. Add basic metadata extraction from SVG output
-6. Integration test: upload PNG → get SVG back
-
-## Inputs
-
-- `engine/pipeline/preprocessing.py`
-- `engine/pipeline/vectorize.py`
-
-## Expected Output
-
-- `engine/api/routes.py`
-- `engine/tests/test_api.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_api.py -v

.gsd/milestones/M001/slices/S01/tasks/T05-SUMMARY.md

@@ -1,77 +0,0 @@
----
-id: T05
-parent: S01
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: ["engine/api/routes.py", "engine/tests/test_api.py", "engine/main.py"]
-key_decisions: ["SVG metadata via regex - lightweight, no XML parser needed", "Vectorize params filtered by known param names per mode"]
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: "cd engine && .venv/bin/python -m pytest tests/test_api.py -v (14 passed), full suite 76 passed"
-completed_at: 2026-03-26T04:21:26.227Z
-blocker_discovered: false
----
-
-# T05: Wired POST /engine/trace endpoint with preprocess + vectorize pipeline, SVG metadata, and 14 integration tests
-
-> Wired POST /engine/trace endpoint with preprocess + vectorize pipeline, SVG metadata, and 14 integration tests
-
-## What Happened
----
-id: T05
-parent: S01
-milestone: M001
-key_files:
-  - engine/api/routes.py
-  - engine/tests/test_api.py
-  - engine/main.py
-key_decisions:
-  - SVG metadata via regex - lightweight, no XML parser needed
-  - Vectorize params filtered by known param names per mode
-duration: ""
-verification_result: passed
-completed_at: 2026-03-26T04:21:26.233Z
-blocker_discovered: false
----
-
-# T05: Wired POST /engine/trace endpoint with preprocess + vectorize pipeline, SVG metadata, and 14 integration tests
-
-**Wired POST /engine/trace endpoint with preprocess + vectorize pipeline, SVG metadata, and 14 integration tests**
-
-## What Happened
-
-Created engine/api/routes.py with POST /engine/trace endpoint accepting multipart form-data (file, mode, output_format, preset, params). Wires full pipeline: decode → preprocess → vectorize (potrace or vtracer) → extract SVG metadata → return JSON. Updated main.py to include the router. Created 14 integration tests covering both modes, metadata shape, custom params, and validation errors.
-
-## Verification
-
-cd engine && .venv/bin/python -m pytest tests/test_api.py -v (14 passed), full suite 76 passed
-
-## Verification Evidence
-
-| # | Command | Exit Code | Verdict | Duration |
-|---|---------|-----------|---------|----------|
-| 1 | `cd engine && .venv/bin/python -m pytest tests/test_api.py -v` | 0 | ✅ pass | 430ms |
-| 2 | `cd engine && .venv/bin/python -m pytest tests/ -v` | 0 | ✅ pass | 470ms |
-
-
-## Deviations
-
-None.
-
-## Known Issues
-
-None.
-
-## Files Created/Modified
-
-- `engine/api/routes.py`
-- `engine/tests/test_api.py`
-- `engine/main.py`
-
-
-## Deviations
-None.

.gsd/milestones/M001/slices/S01/tasks/T05-VERIFY.json

@@ -1,24 +0,0 @@
-{
-  "schemaVersion": 1,
-  "taskId": "T05",
-  "unitId": "M001/S01/T05",
-  "timestamp": 1774498959785,
-  "passed": false,
-  "discoverySource": "task-plan",
-  "checks": [
-    {
-      "command": "cd engine",
-      "exitCode": 0,
-      "durationMs": 5,
-      "verdict": "pass"
-    },
-    {
-      "command": "python -m pytest tests/test_api.py -v",
-      "exitCode": 127,
-      "durationMs": 4,
-      "verdict": "fail"
-    }
-  ],
-  "retryAttempt": 1,
-  "maxRetries": 2
-}

.gsd/milestones/M001/slices/S02/S02-PLAN.md

@@ -1,47 +0,0 @@
-# S02: Post-Processing + Output Formats (SVG, DXF, JSON)
-
-**Goal:** Add post-processing (RDP simplification, island detection, open path repair, node counting) and all three output formats (SVG, DXF, JSON) plus the /engine/simplify endpoint.
-**Demo:** After this: /engine/trace returns valid DXF and JSON output; /engine/simplify reduces node count on complex SVG
-
-## Tasks
-- [x] **T01: Post-processing: RDP simplification, island detection, open path repair** — 1. Create engine/pipeline/postprocess.py
-2. Implement RDP path simplification:
-   - Parse SVG path data into coordinate arrays
-   - Apply Ramer-Douglas-Peucker algorithm with tunable epsilon
-   - Return simplified path data
-3. Implement island detection:
-   - Identify interior counter paths (holes in letters, enclosed shapes)
-   - Flag with metadata for proper DXF nesting
-4. Implement open path detection:
-   - Check if path start/end points match
-   - Flag open paths in metadata
-   - Optional auto-close with straight line segment
-5. Implement node count reporting per path
-6. Unit tests for each function
-  - Estimate: 60min
-  - Files: engine/pipeline/postprocess.py, engine/tests/test_postprocess.py
-  - Verify: cd engine && python -m pytest tests/test_postprocess.py -v
-- [x] **T02: Output format generators: DXF (AC1015+), JSON, SVG** — 1. Create engine/output/dxf.py
-2. Generate AC1015+ DXF format:
-   - Use ezdxf library (Python-native, well-maintained)
-   - Convert SVG path data to DXF LWPOLYLINE/SPLINE entities
-   - Handle bezier curves → polyline approximation
-   - Proper island/counter-path nesting
-3. Create engine/output/json_output.py
-4. JSON format: array of path objects with bezier/polyline commands
-5. Update engine/output/svg.py for clean SVG serialization
-6. Test DXF output opens in Inkscape (if available) or validate structure
-  - Estimate: 90min
-  - Files: engine/output/__init__.py, engine/output/dxf.py, engine/output/json_output.py, engine/output/svg.py, engine/tests/test_output.py
-  - Verify: cd engine && python -m pytest tests/test_output.py -v
-- [x] **T03: Wire post-processing into /engine/trace, add output_format routing for svg/dxf/json, and create /engine/simplify endpoint with 35 passing integration tests** — 1. Integrate post-processing into /engine/trace pipeline
-2. Add output_format parameter routing (svg/dxf/json)
-3. Create /engine/simplify endpoint:
-   - Accepts SVG file upload + epsilon + output_format
-   - Parses SVG, applies RDP simplification, outputs result
-   - Same response shape as /engine/trace
-4. Update metadata to include all fields: format, path_count, node_count_total, open_paths, warnings, processing_ms
-5. Integration tests for all format combinations
-  - Estimate: 45min
-  - Files: engine/api/routes.py, engine/tests/test_api.py
-  - Verify: cd engine && python -m pytest tests/test_api.py -v

.gsd/milestones/M001/slices/S02/S02-SUMMARY.md

@@ -1,112 +0,0 @@
----
-id: S02
-parent: M001
-milestone: M001
-provides:
-  - postprocess_svg() function for RDP simplification + island detection + node counting
-  - Output generators: generate_dxf(), generate_json(), generate_svg()
-  - /engine/simplify endpoint for SVG-to-SVG/DXF/JSON simplification
-  - output_format routing on /engine/trace (svg, dxf, json)
-  - _format_response() pattern for consistent multi-format responses
-requires:
-  - slice: S01
-    provides: Core pipeline: preprocessing + potrace_trace() + vtracer_trace() producing raw SVG output
-affects:
-  - S03
-key_files:
-  - engine/pipeline/postprocess.py
-  - engine/output/dxf.py
-  - engine/output/json_output.py
-  - engine/output/svg.py
-  - engine/output/__init__.py
-  - engine/api/routes.py
-  - engine/tests/test_postprocess.py
-  - engine/tests/test_output.py
-  - engine/tests/test_api.py
-key_decisions:
-  - DXF output as raw bytes with application/dxf content-type and metadata in X-Kerf-Metadata header
-  - postprocess_svg() replaces regex metadata extraction — full XML path parsing for structured PathInfo objects
-  - _format_response() shared helper for consistent response shaping across endpoints
-  - Islands placed on separate ISLANDS layer in DXF for downstream CAM tool compatibility
-  - Bezier curves linearized during post-processing for RDP simplification and DXF polyline generation
-patterns_established:
-  - PostProcessResult as the universal intermediate representation consumed by all output generators
-  - Output generators are pure functions: PostProcessResult → bytes/string, no side effects
-  - _format_response() pattern for consistent multi-format API responses with metadata
-observability_surfaces:
-  - Metadata in every API response: path_count, node_count_total, open_paths, island_count, warnings, processing_ms
-  - X-Kerf-Metadata header on DXF responses carries the same metadata as JSON envelope responses
-drill_down_paths:
-  - .gsd/milestones/M001/slices/S02/tasks/T01-SUMMARY.md
-  - .gsd/milestones/M001/slices/S02/tasks/T02-SUMMARY.md
-  - .gsd/milestones/M001/slices/S02/tasks/T03-SUMMARY.md
-duration: ""
-verification_result: passed
-completed_at: 2026-03-26T04:41:57.970Z
-blocker_discovered: false
----
-
-# S02: Post-Processing + Output Formats (SVG, DXF, JSON)
-
-**Full post-processing pipeline (RDP simplification, island detection, open path repair) with three output format generators (SVG, DXF, JSON) and /engine/simplify endpoint — 169 tests passing.**
-
-## What Happened
-
-This slice added the complete post-processing layer and output format system to the Kerf Engine pipeline.
-
-**T01 — Post-processing module** (`engine/pipeline/postprocess.py`, 414 lines): Built the core `postprocess_svg()` function that parses raw SVG output from vectorizers into structured `PathInfo` objects. Implements: (1) SVG path d-attribute parsing supporting M, L, C, Q, Z, H, V commands with relative variants; (2) Ramer-Douglas-Peucker simplification with tunable epsilon; (3) Island detection via signed-area calculation (negative area = clockwise winding = interior hole); (4) Open path detection by comparing start/end coordinates; (5) Per-path and aggregate node counting. The `PostProcessResult` dataclass carries all structured data downstream to output generators.
-
-**T02 — Output format generators** (`engine/output/`): Created three format generators consuming `PostProcessResult`. DXF generator (`dxf.py`, 66 lines) uses ezdxf to create AC1015 (AutoCAD R2000) documents with LWPOLYLINE entities — islands go on an "ISLANDS" layer, outer contours on layer "0", and closed paths get the polyline close flag. JSON generator (`json_output.py`, 76 lines) outputs structured path arrays with M/L/Z commands and per-path properties (is_closed, is_island, area, node_count). SVG generator (`svg.py`, 22 lines) returns the simplified SVG string from PostProcessResult.
-
-**T03 — API integration** (`engine/api/routes.py`, 175 lines): Wired post-processing into `/engine/trace` after vectorization. Added `output_format` parameter routing (svg/dxf/json). Created `/engine/simplify` endpoint accepting SVG upload + epsilon + output_format. Built `_format_response()` shared helper for consistent response shaping. DXF returns raw bytes with `application/dxf` content type and metadata in `X-Kerf-Metadata` header. SVG and JSON return JSON envelopes with output + metadata. Wrote 35 integration tests covering all format combinations for both endpoints.
-
-## Verification
-
-All verification runs use `.venv/bin/python -m pytest` per project pattern P002.
-
-- `engine/tests/test_postprocess.py`: Tests for RDP simplification, island detection, open path detection, SVG parsing, node counting — all pass.
-- `engine/tests/test_output.py`: Tests for DXF structure (AC1015, LWPOLYLINE entities, closed flags, island layers), JSON structure (path commands, metadata), SVG output, round-trip consistency — all pass.
-- `engine/tests/test_api.py`: 35 integration tests covering /engine/trace (SVG, JSON, DXF output for potrace and vtracer modes, validation errors) and /engine/simplify (SVG, JSON, DXF output, validation errors, epsilon defaults) — all pass.
-- Full suite: 169 tests pass in 0.92s with only ezdxf pyparsing deprecation warnings (harmless).
-
-## Requirements Advanced
-
-None.
-
-## Requirements Validated
-
-None.
-
-## New Requirements Surfaced
-
-None.
-
-## Requirements Invalidated or Re-scoped
-
-None.
-
-## Deviations
-
-Replaced the old _extract_svg_metadata() regex-based function entirely with postprocess_svg() pipeline. D003 (regex-based metadata extraction) is now superseded — full XML/path parsing is required for DXF/JSON generation. DXF responses use raw binary Response with X-Kerf-Metadata header instead of a JSON envelope, since DXF is binary data.
-
-## Known Limitations
-
-- Bezier curves (C, Q commands) in SVG paths are sampled to linear segments during post-processing. This means DXF output uses polylines only, not splines. Adequate for CNC/laser use cases but loses mathematical curve precision.
-- RDP simplification operates on linearized coordinates, not on the original bezier control points. Very small epsilon values may not reconstruct the original curve quality.
-- No viewBox/transform matrix handling in SVG path parsing — assumes paths use absolute coordinates in the document space.
-
-## Follow-ups
-
-None.
-
-## Files Created/Modified
-
-- `engine/pipeline/postprocess.py` — New: Post-processing module with RDP simplification, island detection, open path repair, SVG path parsing (414 lines)
-- `engine/output/__init__.py` — New: Package init exporting generate_dxf, generate_json, generate_svg
-- `engine/output/dxf.py` — New: AC1015 DXF generator using ezdxf — LWPOLYLINE entities with island layer separation (66 lines)
-- `engine/output/json_output.py` — New: JSON output generator with path commands and properties (76 lines)
-- `engine/output/svg.py` — New: SVG output generator returning simplified SVG from PostProcessResult (22 lines)
-- `engine/api/routes.py` — Rewritten: integrated postprocess_svg(), output_format routing, /engine/simplify endpoint, _format_response() helper (175 lines)
-- `engine/tests/test_postprocess.py` — New: Tests for RDP, island detection, open paths, SVG parsing, node counting (375 lines)
-- `engine/tests/test_output.py` — New: Tests for DXF structure, JSON structure, SVG output, round-trip consistency (274 lines)
-- `engine/tests/test_api.py` — Rewritten: 35 integration tests for /engine/trace and /engine/simplify across all format combinations (515 lines)

.gsd/milestones/M001/slices/S02/S02-UAT.md

@@ -1,122 +0,0 @@
-# S02: Post-Processing + Output Formats (SVG, DXF, JSON) — UAT
-
-**Milestone:** M001
-**Written:** 2026-03-26T04:41:57.970Z
-
-# S02: Post-Processing + Output Formats (SVG, DXF, JSON) — UAT
-
-**Milestone:** M001
-**Written:** 2026-03-26
-
-## UAT Type
-
-- UAT mode: artifact-driven
-- Why this mode is sufficient: All endpoints return structured data (SVG/DXF/JSON) that can be validated programmatically. 169 automated tests cover functional correctness, format validity, and edge cases.
-
-## Preconditions
-
-- Engine virtualenv exists at `engine/.venv/` with all dependencies installed (ezdxf, numpy, opencv, etc.)
-- Tests run with `cd engine && .venv/bin/python -m pytest tests/ -v` (NOT bare `python` — see P002)
-
-## Smoke Test
-
-```bash
-cd engine && .venv/bin/python -m pytest tests/test_api.py -v
-```
-Expected: 35 tests pass, exit code 0.
-
-## Test Cases
-
-### 1. /engine/trace returns valid SVG with post-processing metadata
-
-1. POST to /engine/trace with a PNG image, mode=potrace, output_format=svg
-2. Check response JSON has `output` (SVG string), `format` ("svg"), `metadata` object
-3. **Expected:** metadata contains path_count > 0, node_count_total > 0, open_paths >= 0, island_count >= 0, processing_ms > 0
-
-### 2. /engine/trace returns valid DXF binary
-
-1. POST to /engine/trace with a PNG image, mode=potrace, output_format=dxf
-2. Check response content-type is "application/dxf"
-3. Check X-Kerf-Metadata header is valid JSON with path_count, node_count_total
-4. Check response body starts with "0\nSECTION" (DXF header)
-5. **Expected:** Valid AC1015 DXF file with LWPOLYLINE entities
-
-### 3. /engine/trace returns valid JSON output
-
-1. POST to /engine/trace with a PNG image, mode=potrace, output_format=json
-2. Check response JSON has `output.paths` array and `output.metadata`
-3. Check each path has `commands` array with M/L/Z entries and `properties` dict
-4. **Expected:** JSON structure with is_closed, is_island, node_count, area per path
-
-### 4. /engine/trace works with VTracer mode
-
-1. POST to /engine/trace with a PNG image, mode=vtracer, output_format=svg
-2. **Expected:** Valid SVG output with metadata, different path structure from potrace
-
-### 5. /engine/simplify reduces node count
-
-1. POST to /engine/simplify with a complex SVG file, epsilon=2.0
-2. Compare node_count_total in response metadata
-3. **Expected:** node_count_total is less than original SVG path node count
-
-### 6. /engine/simplify supports all output formats
-
-1. POST to /engine/simplify with SVG file, output_format=dxf
-2. POST to /engine/simplify with SVG file, output_format=json
-3. POST to /engine/simplify with SVG file, output_format=svg
-4. **Expected:** All three return valid output in their respective formats
-
-### 7. Island detection identifies interior paths
-
-1. Trace or simplify an image/SVG with interior holes (e.g., letter "O" shape)
-2. Check JSON output for paths with `is_island: true`
-3. Check DXF output for entities on the "ISLANDS" layer
-4. **Expected:** Interior counter-paths correctly flagged as islands
-
-## Edge Cases
-
-### Empty file upload
-
-1. POST to /engine/trace with an empty file
-2. **Expected:** HTTP 422 with detail "Uploaded file is empty"
-
-### Invalid output_format
-
-1. POST to /engine/trace with output_format=pdf
-2. **Expected:** HTTP 422 with detail listing valid formats (dxf, json, svg)
-
-### Non-SVG file to /engine/simplify
-
-1. POST to /engine/simplify with a PNG file
-2. **Expected:** HTTP 422 with detail "File does not appear to be a valid SVG"
-
-### Binary file to /engine/simplify
-
-1. POST to /engine/simplify with random binary data
-2. **Expected:** HTTP 422 with detail "File is not valid UTF-8 text"
-
-### Default epsilon on /engine/simplify
-
-1. POST to /engine/simplify without specifying epsilon
-2. **Expected:** Uses default epsilon=1.0, returns valid output
-
-## Failure Signals
-
-- Any test in `test_api.py`, `test_postprocess.py`, or `test_output.py` fails
-- DXF output doesn't start with "0\nSECTION" (malformed DXF)
-- JSON output missing `commands` or `properties` in path objects
-- X-Kerf-Metadata header missing or invalid JSON on DXF responses
-- node_count_total or path_count is 0 for non-trivial inputs
-
-## Not Proven By This UAT
-
-- Visual quality of DXF output in actual CAD software (Inkscape, AutoCAD)
-- Curve fidelity after bezier-to-polyline linearization
-- Performance under large/complex SVG inputs (no load testing)
-- viewBox/transform matrix handling in SVG path parsing
-
-## Notes for Tester
-
-- ezdxf emits pyparsing deprecation warnings during tests — these are harmless library-internal warnings, not bugs
-- Tests generate images programmatically via numpy (pattern P001) — no fixture files needed
-- Always use `.venv/bin/python -m pytest`, never bare `python` (pattern P002)

.gsd/milestones/M001/slices/S02/tasks/T01-PLAN.md

@@ -1,35 +0,0 @@
----
-estimated_steps: 14
-estimated_files: 2
-skills_used: []
----
-
-# T01: Post-processing: RDP simplification, island detection, open path repair
-
-1. Create engine/pipeline/postprocess.py
-2. Implement RDP path simplification:
-   - Parse SVG path data into coordinate arrays
-   - Apply Ramer-Douglas-Peucker algorithm with tunable epsilon
-   - Return simplified path data
-3. Implement island detection:
-   - Identify interior counter paths (holes in letters, enclosed shapes)
-   - Flag with metadata for proper DXF nesting
-4. Implement open path detection:
-   - Check if path start/end points match
-   - Flag open paths in metadata
-   - Optional auto-close with straight line segment
-5. Implement node count reporting per path
-6. Unit tests for each function
-
-## Inputs
-
-- `engine/pipeline/vectorize.py`
-
-## Expected Output
-
-- `engine/pipeline/postprocess.py`
-- `engine/tests/test_postprocess.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_postprocess.py -v

.gsd/milestones/M001/slices/S02/tasks/T01-SUMMARY.md

@@ -1,22 +0,0 @@
----
-id: T01
-parent: S02
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: []
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: ""
-completed_at: 
-blocker_discovered: false
----
-
-# T01: Post-processing: RDP simplification, island detection, open path repair
-
-## What Happened
-No summary recorded.

.gsd/milestones/M001/slices/S02/tasks/T02-PLAN.md

@@ -1,32 +0,0 @@
----
-estimated_steps: 10
-estimated_files: 5
-skills_used: []
----
-
-# T02: Output format generators: DXF (AC1015+), JSON, SVG
-
-1. Create engine/output/dxf.py
-2. Generate AC1015+ DXF format:
-   - Use ezdxf library (Python-native, well-maintained)
-   - Convert SVG path data to DXF LWPOLYLINE/SPLINE entities
-   - Handle bezier curves → polyline approximation
-   - Proper island/counter-path nesting
-3. Create engine/output/json_output.py
-4. JSON format: array of path objects with bezier/polyline commands
-5. Update engine/output/svg.py for clean SVG serialization
-6. Test DXF output opens in Inkscape (if available) or validate structure
-
-## Inputs
-
-- `engine/pipeline/postprocess.py`
-
-## Expected Output
-
-- `engine/output/dxf.py`
-- `engine/output/json_output.py`
-- `engine/output/svg.py`
-
-## Verification
-
-cd engine && python -m pytest tests/test_output.py -v

.gsd/milestones/M001/slices/S02/tasks/T02-SUMMARY.md

@@ -1,22 +0,0 @@
----
-id: T02
-parent: S02
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: []
-key_decisions: []
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: ""
-completed_at: 
-blocker_discovered: false
----
-
-# T02: Output format generators: DXF (AC1015+), JSON, SVG
-
-## What Happened
-No summary recorded.

.gsd/milestones/M001/slices/S02/tasks/T03-PLAN.md

@@ -1,30 +0,0 @@
----
-estimated_steps: 8
-estimated_files: 2
-skills_used: []
----
-
-# T03: Wire post-processing + /engine/simplify endpoint
-
-1. Integrate post-processing into /engine/trace pipeline
-2. Add output_format parameter routing (svg/dxf/json)
-3. Create /engine/simplify endpoint:
-   - Accepts SVG file upload + epsilon + output_format
-   - Parses SVG, applies RDP simplification, outputs result
-   - Same response shape as /engine/trace
-4. Update metadata to include all fields: format, path_count, node_count_total, open_paths, warnings, processing_ms
-5. Integration tests for all format combinations
-
-## Inputs
-
-- `engine/pipeline/postprocess.py`
-- `engine/output/dxf.py`
-- `engine/output/json_output.py`
-
-## Expected Output
-
-- `engine/api/routes.py (updated)`
-
-## Verification
-
-cd engine && python -m pytest tests/test_api.py -v

.gsd/milestones/M001/slices/S02/tasks/T03-SUMMARY.md

@@ -1,79 +0,0 @@
----
-id: T03
-parent: S02
-milestone: M001
-provides: []
-requires: []
-affects: []
-key_files: ["engine/api/routes.py", "engine/tests/test_api.py"]
-key_decisions: ["DXF output returned as raw bytes with application/dxf content-type and metadata in X-Kerf-Metadata header", "JSON output nests generate_json result as parsed object inside envelope", "_format_response() shared helper for consistent response shaping across endpoints"]
-patterns_established: []
-drill_down_paths: []
-observability_surfaces: []
-duration: ""
-verification_result: "All 35 API integration tests pass (cd engine && python -m pytest tests/test_api.py -v). Full suite of 169 tests across all modules pass clean (cd engine && python -m pytest tests/ -v)."
-completed_at: 2026-03-26T04:39:50.412Z
-blocker_discovered: false
----
-
-# T03: Wire post-processing into /engine/trace, add output_format routing for svg/dxf/json, and create /engine/simplify endpoint with 35 passing integration tests
-
-> Wire post-processing into /engine/trace, add output_format routing for svg/dxf/json, and create /engine/simplify endpoint with 35 passing integration tests
-
-## What Happened
----
-id: T03
-parent: S02
-milestone: M001
-key_files:
-  - engine/api/routes.py
-  - engine/tests/test_api.py
-key_decisions:
-  - DXF output returned as raw bytes with application/dxf content-type and metadata in X-Kerf-Metadata header
-  - JSON output nests generate_json result as parsed object inside envelope
-  - _format_response() shared helper for consistent response shaping across endpoints
-duration: ""
-verification_result: passed
-completed_at: 2026-03-26T04:39:50.423Z
-blocker_discovered: false
----
-
-# T03: Wire post-processing into /engine/trace, add output_format routing for svg/dxf/json, and create /engine/simplify endpoint with 35 passing integration tests
-
-**Wire post-processing into /engine/trace, add output_format routing for svg/dxf/json, and create /engine/simplify endpoint with 35 passing integration tests**
-
-## What Happened
-
-Rewrote engine/api/routes.py to integrate the full post-processing and output pipeline. After vectorization, SVG output now flows through postprocess_svg() for RDP simplification, island detection, and node counting. Added output_format routing (svg/dxf/json) using generators from the output module. Created /engine/simplify endpoint that accepts SVG upload + epsilon + output_format. Built _format_response() shared helper for consistent response shaping. DXF returns raw bytes with metadata in X-Kerf-Metadata header. Wrote 35 integration tests covering all format combinations for both endpoints.
-
-## Verification
-
-All 35 API integration tests pass (cd engine && python -m pytest tests/test_api.py -v). Full suite of 169 tests across all modules pass clean (cd engine && python -m pytest tests/ -v).
-
-## Verification Evidence
-
-| # | Command | Exit Code | Verdict | Duration |
-|---|---------|-----------|---------|----------|
-| 1 | `cd engine && .venv/bin/python -m pytest tests/test_api.py -v` | 0 | ✅ pass | 720ms |
-| 2 | `cd engine && .venv/bin/python -m pytest tests/ -v` | 0 | ✅ pass | 860ms |
-
-
-## Deviations
-
-Removed old _extract_svg_metadata() regex-based function, replaced entirely by postprocess_svg() pipeline. DXF responses use raw Response with binary content + X-Kerf-Metadata header instead of JSON envelope.
-
-## Known Issues
-
-None.
-
-## Files Created/Modified
-
-- `engine/api/routes.py`
-- `engine/tests/test_api.py`
-
-
-## Deviations
-Removed old _extract_svg_metadata() regex-based function, replaced entirely by postprocess_svg() pipeline. DXF responses use raw Response with binary content + X-Kerf-Metadata header instead of JSON envelope.
-
-## Known Issues
-None.

.gsd/milestones/M001/slices/S02/tasks/T03-VERIFY.json

@@ -1,24 +0,0 @@
-{
-  "schemaVersion": 1,
-  "taskId": "T03",
-  "unitId": "M001/S02/T03",
-  "timestamp": 1774499992324,
-  "passed": false,
-  "discoverySource": "task-plan",
-  "checks": [
-    {
-      "command": "cd engine",
-      "exitCode": 0,
-      "durationMs": 5,
-      "verdict": "pass"
-    },
-    {
-      "command": "python -m pytest tests/test_api.py -v",
-      "exitCode": 127,
-      "durationMs": 3,
-      "verdict": "fail"
-    }
-  ],
-  "retryAttempt": 1,
-  "maxRetries": 2
-}

.gsd/milestones/M001/slices/S03/S03-PLAN.md

@@ -1,27 +0,0 @@
-# S03: Preset System + Engine Docker Packaging
-
-**Goal:** Implement preset system (sign, patch, stencil, detailed, custom) as JSON config files and package engine as standalone Docker container with healthcheck.
-**Demo:** After this: GET /engine/presets returns all presets; each preset produces distinct output from same input; engine runs in Docker
-
-## Tasks
-- [x] **T01: Implemented 5 preset configs (sign, patch, stencil, detailed, custom), preset loader with param resolution, GET /engine/presets endpoint, and wired preset selection into /engine/trace pipeline** — 1. Create engine/presets/ directory
-2. Define 5 preset JSON files: sign.json, patch.json, stencil.json, detailed.json, custom.json
-3. Each preset specifies: preprocessing params, vectorization mode + params, postprocessing params
-4. Create engine/presets/loader.py to load presets from directory
-5. Implement GET /engine/presets endpoint returning all presets
-6. Wire preset selection into /engine/trace — preset params as defaults, params field overrides
-7. Test: same image with different presets produces different output
-  - Estimate: 45min
-  - Files: engine/presets/sign.json, engine/presets/patch.json, engine/presets/stencil.json, engine/presets/detailed.json, engine/presets/custom.json, engine/presets/loader.py, engine/api/routes.py
-  - Verify: cd engine && python -m pytest tests/ -v -k preset
-- [x] **T02: Created multi-stage Dockerfile.engine with healthcheck endpoint; container builds, starts, and responds healthy on /engine/health** — 1. Create docker/Dockerfile.engine (multi-stage build)
-2. Install system deps: libopencv, potrace libs
-3. Install Python deps from pyproject.toml
-4. Add healthcheck endpoint: GET /engine/health → {status: 'ok'}
-5. Configure Dockerfile HEALTHCHECK instruction
-6. Build and test container starts
-7. Verify API responds from inside container
-8. Ensure no App dependencies in engine image
-  - Estimate: 30min
-  - Files: docker/Dockerfile.engine, engine/api/routes.py
-  - Verify: cd /vmPool/r/repos/xpltdco/kerf && docker build -f docker/Dockerfile.engine -t kerf-engine:dev . && docker run --rm -d --name kerf-engine-test -p 8100:8000 kerf-engine:dev && sleep 5 && curl -s http://localhost:8100/engine/health && docker stop kerf-engine-test

.gsd/milestones/M001/slices/S03/S03-SUMMARY.md

@@ -1,106 +0,0 @@
----
-id: S03
-parent: M001
-milestone: M001
-provides:
-  - Preset system with 5 tuned configs and merge-based param resolution
-  - GET /engine/presets endpoint
-  - Docker image kerf-engine:dev with healthcheck
-  - GET /engine/health endpoint
-requires:
-  - slice: S02
-    provides: Post-processing pipeline and output format generators (SVG, DXF, JSON) consumed by preset-driven trace flow
-affects:
-  []
-key_files:
-  - engine/presets/sign.json
-  - engine/presets/patch.json
-  - engine/presets/stencil.json
-  - engine/presets/detailed.json
-  - engine/presets/custom.json
-  - engine/presets/loader.py
-  - engine/api/routes.py
-  - engine/tests/test_presets.py
-  - docker/Dockerfile.engine
-  - .dockerignore
-key_decisions:
-  - Preset default is 'sign' — covers the most common use case
-  - Presets use flat JSON with three sections (preprocessing, vectorization, postprocessing)
-  - resolve_params merges preset → user_params with user taking precedence
-  - Custom preset has empty param sections so pipeline defaults apply unless user provides overrides
-  - Multi-stage Docker build separates build deps from runtime (smaller image, no compiler tools)
-  - Engine image contains only engine source — enforces Engine/App separation (D001)
-  - Health endpoint at /engine/health for namespace consistency with other /engine/* routes
-patterns_established:
-  - Preset-driven pipeline configuration: presets define defaults, user params override
-  - Multi-stage Docker build pattern for Python+C extension packages (pypotrace)
-  - Dual health endpoints: /health (root) for simple checks, /engine/health (namespaced) for Docker/orchestration
-observability_surfaces:
-  - GET /engine/health — container health probe endpoint
-  - GET /engine/presets — returns all available presets with full config (useful for debugging preset state)
-  - Docker HEALTHCHECK — automatic container health monitoring (15s interval, 3 retries)
-drill_down_paths:
-  - .gsd/milestones/M001/slices/S03/tasks/T01-SUMMARY.md
-  - .gsd/milestones/M001/slices/S03/tasks/T02-SUMMARY.md
-duration: ""
-verification_result: passed
-completed_at: 2026-03-26T04:52:09.425Z
-blocker_discovered: false
----
-
-# S03: Preset System + Engine Docker Packaging
-
-**Shipped 5 pipeline presets (sign, patch, stencil, detailed, custom) with merge-based param resolution, GET /engine/presets endpoint, and a multi-stage Docker image with healthcheck that runs the engine standalone.**
-
-## What Happened
-
-This slice wrapped up the M001 engine milestone with two deliverables: a preset system and Docker packaging.
-
-**T01 — Preset System:** Created engine/presets/ package with 5 JSON config files, each tuned for a distinct vectorization use case: sign (aggressive simplification for signage), patch (smooth curves with auto-close for embroidery patches), stencil (heavy simplification with fixed threshold), detailed (max fidelity for illustrations), and custom (empty defaults — all params from user). Built loader.py with in-memory caching and resolve_params() that merges preset defaults with user-supplied overrides (user wins on conflicts). Mode now comes from the preset unless the user explicitly overrides it. Added GET /engine/presets endpoint that returns all available presets with their full config. Wired preset selection into the /engine/trace pipeline so posting with `preset: "stencil"` applies that preset's params. Postprocessing params (close_tolerance, auto_close) are now also preset-driven. 28 preset-specific tests validate loader logic, param resolution, endpoint response shape, per-preset integration, and cross-preset output differentiation.
-
-**T02 — Docker Packaging:** Created docker/Dockerfile.engine as a two-stage build. Builder stage installs build-essential, libagg-dev, libpotrace-dev to compile pypotrace, installs all Python deps into /opt/venv. Runtime stage uses python:3.11-slim with only runtime libs (libpotrace0, libagg2, curl), copies the venv and only engine source — no App code. Added GET /engine/health returning {"status":"ok"} on the router for namespace consistency. Docker HEALTHCHECK instruction pings /engine/health (15s interval, 5s timeout, 10s start-period, 3 retries). Container builds cleanly, starts, reports healthy, and serves all engine endpoints.
-
-## Verification
-
-All 196 tests pass (28 preset-specific). Docker image builds from project root with `docker build -f docker/Dockerfile.engine -t kerf-engine:dev .` (exit 0). Container starts on port 8100, /engine/health returns {"status":"ok"}, Docker health status shows "healthy" with 0 failing streak, /engine/presets returns all 5 presets with full config. Container contains only engine source — no App files.
-
-## Requirements Advanced
-
-None.
-
-## Requirements Validated
-
-None.
-
-## New Requirements Surfaced
-
-None.
-
-## Requirements Invalidated or Re-scoped
-
-None.
-
-## Deviations
-
-T02 verification command in the plan used `cd /vmPool/r/repos/xpltdco/kerf` which doesn't exist — the correct build context is the project root at `/home/aux/development/xpltdco/kerf-engine`. T01 added auto_close and close_tolerance postprocessing params to the preset-driven trace flow (already supported by postprocess_svg but not previously exposed through the API). T02 added /engine/health alongside the existing /health root endpoint for namespace consistency.
-
-## Known Limitations
-
-Preset files are baked into the Docker image at build time — adding/editing presets requires a rebuild. No runtime preset hot-reload. Custom preset has empty param sections which means pipeline code defaults apply — these defaults aren't documented in the preset file itself.
-
-## Follow-ups
-
-Consider adding preset validation on load (schema check). Consider documenting pipeline defaults in the custom preset for discoverability. Future M002/M003 work will consume the engine container as a service.
-
-## Files Created/Modified
-
-- `engine/presets/sign.json` — Sign preset — aggressive simplification for signage vectorization
-- `engine/presets/patch.json` — Patch preset — smooth curves with auto-close for embroidery
-- `engine/presets/stencil.json` — Stencil preset — heavy simplification with fixed threshold
-- `engine/presets/detailed.json` — Detailed preset — max fidelity for illustrations
-- `engine/presets/custom.json` — Custom preset — empty defaults, user controls everything
-- `engine/presets/loader.py` — Preset loader with caching, listing, and param merge resolution
-- `engine/api/routes.py` — Added GET /engine/presets, GET /engine/health, wired preset into /engine/trace
-- `engine/tests/test_presets.py` — 28 tests covering loader, resolution, endpoint, integration, cross-preset differentiation
-- `docker/Dockerfile.engine` — Multi-stage Dockerfile: builder compiles pypotrace, runtime uses slim image with engine source only
-- `.dockerignore` — Excludes .git, .venv, __pycache__, .gsd, node_modules from Docker build context