{"type":"thinking_level_change","id":"e9e05c74","parentId":null,"timestamp":"2026-03-30T06:57:07.337Z","thinkingLevel":"off"}
{"type":"model_change","id":"715befd7","parentId":"e9e05c74","timestamp":"2026-03-30T06:57:07.339Z","provider":"anthropic","modelId":"claude-opus-4-6"}
{"type":"custom_message","customType":"gsd-auto","content":"You are executing GSD auto-mode.\n\n## Working Directory\n\nYour working directory is `/home/aux/projects/content-to-kb-automator`. All file reads, writes, and shell commands MUST operate relative to this directory. Do NOT `cd` to any other directory.\n\n## UNIT: Complete Slice S03 (\"Technique Page Redesign + Video Source on Moments\") — Milestone M004\n\n## Your Role in the Pipeline\n\nExecutor agents built each task and wrote task summaries. You are the closer — verify the assembled work actually delivers the slice goal, then compress everything into a slice summary. After you finish, a **reassess-roadmap agent** reads your slice summary to decide if the remaining roadmap still makes sense. The slice summary is also the primary record of what this slice achieved — future slice researchers and planners read it as a dependency summary when their work builds on yours.\n\nWrite the summary for those downstream readers. What did this slice actually deliver? What patterns did it establish? What should the next slice know?\n\nAll relevant context has been preloaded below — the slice plan, all task summaries, and the milestone roadmap are inlined. Start working immediately without re-reading these files.\n\n## Inlined Context (preloaded — do not re-read these files)\n\n### Milestone Roadmap\nSource: `.gsd/milestones/M004/M004-ROADMAP.md`\n\n# M004: \n\n## Vision\nFix the immediate bugs (422 errors, creators page), apply a dark mode theme with cyan accents and fix mobile responsive issues, redesign the technique page to match the reference HTML (proper sections, signal chain blocks, key moments with video source), and introduce article versioning with pipeline tuning metadata for benchmarking extraction quality across prompt iterations.\n\n## Slice Overview\n| ID | Slice | Risk | Depends | Done | After this |\n|----|-------|------|---------|------|------------|\n| S01 | Fix API Bugs — Review Detail 422 + Creators Page | low | — | ✅ | Review detail page and creators page load without errors using real pipeline data |\n| S02 | Dark Theme + Cyan Accents + Mobile Responsive Fix | medium | — | ✅ | App uses dark theme with cyan accents, no horizontal scroll on mobile |\n| S03 | Technique Page Redesign + Video Source on Moments | medium | S01 | ⬜ | Technique page matches reference HTML layout with video source on key moments, signal chain blocks, and proper section structure |\n| S04 | Article Versioning + Pipeline Tuning Metadata | high | S03 | ⬜ | Technique pages track version history with pipeline metadata; API returns version list |\n\n---\n\n### Slice Plan\nSource: `.gsd/milestones/M004/slices/S03/S03-PLAN.md`\n\n# S03: Technique Page Redesign + Video Source on Moments\n\n**Goal:** Technique page matches the reference layout: meta stats line below title, key moments show source video filename, signal chains render as monospace flow blocks with arrow separators instead of numbered lists.\n**Demo:** After this: Technique page matches reference HTML layout with video source on key moments, signal chain blocks, and proper section structure\n\n## Tasks\n- [x] **T01: Added video_filename field to KeyMomentSummary schema and populated it via chained selectinload in the technique detail endpoint** — Extend the backend technique detail endpoint to include the source video filename on each key moment. This is the data prerequisite for all frontend changes in T02.\n\n## Steps\n\n1. In `backend/schemas.py`, add `video_filename: str = \"\"` to the `KeyMomentSummary` class.\n2. In `backend/routers/techniques.py`, chain a selectinload for the source video onto the existing key_moments load: change `selectinload(TechniquePage.key_moments)` to `selectinload(TechniquePage.key_moments).selectinload(KeyMoment.source_video)`. Import `SourceVideo` from models if not already imported.\n3. In the response construction section of `get_technique()`, after building the sorted key_moments list, populate video_filename when constructing KeyMomentSummary objects. Change the model_validate call to manually construct the dict or use a post-processing step:\n   ```python\n   key_moment_items = []\n   for km in key_moments:\n       item = KeyMomentSummary.model_validate(km)\n       item.video_filename = km.source_video.filename if km.source_video else \"\"\n       key_moment_items.append(item)\n   ```\n4. Verify locally or on ub01 that `curl http://ub01:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -m json.tool` now includes `video_filename` in each key_moments entry.\n\n## Must-Haves\n\n- [ ] `KeyMomentSummary` schema has `video_filename: str = \"\"` field\n- [ ] Technique detail query uses chained selectinload for source_video\n- [ ] Each key moment in API response includes populated `video_filename`\n- [ ] Existing fields and behavior unchanged\n  - Estimate: 20m\n  - Files: backend/schemas.py, backend/routers/techniques.py\n  - Verify: ssh ub01 'cd /vmPool/r/repos/xpltdco/chrysopedia && docker compose build chrysopedia-api && docker compose up -d chrysopedia-api && sleep 3 && curl -s http://localhost:8096/api/v1/techniques/ | python3 -m json.tool | head -5' && ssh ub01 'curl -s http://localhost:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -c \"import sys,json; d=json.load(sys.stdin); kms=d.get(\\\"key_moments\\\",[]); assert len(kms)>0; assert all(\\\"video_filename\\\" in km for km in kms); assert any(km[\\\"video_filename\\\"]!=\\\"\\\" for km in kms); print(f\\\"OK: {len(kms)} moments, all have video_filename\\\")\"'\n- [x] **T02: Redesigned technique page frontend: meta stats line, video filenames on key moments, monospace signal chain flow blocks with arrow separators** — Redesign the frontend technique page to match the spec layout. Three visual changes: meta stats line, video filename on key moments, and monospace signal chain flow blocks. All CSS must use existing `var(--*)` tokens.\n\n## Steps\n\n1. In `frontend/src/api/public-client.ts`, add `video_filename: string` to the `KeyMomentSummary` interface (with empty string default behavior — JSON will supply it).\n\n2. In `frontend/src/pages/TechniquePage.tsx`, add a meta stats line between the header and summary sections:\n   - Compute unique source count: `new Set(technique.key_moments.map(km => km.video_filename).filter(Boolean)).size`\n   - Moment count: `technique.key_moments.length`\n   - Last updated: format `technique.updated_at` as a readable date\n   - Render: `<div className=\"technique-header__stats\">Compiled from {N} source{s} · {M} key moment{s} · Last updated {date}</div>`\n\n3. In the key moments section, add the video filename between the title and timestamp:\n   ```tsx\n   {km.video_filename && (\n     <span className=\"technique-moment__source\">{km.video_filename}</span>\n   )}\n   ```\n\n4. Redesign the signal chains section. Replace the `<ol className=\"technique-chain__steps\">` with a monospace flow block:\n   ```tsx\n   <div className=\"technique-chain__flow\">\n     {steps.map((step, j) => (\n       <span key={j}>\n         {j > 0 && <span className=\"technique-chain__arrow\"> → </span>}\n         <span className=\"technique-chain__step\">{String(step)}</span>\n       </span>\n     ))}\n   </div>\n   ```\n\n5. In `frontend/src/App.css`, add CSS classes using only `var(--*)` tokens:\n   - `.technique-header__stats` — secondary text color, smaller font, margin below header\n   - `.technique-moment__source` — truncated text, muted color, monospace-ish, smaller font\n   - `.technique-chain__flow` — monospace font, horizontal wrap, background surface, padding, border-radius\n   - `.technique-chain__arrow` — accent color (cyan)\n   - `.technique-chain__step` — inline display\n   - Remove or restyle `.technique-chain__steps` (the old `<ol>` style)\n\n6. Run `cd frontend && npm run build` to verify zero TypeScript errors.\n\n7. Deploy to ub01: push changes, SSH in, `docker compose build chrysopedia-web-8096 && docker compose up -d chrysopedia-web-8096`.\n\n## Constraints\n- All CSS colors MUST use `var(--*)` tokens. The S02 dark theme established 84 semantic custom properties. Grep verification: `grep -P '#[0-9a-fA-F]{3,8}' frontend/src/App.css | grep -v ':root' | grep -v '^\\/\\*'` should return zero new hex colors.\n- Do NOT modify `:root` custom property definitions unless adding a genuinely new semantic token.\n\n## Must-Haves\n\n- [ ] TypeScript `KeyMomentSummary` includes `video_filename: string`\n- [ ] Meta stats line renders below technique title\n- [ ] Key moment rows show video filename\n- [ ] Signal chains render as monospace flow with arrow separators\n- [ ] All new CSS uses `var(--*)` tokens only\n- [ ] `npm run build` succeeds with zero errors\n  - Estimate: 45m\n  - Files: frontend/src/api/public-client.ts, frontend/src/pages/TechniquePage.tsx, frontend/src/App.css\n  - Verify: cd frontend && npm run build 2>&1 | tail -5 && echo 'BUILD OK' && grep -cP '#[0-9a-fA-F]{3,8}' src/App.css | grep -v ':root' || echo 'No hardcoded colors outside :root'\n\n---\n\n### Requirements\nSource: `.gsd/REQUIREMENTS.md`\n\n# Requirements\n\n## R001 — Whisper Transcription Pipeline\n**Status:** validated\n**Description:** Desktop Python script that accepts video files (MP4/MKV), extracts audio via ffmpeg, runs Whisper large-v3 on RTX 4090, and outputs timestamped transcript JSON with segment-level timestamps and word-level timing. Must be resumable.\n**Validation:** Script processes a sample video and produces valid JSON with timestamped segments.\n**Primary Owner:** M001/S01\n\n## R002 — Transcript Ingestion API\n**Status:** validated\n**Description:** FastAPI endpoint that accepts transcript JSON uploads, creates/updates Creator and Source Video records, and stores transcript data in PostgreSQL. Handles new creator detection from folder names.\n**Validation:** POST transcript JSON → 200 OK, records created in DB, file stored on filesystem.\n**Primary Owner:** M001/S02\n\n## R003 — LLM-Powered Extraction Pipeline (Stages 2-5)\n**Status:** validated\n**Description:** Background worker pipeline: transcript segmentation → key moment extraction → classification/tagging → technique page synthesis. Uses OpenAI-compatible API with primary (DGX Sparks Qwen) and fallback (local Ollama) endpoints. Pipeline must be resumable per-video per-stage.\n**Validation:** End-to-end: transcript JSON in → technique pages with key moments, tags, and cross-references out.\n**Primary Owner:** M001/S03\n\n## R004 — Review Queue UI\n**Status:** validated\n**Description:** Admin interface for reviewing extracted key moments: approve, edit+approve, split, merge, reject. Organized by source video for contextual review. Includes mode toggle (review vs auto-publish).\n**Validation:** Admin can review, edit, and approve/reject moments; mode toggle controls whether new moments require review.\n**Primary Owner:** M001/S04\n\n## R005 — Search-First Web UI\n**Status:** validated\n**Description:** Landing page with prominent search bar, live typeahead (results after 2-3 chars), scope toggle (All/Topics/Creators), and two navigation cards (Topics, Creators). Recently added section. Search powered by Qdrant semantic search with keyword fallback.\n**Validation:** User types query → results appear within 500ms, grouped by type, with clickable navigation.\n**Primary Owner:** M001/S05\n\n## R006 — Technique Page Display\n**Status:** validated\n**Description:** Core content unit: header (tags, title, creator, meta), study guide prose (organized by sub-aspects with signal chain blocks and quotes), key moments index (timestamped list), related techniques, plugins referenced. Amber banner for livestream-sourced content.\n**Validation:** Technique page renders with all sections populated from synthesized data.\n**Primary Owner:** M001/S05\n\n## R007 — Creators Browse Page\n**Status:** validated\n**Description:** Filterable creator list with genre filter pills, type-to-narrow, sort options (randomized default, alphabetical, view count). Each row: name, genre tags, technique count, video count, view count. Links to creator detail page.\n**Validation:** Page loads with randomized order, genre filtering works, clicking row navigates to creator detail.\n**Primary Owner:** M001/S05\n\n## R008 — Topics Browse Page\n**Status:** validated\n**Description:** Two-level topic hierarchy (6 top-level categories → sub-topics). Filter input, genre filter pills. Each sub-topic shows technique count and creator count. Clicking sub-topic shows technique pages.\n**Validation:** Hierarchy renders, filtering works, sub-topic links show correct technique pages.\n**Primary Owner:** M001/S05\n\n## R009 — Qdrant Vector Search Integration\n**Status:** validated\n**Description:** Embed key moment summaries, technique page content, and transcript segments in Qdrant using configurable embedding model (nomic-embed-text default). Power semantic search with metadata filtering.\n**Validation:** Semantic search returns relevant results for natural language queries; embeddings update when content changes.\n**Primary Owner:** M001/S03\n\n## R010 — Docker Compose Deployment\n**Status:** validated\n**Description:** Single docker-compose.yml packaging API, web UI, PostgreSQL, and worker services. Follows XPLTD conventions: bind mounts at /vmPool/r/services/, compose at /vmPool/r/compose/chrysopedia/, xpltd_chrysopedia project name, dedicated Docker network.\n**Validation:** `docker compose up -d` brings up all services; data persists across restarts.\n**Primary Owner:** M001/S01\n\n## R011 — Canonical Tag System\n**Status:** validated\n**Description:** Editable canonical tag list (config file) with aliases. Pipeline references tags during classification. New tags can be proposed by LLM and queued for admin approval or auto-added within existing categories.\n**Validation:** Tag list is editable; pipeline uses canonical tags consistently; alias normalization works.\n**Primary Owner:** M001/S03\n\n## R012 — Incremental Content Addition\n**Status:** validated\n**Description:** System handles ongoing content: new videos processed through pipeline, new creators auto-detected, existing technique pages updated when new moments are added for same creator+topic.\n**Validation:** Adding a new video for an existing creator updates their technique pages; new creator folder creates new Creator record.\n**Primary Owner:** M001/S03\n\n## R013 — Prompt Template System\n**Status:** validated\n**Description:** Extraction prompts (stages 2-5) stored as editable configuration files, not hardcoded. Admin can edit prompts and re-run extraction on specific or all videos for calibration.\n**Validation:** Prompt files are editable; re-processing a video with updated prompts produces different output.\n**Primary Owner:** M001/S03\n\n## R014 — Creator Equity\n**Status:** validated\n**Description:** No creator is privileged in the UI. Default sort on Creators page is randomized on every page load. All creators get equal visual weight.\n**Validation:** Refreshing Creators page shows different order each time; no creator gets larger/bolder display.\n**Primary Owner:** M001/S05\n\n## R015 — 30-Second Retrieval Target\n**Status:** active\n**Description:** A producer mid-session can find a specific technique in under 30 seconds from Alt+Tab to reading the key insight.\n**Validation:** Timed test: Alt+Tab → search → read technique → under 30 seconds.\n**Primary Owner:** M001/S05\n\n---\n\n### Project Knowledge\nSource: `.gsd/KNOWLEDGE.md`\n\n# KNOWLEDGE\n\n## SQLAlchemy column names that shadow ORM functions\n\n**Context:** If a model has a column named `relationship` (or any other ORM function name like `query`, `metadata`), Python resolves the name to the column's `MappedColumn` descriptor within the class body. This causes `relationship(...)` calls below it to fail with \"MappedColumn object is not callable\".\n\n**Fix:** Import with an alias: `from sqlalchemy.orm import relationship as sa_relationship` and use `sa_relationship(...)` throughout. Alternatively, rename the database column, but the spec defines `relationship` as the column name so we preserved it.\n\n## Docker Compose variable interpolation and `:?` syntax\n\n**Context:** `${VAR:?error message}` in docker-compose.yml makes `docker compose config` fail when the variable is unset, even if `env_file: required: false` is used. The `required: false` only controls whether the `.env` file must exist — it does NOT provide defaults for variables referenced with `:?`.\n\n**Fix:** Use `${VAR:-default}` for variables that need a fallback, or ensure the variable is always set in the environment.\n\n## Host port 8000 conflict with kerf-engine\n\n**Context:** The kerf-engine Docker container (`kerf-engine-kerf-engine-1`) binds to `0.0.0.0:8000`. When testing the Chrysopedia API locally (outside Docker), curl requests to `localhost:8000` hit the kerf-engine container instead of the local uvicorn process, even when uvicorn binds to `127.0.0.1:8000`.\n\n**Fix:** Use an alternate port (e.g., 8001) for local testing. In Docker Compose, chrysopedia-api maps `127.0.0.1:8000:8000` which is fine because it goes through Docker's port forwarding, but will conflict with kerf-engine if both stacks run simultaneously. Consider changing one project's external port mapping.\n\n## asyncpg rejects timezone-aware datetimes for TIMESTAMP WITHOUT TIME ZONE columns\n\n**Context:** SQLAlchemy models using `default=datetime.now(timezone.utc)` produce timezone-aware Python datetimes. When the PostgreSQL column type is `TIMESTAMP WITHOUT TIME ZONE` (the default), asyncpg raises `DataError: can't subtract offset-naive and offset-aware datetimes`. This only surfaces when running against a real PostgreSQL database — SQLite-based tests won't catch it.\n\n**Fix:** Use `datetime.now(timezone.utc).replace(tzinfo=None)` in the `_now()` helper, or change the column type to `TIMESTAMP WITH TIME ZONE`. We chose the former since the existing schema uses naive timestamps.\n\n## asyncpg NullPool required for pytest-asyncio integration tests\n\n**Context:** When using a session-scoped SQLAlchemy async engine with asyncpg in pytest-asyncio tests, the connection pool reuses connections across fixtures and test functions. This causes `InterfaceError: cannot perform operation: another operation is in progress` because the ASGI test client's session holds a connection while cleanup/verification fixtures try to use the same pool.\n\n**Fix:** Use `poolclass=NullPool` when creating the test engine. Each connection is created fresh and immediately closed, eliminating contention. Performance cost is negligible for test suites.\n\n## Testing Celery tasks that use sync SQLAlchemy: patch module-level globals\n\n**Context:** Pipeline stages in `pipeline/stages.py` create their own sync SQLAlchemy engine/session via module-level `_engine` and `_SessionLocal` globals (because Celery is sync, not async). Tests need to redirect these to the test database, but the engine is created lazily at module scope.\n\n**Fix:** Patch the module globals directly: `unittest.mock.patch.object(stages, '_engine', test_engine)` and `unittest.mock.patch.object(stages, '_SessionLocal', test_session_factory)`. This redirects all DB access in stage functions to the test database without modifying production code.\n\n## Lazy imports in FastAPI handlers defeat simple mock patching\n\n**Context:** When a FastAPI handler imports a function lazily (inside the function body) like `from pipeline.stages import run_pipeline`, patching `routers.ingest.run_pipeline` has no effect because the name is re-bound on every call from the source module.\n\n**Fix:** Patch at the source module: `unittest.mock.patch('pipeline.stages.run_pipeline')`. The lazy import will pick up the mock from the source module. This applies to any handler that uses lazy imports to avoid circular dependencies at module load time.\n\n## Separate async/sync clients for FastAPI vs Celery\n\n**Context:** The Chrysopedia backend has both sync Celery tasks (pipeline stages using `openai.OpenAI`, `QdrantClient`, sync SQLAlchemy) and async FastAPI handlers. Reusing sync clients in async handlers blocks the event loop; reusing async clients in Celery risks nested event loop errors.\n\n**Fix:** Create separate client classes: `SearchService` (async, for FastAPI request path) wraps `openai.AsyncOpenAI` and `AsyncQdrantClient`. The pipeline's `EmbeddingClient` and `QdrantManager` (sync, for Celery) remain untouched. This doubles the client code surface but eliminates the async/sync mismatch class of bugs entirely.\n\n## Mocking SearchService at the router dependency level for tests\n\n**Context:** The search endpoint creates a `SearchService` instance internally. Testing search results with real embedding API and Qdrant is fragile (external dependencies). Mocking individual `openai.AsyncOpenAI` or `AsyncQdrantClient` is complex.\n\n**Fix:** Mock `SearchService` at the router level by patching the service instance in the endpoint function. This gives full control over search results in tests without complex async mock setup. Used in `test_search.py` — mock returns canned `SearchResponse` dicts.\n\n## Frontend detail page without a single-resource GET endpoint\n\n**Context:** The review queue backend has `GET /review/queue` (list, paginated) but no `GET /review/moments/{id}` for fetching a single moment. The MomentDetail page needs to display one specific moment by ID from the URL params.\n\n**Fix:** MomentDetail fetches the full queue with `limit=500` and filters client-side by ID. This works for a single-admin tool with small datasets but would not scale. If the moment count grows significantly, add a dedicated `GET /review/moments/{id}` endpoint to the review router.\n\n## Stage 4 classification data stored in Redis (not DB columns)\n\n**Context:** The KeyMoment SQLAlchemy model doesn't have `topic_tags` or `topic_category` columns. Stage 4 classification needs somewhere to store per-moment tag assignments that stage 5 can read.\n\n**Fix:** Store classification results in Redis under key `chrysopedia:classification:{video_id}` with a 24-hour TTL. Stage 5 reads from Redis. This avoids schema migrations during initial pipeline development. The data is ephemeral — if Redis loses it, re-running stage 4 regenerates it.\n\n## QdrantManager uses random UUIDs for point IDs\n\n**Context:** `QdrantManager.upsert_technique_pages()` and `upsert_key_moments()` generate `uuid4()` for each Qdrant point. Re-indexing the same content creates duplicate points rather than updating existing ones.\n\n**Fix (deferred):** Use deterministic UUIDs based on content hash (e.g., `uuid5(NAMESPACE, f\"{technique_slug}:{section}\")`) so re-indexing overwrites the same points. This should be addressed before running the pipeline on production data to avoid index bloat.\n\n## Non-blocking side-effect pattern for external service calls in pipelines\n\n**Context:** Celery pipeline stages that call external services (embedding API, Qdrant) should not fail the entire pipeline if those services are down. Stage 6 (embed_and_index) is valuable but not critical — the pipeline's primary output (technique pages in PostgreSQL) doesn't depend on it.\n\n**Fix:** Use `max_retries=0` and a catch-all exception handler that logs WARNING and returns without raising. The pipeline orchestrator chains stage 6 after stage 5 but a failure there doesn't prevent `processing_status` from reaching its final state. This pattern applies to any \"best-effort enrichment\" stage in a pipeline.\n\n## Container healthcheck tool availability varies by base image\n\n**Context:** Qdrant (distroless-ish), Ollama, and nginx-alpine images don't have curl or wget. Standard healthcheck patterns like `curl -f http://localhost:PORT/health` fail silently inside these containers.\n\n**Fix by image:**\n- **Ollama:** Use `ollama list` (built-in CLI)\n- **Qdrant:** Use `bash -c 'echo > /dev/tcp/localhost/6333'` (bash is available)\n- **nginx-alpine:** Use `curl` (available) but NOT busybox `wget` (fails on localhost)\n- **Celery worker (same image as API):** Use `celery -A worker inspect ping` instead of HTTP healthcheck\n\n**Rule:** Always `docker exec <container> <healthcheck-cmd>` to verify the command works before deploying.\n\n## XPLTD domain setup flow\n\n**Context:** Adding a new external domain (like chrysopedia.com) to the XPLTD infrastructure requires three steps across two machines.\n\n**Flow:**\n1. **AdGuard on ub01 (10.0.0.10):** Add DNS rewrite via API: `POST /control/rewrite/add` with `{domain, answer: \"10.0.0.9\"}`\n2. **nginx on nuc01 (10.0.0.9):** Create server block in `/etc/nginx/sites-enabled/{domain}.conf` with `proxy_pass http://10.0.0.10:{port}`\n3. **Certbot on nuc01:** `sudo certbot --nginx -d {domain}` (requires external DNS A record or CNAME pointing to public IP first)\n\n**Note:** The AD DNS servers (10.0.0.15/.16) may already have CNAME entries for domains. Check `nslookup {domain} 10.0.0.15` before assuming setup is needed. ub01's resolv.conf uses AD DNS, not AdGuard, so `curl {domain}` from ub01 requires the AD DNS chain to resolve.\n\n## Alembic env.py sys.path needs both local and Docker paths\n\n**Context:** Alembic's env.py imports from `database` and `models`, which live in `backend/` locally but at `/app/` (the WORKDIR) inside Docker. The original `sys.path.insert(0, \"../backend\")` works locally but fails in Docker.\n\n**Fix:** Add both paths: `sys.path.insert(0, os.path.join(os.path.dirname(__file__), \"..\", \"backend\"))` AND `sys.path.insert(0, os.path.join(os.path.dirname(__file__), \"..\"))`. The second resolves to `/app/` inside Docker.\n\n---\n\n### Task Summary: T01\nSource: `.gsd/milestones/M004/slices/S03/tasks/T01-SUMMARY.md`\n\n---\nid: T01\nparent: S03\nmilestone: M004\nprovides: []\nrequires: []\naffects: []\nkey_files: [\"backend/schemas.py\", \"backend/routers/techniques.py\"]\nkey_decisions: [\"Populate video_filename via post-processing loop rather than from_attributes auto-mapping, since the field comes from a joined relation not a direct column\"]\npatterns_established: []\ndrill_down_paths: []\nobservability_surfaces: []\nduration: \"\"\nverification_result: \"Rebuilt chrysopedia-api container on ub01 and verified: (1) wave-shaping-synthesis-m-wave-shaper returns 13 key moments all with video_filename populated, (2) second technique page returns 2 moments with video_filename, (3) all existing fields unchanged, (4) assertion script confirms all moments have video_filename and at least one is non-empty.\"\ncompleted_at: 2026-03-30T06:49:59.009Z\nblocker_discovered: false\n---\n\n# T01: Added video_filename field to KeyMomentSummary schema and populated it via chained selectinload in the technique detail endpoint\n\n> Added video_filename field to KeyMomentSummary schema and populated it via chained selectinload in the technique detail endpoint\n\n## What Happened\n---\nid: T01\nparent: S03\nmilestone: M004\nkey_files:\n  - backend/schemas.py\n  - backend/routers/techniques.py\nkey_decisions:\n  - Populate video_filename via post-processing loop rather than from_attributes auto-mapping, since the field comes from a joined relation not a direct column\nduration: \"\"\nverification_result: passed\ncompleted_at: 2026-03-30T06:49:59.009Z\nblocker_discovered: false\n---\n\n# T01: Added video_filename field to KeyMomentSummary schema and populated it via chained selectinload in the technique detail endpoint\n\n**Added video_filename field to KeyMomentSummary schema and populated it via chained selectinload in the technique detail endpoint**\n\n## What Happened\n\nAdded `video_filename: str = \"\"` to the KeyMomentSummary Pydantic schema. Chained `.selectinload(KeyMoment.source_video)` onto the existing key_moments eager load in the technique detail endpoint. Changed response construction to a loop that populates video_filename from the eager-loaded source_video relation. Deployed to ub01 and verified both technique pages return video_filename on all key moments with correct values.\n\n## Verification\n\nRebuilt chrysopedia-api container on ub01 and verified: (1) wave-shaping-synthesis-m-wave-shaper returns 13 key moments all with video_filename populated, (2) second technique page returns 2 moments with video_filename, (3) all existing fields unchanged, (4) assertion script confirms all moments have video_filename and at least one is non-empty.\n\n## Verification Evidence\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| 1 | `ssh ub01 'docker compose build chrysopedia-api'` | 0 | ✅ pass | 8000ms |\n| 2 | `ssh ub01 'docker compose up -d chrysopedia-api'` | 0 | ✅ pass | 5000ms |\n| 3 | `ssh ub01 'curl -s .../techniques/wave-shaping-synthesis-m-wave-shaper | python3 assert video_filename'` | 0 | ✅ pass | 1000ms |\n| 4 | `ssh ub01 'curl -s .../techniques/balancing-softness-... | python3 check video_filename'` | 0 | ✅ pass | 1000ms |\n\n\n## Deviations\n\nNone.\n\n## Known Issues\n\nNone.\n\n## Files Created/Modified\n\n- `backend/schemas.py`\n- `backend/routers/techniques.py`\n\n\n## Deviations\nNone.\n\n## Known Issues\nNone.\n\n---\n\n### Task Summary: T02\nSource: `.gsd/milestones/M004/slices/S03/tasks/T02-SUMMARY.md`\n\n---\nid: T02\nparent: S03\nmilestone: M004\nprovides: []\nrequires: []\naffects: []\nkey_files: [\"frontend/src/api/public-client.ts\", \"frontend/src/pages/TechniquePage.tsx\", \"frontend/src/App.css\"]\nkey_decisions: [\"Used text-overflow ellipsis on video filename with max-width 20rem to prevent layout breakage\", \"Used IIFE in JSX for meta stats computation to keep template readable\"]\npatterns_established: []\ndrill_down_paths: []\nobservability_surfaces: []\nduration: \"\"\nverification_result: \"npm run build succeeds with zero errors. No hardcoded hex colors outside :root. Browser verification on ub01:8096 confirms meta stats line, video filenames, and monospace signal chain flow blocks all render correctly.\"\ncompleted_at: 2026-03-30T06:56:54.253Z\nblocker_discovered: false\n---\n\n# T02: Redesigned technique page frontend: meta stats line, video filenames on key moments, monospace signal chain flow blocks with arrow separators\n\n> Redesigned technique page frontend: meta stats line, video filenames on key moments, monospace signal chain flow blocks with arrow separators\n\n## What Happened\n---\nid: T02\nparent: S03\nmilestone: M004\nkey_files:\n  - frontend/src/api/public-client.ts\n  - frontend/src/pages/TechniquePage.tsx\n  - frontend/src/App.css\nkey_decisions:\n  - Used text-overflow ellipsis on video filename with max-width 20rem to prevent layout breakage\n  - Used IIFE in JSX for meta stats computation to keep template readable\nduration: \"\"\nverification_result: passed\ncompleted_at: 2026-03-30T06:56:54.254Z\nblocker_discovered: false\n\n[...truncated 14 sections]\n\n**Match effort to complexity.** A simple slice with 1-2 tasks needs a brief summary and lightweight verification. A complex slice with 5 tasks across multiple subsystems needs thorough verification and a detailed summary. Scale the work below accordingly.\n\nThen:\n1. Use the **Slice Summary** and **UAT** output templates from the inlined context above\n2. If a `GSD Skill Preferences` block is present in system context, use it and the `<available_skills>` catalog in your system prompt to decide which skills to load and follow for this unit, without relaxing required verification or artifact rules.\n3. Run all slice-level verification checks defined in the slice plan. All must pass before marking the slice done. If any fail, fix them first.\n4. If the slice plan includes observability/diagnostic surfaces, confirm they work. Skip this for simple slices that don't have observability sections.\n5. If the slice involved runtime behavior, fill the **Operational Readiness** section (Q8) in the slice summary: health signal, failure signal, recovery procedure, and monitoring gaps. Omit entirely for simple slices with no runtime concerns.\n6. If this slice produced evidence that a requirement changed status (Active → Validated, Active → Deferred, etc.), call `gsd_save_decision` with scope=\"requirement\", decision=\"{requirement-id}\", choice=\"{new-status}\", rationale=\"{evidence}\". Do NOT write `.gsd/REQUIREMENTS.md` directly — the engine renders it from the database.\n7. Write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-SUMMARY.md` (compress all task summaries).\n8. Write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-UAT.md` — a concrete UAT script with real test cases derived from the slice plan and task summaries. Include preconditions, numbered steps with expected outcomes, and edge cases. This must NOT be a placeholder or generic template — tailor every test case to what this slice actually built.\n9. Review task summaries for `key_decisions`. Append any significant decisions to `.gsd/DECISIONS.md` if missing.\n10. Review task summaries for patterns, gotchas, or non-obvious lessons learned. If any would save future agents from repeating investigation or hitting the same issues, append them to `.gsd/KNOWLEDGE.md`. Only add entries that are genuinely useful — don't pad with obvious observations.\n11. Call `gsd_complete_slice` with milestone_id, slice_id, the slice summary, and the UAT result. Do NOT manually mark the roadmap checkbox — the tool writes to the DB and renders the ROADMAP.md projection automatically.\n12. Do not run git commands — the system commits your changes and handles any merge after this unit succeeds.\n13. Update `.gsd/PROJECT.md` if it exists — refresh current state if needed.\n\n**You MUST call `gsd_complete_slice` with the slice summary and UAT content before finishing. The tool persists to both DB and disk and renders `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-SUMMARY.md` and `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-UAT.md` automatically.**\n\nWhen done, say: \"Slice S03 complete.\"","display":false,"id":"0ab6f618","parentId":"715befd7","timestamp":"2026-03-30T06:57:07.341Z"}
{"type":"message","id":"fd663aed","parentId":"0ab6f618","timestamp":"2026-03-30T06:57:15.214Z","message":{"role":"assistant","content":[{"type":"text","text":"\n\nI'll verify the slice deliverables before writing the summary. Let me check the actual code changes and run verification."},{"type":"toolCall","id":"toolu_01G4kzaA3shXEZhNeMqqT1Ex","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && ssh ub01 'curl -s http://localhost:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -c \"import sys,json; d=json.load(sys.stdin); kms=d.get(\\\"key_moments\\\",[]); assert len(kms)>0; assert all(\\\"video_filename\\\" in km for km in kms); assert any(km[\\\"video_filename\\\"]!=\\\"\\\" for km in kms); print(f\\\"OK: {len(kms)} moments, all have video_filename\\\"); [print(f\\\"  - {km[\\\"video_filename\\\"]}\\\") for km in kms[:3]]\"'"}},{"type":"toolCall","id":"toolu_01KZ16qMvEP8cZg64yUBY3ax","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator/frontend && npm run build 2>&1 | tail -10"}},{"type":"toolCall","id":"toolu_01Tfn228XZJfEckACQTyUwqb","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator/frontend && grep -nP '#[0-9a-fA-F]{3,8}' src/App.css | grep -v ':root' | grep -v '^\\s*/\\*' | grep -v '^\\s*\\*' || echo 'No hardcoded hex colors outside :root'"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":3,"output":448,"cacheRead":56783,"cacheWrite":9330,"totalTokens":66564,"cost":{"input":0.000015000000000000002,"output":0.0112,"cacheRead":0.0283915,"cacheWrite":0.0583125,"total":0.097919}},"stopReason":"toolUse","timestamp":1774853827340}}
{"type":"message","id":"961a7991","parentId":"fd663aed","timestamp":"2026-03-30T06:57:16.147Z","message":{"role":"toolResult","toolCallId":"toolu_01G4kzaA3shXEZhNeMqqT1Ex","toolName":"bash","content":[{"type":"text","text":"OK: 13 moments, all have video_filename\n  - Skope - Understanding Waveshapers (2160p).mp4\n  - Skope - Understanding Waveshapers (2160p).mp4\n  - Skope - Understanding Waveshapers (2160p).mp4\n"}],"isError":false,"timestamp":1774853836146}}
{"type":"message","id":"c6da8399","parentId":"961a7991","timestamp":"2026-03-30T06:57:17.718Z","message":{"role":"toolResult","toolCallId":"toolu_01KZ16qMvEP8cZg64yUBY3ax","toolName":"bash","content":[{"type":"text","text":"\nvite v6.4.1 building for production...\ntransforming...\n✓ 43 modules transformed.\nrendering chunks...\ncomputing gzip size...\ndist/index.html                   0.45 kB │ gzip:  0.29 kB\ndist/assets/index-XJBixYYF.css   29.49 kB │ gzip:  4.86 kB\ndist/assets/index-OFI9e8cm.js   200.16 kB │ gzip: 61.99 kB\n✓ built in 830ms\n"}],"isError":false,"timestamp":1774853837718}}
{"type":"message","id":"4788b2f2","parentId":"c6da8399","timestamp":"2026-03-30T06:57:17.721Z","message":{"role":"toolResult","toolCallId":"toolu_01Tfn228XZJfEckACQTyUwqb","toolName":"bash","content":[{"type":"text","text":"5:  --color-bg-page: #0f0f14;\n6:  --color-bg-surface: #1a1a24;\n7:  --color-bg-surface-hover: #22222e;\n8:  --color-bg-input: #1a1a24;\n9:  --color-bg-header: #0a0a12;\n10:  --color-bg-header-alt: #14141e;\n11:  --color-bg-transcript: #12121a;\n14:  --color-text-primary: #e2e2ea;\n15:  --color-text-secondary: #8b8b9a;\n16:  --color-text-muted: #6b6b7a;\n17:  --color-text-active: #e2e2ea;\n19:  --color-text-on-header-hover: #fff;\n23:  --color-border: #2a2a38;\n24:  --color-border-active: #22d3ee;\n27:  --color-accent: #22d3ee;\n28:  --color-accent-hover: #67e8f9;\n38:  --color-badge-pending-bg: #422006;\n39:  --color-badge-pending-text: #fcd34d;\n40:  --color-badge-approved-bg: #052e16;\n41:  --color-badge-approved-text: #6ee7b7;\n42:  --color-badge-edited-bg: #1e1b4b;\n43:  --color-badge-edited-text: #93c5fd;\n44:  --color-badge-rejected-bg: #450a0a;\n45:  --color-badge-rejected-text: #fca5a5;\n48:  --color-btn-approve: #059669;\n49:  --color-btn-approve-hover: #047857;\n50:  --color-btn-reject: #dc2626;\n51:  --color-btn-reject-hover: #b91c1c;\n54:  --color-toggle-review: #10b981;\n55:  --color-toggle-auto: #f59e0b;\n56:  --color-toggle-track: #6b7280;\n57:  --color-toggle-track-active: #059669;\n58:  --color-toggle-thumb: #fff;\n61:  --color-error: #f87171;\n62:  --color-error-bg: #450a0a;\n63:  --color-error-border: #7f1d1d;\n66:  --color-banner-amber-bg: #422006;\n67:  --color-banner-amber-border: #854d0e;\n68:  --color-banner-amber-text: #fcd34d;\n71:  --color-pill-bg: #22222e;\n72:  --color-pill-text: #e2e2ea;\n73:  --color-pill-plugin-bg: #2e1065;\n74:  --color-pill-plugin-text: #c4b5fd;\n75:  --color-badge-category-bg: #1e1b4b;\n76:  --color-badge-category-text: #93c5fd;\n77:  --color-badge-type-technique-bg: #1e1b4b;\n78:  --color-badge-type-technique-text: #93c5fd;\n79:  --color-badge-type-moment-bg: #422006;\n80:  --color-badge-type-moment-text: #fcd34d;\n81:  --color-badge-content-type-bg: #22222e;\n82:  --color-badge-content-type-text: #e2e2ea;\n83:  --color-badge-quality-structured-bg: #052e16;\n84:  --color-badge-quality-structured-text: #6ee7b7;\n85:  --color-badge-quality-unstructured-bg: #422006;\n86:  --color-badge-quality-unstructured-text: #fcd34d;\n89:  --color-genre-pill-bg: #1a1a24;\n90:  --color-genre-pill-text: #e2e2ea;\n91:  --color-genre-pill-border: #2a2a38;\n92:  --color-genre-pill-hover-bg: #22222e;\n93:  --color-genre-pill-hover-border: #67e8f9;\n94:  --color-genre-pill-active-bg: #22d3ee;\n95:  --color-genre-pill-active-text: #0f0f14;\n96:  --color-genre-pill-active-border: #22d3ee;\n97:  --color-genre-pill-active-hover-bg: #67e8f9;\n100:  --color-sort-btn-bg: #1a1a24;\n101:  --color-sort-btn-text: #8b8b9a;\n102:  --color-sort-btn-border: #2a2a38;\n103:  --color-sort-btn-hover-bg: #22222e;\n104:  --color-sort-btn-hover-text: #e2e2ea;\n105:  --color-sort-btn-active-bg: #22d3ee;\n106:  --color-sort-btn-active-text: #0f0f14;\n107:  --color-sort-btn-active-hover-bg: #67e8f9;\n110:  --color-link-accent: #22d3ee;\n113:  --color-btn-search-bg: #22d3ee;\n114:  --color-btn-search-text: #0f0f14;\n115:  --color-btn-search-hover-bg: #67e8f9;\n118:  --color-typeahead-see-all: #22d3ee;\n"}],"isError":false,"timestamp":1774853837718}}
{"type":"message","id":"22aedacb","parentId":"4788b2f2","timestamp":"2026-03-30T06:57:27.370Z","message":{"role":"assistant","content":[{"type":"text","text":"All hex colors are inside `:root` — the grep is correctly showing `:root` definitions (lines 5-118 are all within the `:root {}` block). Let me verify that more precisely and check the actual frontend changes."},{"type":"toolCall","id":"toolu_01PiyAG8vQY3ytt4EWd2wThi","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator/frontend && awk '/:root\\s*\\{/,/^\\}/' src/App.css | wc -l && echo \"---\" && awk 'BEGIN{in_root=0} /:root\\s*\\{/{in_root=1} /^\\}/{if(in_root) in_root=0} !in_root{print NR\": \"$0}' src/App.css | grep -P '#[0-9a-fA-F]{3,8}' | grep -v '^\\s*/\\*' | grep -v '^\\s*\\*' || echo 'PASS: No hex colors outside :root'"}},{"type":"toolCall","id":"toolu_019cHFv3GFz5gfJujU5cdpUi","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && grep -n 'video_filename' backend/schemas.py"}},{"type":"toolCall","id":"toolu_01HPjQGVRX1LAacYuffgZnoX","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && grep -n 'video_filename\\|source_video\\|selectinload' backend/routers/techniques.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":414,"cacheRead":66113,"cacheWrite":2228,"totalTokens":68756,"cost":{"input":0.000005,"output":0.01035,"cacheRead":0.033056499999999996,"cacheWrite":0.013925,"total":0.05733649999999999}},"stopReason":"toolUse","timestamp":1774853837719}}
{"type":"message","id":"6de42fa9","parentId":"22aedacb","timestamp":"2026-03-30T06:57:27.386Z","message":{"role":"toolResult","toolCallId":"toolu_01PiyAG8vQY3ytt4EWd2wThi","toolName":"bash","content":[{"type":"text","text":"117\n---\nPASS: No hex colors outside :root\n"}],"isError":false,"timestamp":1774853847386}}
{"type":"message","id":"a7517a03","parentId":"6de42fa9","timestamp":"2026-03-30T06:57:27.386Z","message":{"role":"toolResult","toolCallId":"toolu_019cHFv3GFz5gfJujU5cdpUi","toolName":"bash","content":[{"type":"text","text":"203:    video_filename: str\n289:    video_filename: str = \"\"\n"}],"isError":false,"timestamp":1774853847386}}
{"type":"message","id":"cdf988ba","parentId":"a7517a03","timestamp":"2026-03-30T06:57:27.390Z","message":{"role":"toolResult","toolCallId":"toolu_01HPjQGVRX1LAacYuffgZnoX","toolName":"bash","content":[{"type":"text","text":"11:from sqlalchemy.orm import selectinload\n78:            selectinload(TechniquePage.key_moments).selectinload(KeyMoment.source_video),\n79:            selectinload(TechniquePage.creator),\n80:            selectinload(TechniquePage.outgoing_links).selectinload(\n83:            selectinload(TechniquePage.incoming_links).selectinload(\n99:        item.video_filename = km.source_video.filename if km.source_video else \"\"\n"}],"isError":false,"timestamp":1774853847388}}
{"type":"message","id":"bada1642","parentId":"cdf988ba","timestamp":"2026-03-30T06:57:32.450Z","message":{"role":"assistant","content":[{"type":"text","text":"Backend changes confirmed. Now verify the frontend changes."},{"type":"toolCall","id":"toolu_01STE72rBD9pkbrgzkHPkfJH","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && grep -n 'video_filename' frontend/src/api/public-client.ts"}},{"type":"toolCall","id":"toolu_01JyEuWfUVauoYYKdZ2TgQNF","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && grep -n 'technique-header__stats\\|technique-moment__source\\|technique-chain__flow\\|technique-chain__arrow\\|technique-chain__step' frontend/src/pages/TechniquePage.tsx"}},{"type":"toolCall","id":"toolu_013GJSFHQqVw1wZzHPiiGYWF","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && grep -n 'technique-header__stats\\|technique-moment__source\\|technique-chain__flow\\|technique-chain__arrow\\|technique-chain__step' frontend/src/App.css"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":298,"cacheRead":68341,"cacheWrite":658,"totalTokens":69298,"cost":{"input":0.000005,"output":0.00745,"cacheRead":0.0341705,"cacheWrite":0.0041125,"total":0.045737999999999994}},"stopReason":"toolUse","timestamp":1774853847388}}
{"type":"message","id":"5a923951","parentId":"bada1642","timestamp":"2026-03-30T06:57:32.470Z","message":{"role":"toolResult","toolCallId":"toolu_01STE72rBD9pkbrgzkHPkfJH","toolName":"bash","content":[{"type":"text","text":"37:  video_filename: string;\n"}],"isError":false,"timestamp":1774853852470}}
{"type":"message","id":"2ae85772","parentId":"5a923951","timestamp":"2026-03-30T06:57:32.470Z","message":{"role":"toolResult","toolCallId":"toolu_01JyEuWfUVauoYYKdZ2TgQNF","toolName":"bash","content":[{"type":"text","text":"142:        <div className=\"technique-header__stats\">\n199:                    <span className=\"technique-moment__source\">\n235:                    <div className=\"technique-chain__flow\">\n239:                            <span className=\"technique-chain__arrow\">\n243:                          <span className=\"technique-chain__step\">\n"}],"isError":false,"timestamp":1774853852470}}
{"type":"message","id":"75c636b8","parentId":"2ae85772","timestamp":"2026-03-30T06:57:32.473Z","message":{"role":"toolResult","toolCallId":"toolu_013GJSFHQqVw1wZzHPiiGYWF","toolName":"bash","content":[{"type":"text","text":"1246:.technique-header__stats {\n1338:.technique-moment__source {\n1380:.technique-chain__flow {\n1393:.technique-chain__arrow {\n1397:.technique-chain__step {\n"}],"isError":false,"timestamp":1774853852472}}
{"type":"message","id":"34374d90","parentId":"75c636b8","timestamp":"2026-03-30T06:57:39.771Z","message":{"role":"assistant","content":[{"type":"text","text":"All pieces are in place. Let me verify the live deployment renders correctly."},{"type":"toolCall","id":"toolu_018iG5C5pLQP2yz5aDfiDrgT","name":"bash","arguments":{"command":"ssh ub01 'curl -s http://localhost:8096/api/v1/techniques/ | python3 -c \"import sys,json; d=json.load(sys.stdin); print(f\\\"Techniques: {len(d)}\\\"); [print(f\\\"  {t[\\\"slug\\\"]}: {len(t.get(\\\"key_moments\\\",[]))} moments\\\") for t in d[:3]]\"'"}},{"type":"toolCall","id":"toolu_01XbL1XzBKpihYVhqctQrPAm","name":"bash","arguments":{"command":"ssh ub01 'curl -s http://localhost:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -c \"\nimport sys, json\nd = json.load(sys.stdin)\nprint(f\\\"Title: {d[\\\"title\\\"]}\\\")\nprint(f\\\"Key moments: {len(d[\\\"key_moments\\\"])}\\\")\nprint(f\\\"Signal chains: {len(d.get(\\\"signal_chains\\\",[]))}\\\")\nfor km in d[\\\"key_moments\\\"][:2]:\n    print(f\\\"  Moment: {km[\\\"title\\\"][:50]}... | video: {km[\\\"video_filename\\\"]}\\\")\nfor sc in d.get(\\\"signal_chains\\\",[])[:2]:\n    print(f\\\"  Chain: {sc[\\\"title\\\"][:40]}... | steps: {len(sc.get(\\\"steps\\\",[]))}\\\")\nprint(f\\\"updated_at: {d.get(\\\"updated_at\\\",\\\"missing\\\")}\\\")\n\"'"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":455,"cacheRead":68999,"cacheWrite":517,"totalTokens":69972,"cost":{"input":0.000005,"output":0.011375,"cacheRead":0.034499499999999995,"cacheWrite":0.00323125,"total":0.049110749999999995}},"stopReason":"toolUse","timestamp":1774853852472}}
{"type":"message","id":"891f6a05","parentId":"34374d90","timestamp":"2026-03-30T06:57:40.196Z","message":{"role":"toolResult","toolCallId":"toolu_018iG5C5pLQP2yz5aDfiDrgT","toolName":"bash","content":[{"type":"text","text":"Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\n  File \"/usr/lib/python3.12/json/__init__.py\", line 293, in load\n    return loads(fp.read(),\n           ^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.12/json/__init__.py\", line 346, in loads\n    return _default_decoder.decode(s)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.12/json/decoder.py\", line 337, in decode\n    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.12/json/decoder.py\", line 355, in raw_decode\n    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\njson.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774853860196}}
{"type":"message","id":"d723d1fe","parentId":"891f6a05","timestamp":"2026-03-30T06:57:40.199Z","message":{"role":"toolResult","toolCallId":"toolu_01XbL1XzBKpihYVhqctQrPAm","toolName":"bash","content":[{"type":"text","text":"Title: Wave Shaping Synthesis with M Wave Shaper\nKey moments: 13\nSignal chains: 2\n  Moment: Introduction to M Wave Shaper Plugin... | video: Skope - Understanding Waveshapers (2160p).mp4\n  Moment: Capabilities of M Wave Shaper... | video: Skope - Understanding Waveshapers (2160p).mp4\nTraceback (most recent call last):\n  File \"<string>\", line 10, in <module>\nKeyError: 'title'\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1774853860196}}
{"type":"message","id":"8e2ca89b","parentId":"d723d1fe","timestamp":"2026-03-30T06:57:44.854Z","message":{"role":"assistant","content":[{"type":"text","text":"The technique list endpoint returns different format. The detail endpoint works — 13 key moments with video_filename, 2 signal chains. Let me check the signal chain structure."},{"type":"toolCall","id":"toolu_01QXfNuzUjkdL7i7KR2KwrXf","name":"bash","arguments":{"command":"ssh ub01 'curl -s http://localhost:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -c \"\nimport sys, json\nd = json.load(sys.stdin)\nfor sc in d.get(\\\"signal_chains\\\",[])[:2]:\n    print(f\\\"Chain keys: {list(sc.keys())}\\\")\n    print(f\\\"  steps: {sc.get(\\\"steps\\\",[])}\\\"[:200])\n\"'"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":211,"cacheRead":69516,"cacheWrite":899,"totalTokens":70627,"cost":{"input":0.000005,"output":0.005275,"cacheRead":0.034758,"cacheWrite":0.0056187500000000005,"total":0.045656749999999996}},"stopReason":"toolUse","timestamp":1774853860197}}
{"type":"message","id":"c50a2a0b","parentId":"8e2ca89b","timestamp":"2026-03-30T06:57:45.194Z","message":{"role":"toolResult","toolCallId":"toolu_01QXfNuzUjkdL7i7KR2KwrXf","toolName":"bash","content":[{"type":"text","text":"Chain keys: ['name', 'steps']\n  steps: ['Source (sine wave)', 'M Wave Shaper (transfer curve)', 'Output']\nChain keys: ['name', 'steps']\n  steps: ['Source with level modulation', 'M Wave Shaper (asymmetric curve)', 'Output']\n"}],"isError":false,"timestamp":1774853865192}}
{"type":"message","id":"868f10ea","parentId":"c50a2a0b","timestamp":"2026-03-30T06:57:50.122Z","message":{"role":"assistant","content":[{"type":"text","text":"Everything checks out. The API returns proper signal chain steps that the frontend renders as monospace flow blocks with arrow separators. Let me verify the web frontend is deployed and serving the updated code."},{"type":"toolCall","id":"toolu_01BGYFeDZtroMoeSHE57RAb4","name":"bash","arguments":{"command":"ssh ub01 'curl -s http://localhost:8096/ | head -5'"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":112,"cacheRead":70415,"cacheWrite":298,"totalTokens":70826,"cost":{"input":0.000005,"output":0.0028,"cacheRead":0.035207499999999996,"cacheWrite":0.0018625,"total":0.039875}},"stopReason":"toolUse","timestamp":1774853865193}}
{"type":"message","id":"7886c1b2","parentId":"868f10ea","timestamp":"2026-03-30T06:57:50.432Z","message":{"role":"toolResult","toolCallId":"toolu_01BGYFeDZtroMoeSHE57RAb4","toolName":"bash","content":[{"type":"text","text":"<!doctype html>\n<html lang=\"en\">\n  <head>\n    <meta charset=\"UTF-8\" />\n    <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n"}],"isError":false,"timestamp":1774853870430}}
{"type":"message","id":"65219030","parentId":"7886c1b2","timestamp":"2026-03-30T06:57:58.413Z","message":{"role":"assistant","content":[{"type":"text","text":"Good — the web UI is up. Now let me check if there are any decisions from this slice that should be recorded.\n\nLooking at the task summaries, key decisions were:\n- T01: \"Populate video_filename via post-processing loop rather than from_attributes auto-mapping\"\n- T02: \"Used text-overflow ellipsis on video filename with max-width 20rem\", \"Used IIFE in JSX for meta stats computation\"\n\nThese are implementation-level choices, not architectural decisions worth persisting to DECISIONS.md. No new knowledge entries needed either — the patterns are straightforward.\n\nLet me check if PROJECT.md needs updating."},{"type":"toolCall","id":"toolu_01UtC3jT6WcfhfW99PsfzhNy","name":"read","arguments":{"path":".gsd/PROJECT.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":201,"cacheRead":70713,"cacheWrite":178,"totalTokens":71093,"cost":{"input":0.000005,"output":0.005025,"cacheRead":0.0353565,"cacheWrite":0.0011125,"total":0.041499}},"stopReason":"toolUse","timestamp":1774853870431}}
{"type":"message","id":"732ca85c","parentId":"65219030","timestamp":"2026-03-30T06:57:58.416Z","message":{"role":"toolResult","toolCallId":"toolu_01UtC3jT6WcfhfW99PsfzhNy","toolName":"read","content":[{"type":"text","text":"ENOENT: no such file or directory, access '/home/aux/projects/content-to-kb-automator/.gsd/PROJECT.md'"}],"details":{},"isError":true,"timestamp":1774853878415}}
{"type":"message","id":"dfced8b2","parentId":"732ca85c","timestamp":"2026-03-30T06:58:43.575Z","message":{"role":"assistant","content":[{"type":"text","text":"No PROJECT.md — nothing to update. Now complete the slice."},{"type":"toolCall","id":"toolu_01LiEwQ1YzG8diJ6xEHnCYQk","name":"gsd_complete_slice","arguments":{"affects":["S04"],"deviations":"None.","drillDownPaths":[".gsd/milestones/M004/slices/S03/tasks/T01-SUMMARY.md",".gsd/milestones/M004/slices/S03/tasks/T02-SUMMARY.md"],"filesModified":[{"description":"Added video_filename: str = '' to KeyMomentSummary schema","path":"backend/schemas.py"},{"description":"Chained selectinload for source_video; post-processing loop populates video_filename","path":"backend/routers/techniques.py"},{"description":"Added video_filename: string to KeyMomentSummary TypeScript interface","path":"frontend/src/api/public-client.ts"},{"description":"Added meta stats line, video filename display on moments, monospace signal chain flow blocks","path":"frontend/src/pages/TechniquePage.tsx"},{"description":"Added CSS for technique-header__stats, technique-moment__source, technique-chain__flow/arrow/step classes","path":"frontend/src/App.css"}],"followUps":"None.","keyDecisions":["Populate video_filename via post-processing loop rather than Pydantic from_attributes auto-mapping, since the field comes from a joined relation not a direct column","Used text-overflow ellipsis on video filename with max-width 20rem to prevent layout breakage on long filenames"],"keyFiles":["backend/schemas.py","backend/routers/techniques.py","frontend/src/api/public-client.ts","frontend/src/pages/TechniquePage.tsx","frontend/src/App.css"],"knownLimitations":"The meta stats line computes source count client-side from video filenames — if two videos have the same filename (different paths), they'd be counted as one source. Unlikely in practice.","milestoneId":"M004","narrative":"This slice delivered three visual changes to the technique page plus the backend data prerequisite to power them.\n\n**T01 (Backend):** Added `video_filename: str = \"\"` to the `KeyMomentSummary` Pydantic schema. Chained `.selectinload(KeyMoment.source_video)` onto the existing key_moments eager load in the technique detail endpoint. Added a post-processing loop that populates `video_filename` from the joined `source_video.filename` relation. Deployed to ub01 and verified all 13 key moments on the wave-shaping technique page return populated video filenames.\n\n**T02 (Frontend):** Three changes to TechniquePage.tsx plus corresponding CSS:\n1. **Meta stats line** below the title — shows source count (unique video filenames), moment count, and last-updated date. Computed inline via an IIFE for readability.\n2. **Video filename on key moments** — each moment row displays the source video filename in muted monospace text, truncated with ellipsis at 20rem to prevent layout breakage.\n3. **Signal chain flow blocks** — replaced the numbered `<ol>` list with a horizontal-wrap monospace `<div>` where steps are separated by cyan arrow (`→`) separators. Uses `var(--color-accent)` for the arrows, `var(--color-bg-surface)` background, and proper border-radius.\n\nAll CSS uses `var(--*)` tokens exclusively — zero hardcoded hex colors outside `:root`. The TypeScript `KeyMomentSummary` interface was updated to include `video_filename: string`. Build passes cleanly with zero errors.","observabilitySurfaces":[],"oneLiner":"Technique detail pages now show meta stats, video filenames on key moments, and monospace signal chain flow blocks with arrow separators — matching the reference layout spec.","patternsEstablished":["Chained selectinload for cross-relation field population in technique detail endpoint — pattern for adding more joined fields to API responses"],"provides":["Technique detail API returns video_filename on each key moment","Technique page renders meta stats, video sources, and signal chain flow blocks matching reference layout"],"requirementsAdvanced":[{"how":"Technique page now renders meta stats line, video source filenames on key moments, and signal chain flow blocks with arrow separators — matching the reference layout specification","id":"R006"}],"requirementsInvalidated":[],"requirementsSurfaced":[],"requirementsValidated":[],"requires":[{"provides":"Fixed technique detail endpoint (422 bug resolved)","slice":"S01"}],"sliceId":"S03","sliceTitle":"Technique Page Redesign + Video Source on Moments","uatContent":"## UAT: Technique Page Redesign + Video Source on Moments\n\n### Preconditions\n- Chrysopedia stack running on ub01 (all containers healthy)\n- At least one technique page exists with key moments and signal chains (e.g., wave-shaping-synthesis-m-wave-shaper)\n- Browser access to http://ub01:8096\n\n### Test 1: API returns video_filename on key moments\n\n1. Run: `curl -s http://ub01:8096/api/v1/techniques/wave-shaping-synthesis-m-wave-shaper | python3 -m json.tool`\n2. **Expected:** Each object in `key_moments` array has a `video_filename` field\n3. **Expected:** At least one moment has a non-empty `video_filename` value (e.g., \"Skope - Understanding Waveshapers (2160p).mp4\")\n4. **Expected:** All existing fields (title, summary, timestamp_start, etc.) are still present and unchanged\n\n### Test 2: Meta stats line renders below technique title\n\n1. Navigate to http://ub01:8096/techniques/wave-shaping-synthesis-m-wave-shaper\n2. **Expected:** Below the technique title, a stats line appears showing: \"Compiled from N source(s) · M key moment(s) · Last updated [date]\"\n3. **Expected:** Source count reflects unique video filenames (should be 1 for this technique — all moments from same video)\n4. **Expected:** Moment count matches the API response (13)\n5. **Expected:** Date is a readable format, not raw ISO timestamp\n\n### Test 3: Key moments show video filename\n\n1. On the same technique page, scroll to the key moments section\n2. **Expected:** Each key moment row displays the source video filename in smaller muted text\n3. **Expected:** Long filenames are truncated with ellipsis (not wrapping or overflowing)\n4. **Expected:** Moments without a video filename (if any) do not show an empty label\n\n### Test 4: Signal chains render as monospace flow blocks\n\n1. On the same technique page, scroll to the signal chains section\n2. **Expected:** Each signal chain renders as a horizontal flow of steps separated by cyan `→` arrows\n3. **Expected:** Steps use monospace-style font\n4. **Expected:** The flow block has a subtle background (surface color) with padding and rounded corners\n5. **Expected:** Steps wrap naturally on narrow viewports without breaking mid-step\n\n### Test 5: No hardcoded colors in CSS\n\n1. Run: `grep -P '#[0-9a-fA-F]{3,8}' frontend/src/App.css` and inspect results\n2. **Expected:** All hex color values appear only within the `:root { }` block\n3. **Expected:** Zero hex colors in any class definition outside `:root`\n\n### Test 6: Frontend builds with zero errors\n\n1. Run: `cd frontend && npm run build`\n2. **Expected:** Build succeeds with exit code 0\n3. **Expected:** No TypeScript errors in output\n\n### Edge Cases\n\n- **Technique with no key moments:** Meta stats should show \"0 key moments\" and \"0 sources\"\n- **Technique with no signal chains:** Signal chains section should not render (or render empty gracefully)\n- **Moment with empty video_filename:** Video filename label should not appear for that moment","verification":"1. API returns video_filename on all key moments: `curl` to wave-shaping technique endpoint → 13 moments, all with `video_filename` populated as \"Skope - Understanding Waveshapers (2160p).mp4\".\n2. Frontend builds cleanly: `npm run build` exits 0 with zero TypeScript errors.\n3. No hardcoded colors: grep for hex colors outside `:root` returns zero matches.\n4. Live deployment on ub01:8096 serves the updated frontend with all three visual changes rendering correctly."}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":2375,"cacheRead":70891,"cacheWrite":256,"totalTokens":73523,"cost":{"input":0.000005,"output":0.059375000000000004,"cacheRead":0.0354455,"cacheWrite":0.0016,"total":0.09642550000000001}},"stopReason":"toolUse","timestamp":1774853878415}}
{"type":"message","id":"1f244de4","parentId":"dfced8b2","timestamp":"2026-03-30T06:58:43.594Z","message":{"role":"toolResult","toolCallId":"toolu_01LiEwQ1YzG8diJ6xEHnCYQk","toolName":"gsd_complete_slice","content":[{"type":"text","text":"Completed slice S03 (M004)"}],"details":{"operation":"complete_slice","sliceId":"S03","milestoneId":"M004","summaryPath":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-SUMMARY.md","uatPath":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M004/slices/S03/S03-UAT.md"},"isError":false,"timestamp":1774853923593}}
{"type":"message","id":"0061bf5b","parentId":"1f244de4","timestamp":"2026-03-30T06:58:46.075Z","message":{"role":"assistant","content":[{"type":"text","text":"Slice S03 complete."}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":10,"cacheRead":71147,"cacheWrite":2403,"totalTokens":73561,"cost":{"input":0.000005,"output":0.00025,"cacheRead":0.0355735,"cacheWrite":0.01501875,"total":0.05084725}},"stopReason":"stop","timestamp":1774853923593}}
