{"type":"thinking_level_change","id":"fbc67663","parentId":null,"timestamp":"2026-04-03T00:48:57.301Z","thinkingLevel":"medium"}
{"type":"model_change","id":"b0053456","parentId":"fbc67663","timestamp":"2026-04-03T00:48:57.302Z","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\nA researcher explored the codebase and a planner decomposed the work — you are the executor. The task plan below is your authoritative contract for the slice goal and verification bar, but it is not a substitute for local reality. Verify the referenced files and surrounding code before changing them. Do not do broad re-research or spontaneous re-planning. Small factual corrections, file-path fixes, and local implementation adaptations are part of execution. Escalate to `blocker_discovered: true` only when the slice contract or downstream task graph no longer holds.\n\n\n\n\n\n## Backing Source Artifacts\n- Slice plan: `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/S01-PLAN.md`\n- Task plan source: `.gsd/milestones/M014/slices/S01/tasks/T01-PLAN.md`\n- Prior task summaries in this slice:\n- (no prior tasks)\n\nThen:\n0. Narrate step transitions, key implementation decisions, and verification outcomes as you work. Keep it terse — one line between tool-call clusters, not between every call — but write complete sentences in user-facing prose, not shorthand notes or scratchpad fragments.\n1.  Follow any activated skills before writing code. If no skills match this task, skip this step.\n2. Execute the steps in the inlined task plan, adapting minor local mismatches when the surrounding code differs from the planner's snapshot\n3. Build the real thing. If the task plan says \"create login endpoint\", build an endpoint that actually authenticates against a real store, not one that returns a hardcoded success response. If the task plan says \"create dashboard page\", build a page that renders real data from the API, not a component with hardcoded props. Stubs and mocks are for tests, not for the shipped feature.\n4. Write or update tests as part of execution — tests are verification, not an afterthought. If the slice plan defines test files in its Verification section and this is the first task, create them (they should initially fail).\n5. When implementing non-trivial runtime behavior (async flows, API boundaries, background processes, error paths), add or preserve agent-usable observability. Skip this for simple changes where it doesn't apply.\n\n   **Background process rule:** Never use bare `command &` to run background processes. The shell's `&` operator leaves stdout/stderr attached to the parent, which causes the Bash tool to hang indefinitely waiting for those streams to close. Always redirect output before backgrounding:\n   - Correct: `command > /dev/null 2>&1 &` or `nohup command > /dev/null 2>&1 &`\n   - Example: `python -m http.server 8080 > /dev/null 2>&1 &` (NOT `python -m http.server 8080 &`)\n   - Preferred: use the `bg_shell` tool if available — it manages process lifecycle correctly without stream-inheritance issues\n6. If the task plan includes a **Failure Modes** section (Q5), implement the error/timeout/malformed handling specified. Verify each dependency's failure path is handled. Skip if the section is absent.\n7. If the task plan includes a **Load Profile** section (Q6), implement protections for the identified 10x breakpoint (connection pooling, rate limiting, pagination, etc.). Skip if absent.\n8. If the task plan includes a **Negative Tests** section (Q7), write the specified negative test cases alongside the happy-path tests — malformed inputs, error paths, and boundary conditions. Skip if absent.\n9. Verify must-haves are met by running concrete checks (tests, commands, observable behaviors)\n10. Run the slice-level verification checks defined in the slice plan's Verification section. Track which pass. On the final task of the slice, all must pass before marking done. On intermediate tasks, partial passes are expected — note which ones pass in the summary.\n11. After the verification gate runs (you'll see gate results in stderr/notify output), populate the `## Verification Evidence` table in your task summary with the check results. Use the `formatEvidenceTable` format: one row per check with command, exit code, verdict (✅ pass / ❌ fail), and duration. If no verification commands were discovered, note that in the section.\n12. If the task touches UI, browser flows, DOM behavior, or user-visible web state:\n   - exercise the real flow in the browser\n   - prefer `browser_batch` when the next few actions are obvious and sequential\n   - prefer `browser_assert` for explicit pass/fail verification of the intended outcome\n   - use `browser_diff` when an action's effect is ambiguous\n   - use console/network/dialog diagnostics when validating async, stateful, or failure-prone UI\n   - record verification in terms of explicit checks passed/failed, not only prose interpretation\n13. If the task plan includes an Observability Impact section, verify those signals directly. Skip this step if the task plan omits the section.\n14. **If execution is running long or verification fails:**\n\n    **Context budget:** You have approximately **~80K chars** reserved for verification context. If you've used most of your context and haven't finished all steps, stop implementing and prioritize writing the task summary with clear notes on what's done and what remains. A partial summary that enables clean resumption is more valuable than one more half-finished step with no documentation. Never sacrifice summary quality for one more implementation step.\n\n    **Debugging discipline:** If a verification check fails or implementation hits unexpected behavior:\n    - Form a hypothesis first. State what you think is wrong and why, then test that specific theory. Don't shotgun-fix.\n    - Change one variable at a time. Make one change, test, observe. Multiple simultaneous changes mean you can't attribute what worked.\n    - Read completely. When investigating, read entire functions and their imports, not just the line that looks relevant.\n    - Distinguish \"I know\" from \"I assume.\" Observable facts (the error says X) are strong evidence. Assumptions (this library should work this way) need verification.\n    - Know when to stop. If you've tried 3+ fixes without progress, your mental model is probably wrong. Stop. List what you know for certain. List what you've ruled out. Form fresh hypotheses from there.\n    - Don't fix symptoms. Understand *why* something fails before changing code. A test that passes after a change you don't understand is luck, not a fix.\n15. **Blocker discovery:** If execution reveals that the remaining slice plan is fundamentally invalid — not just a bug or minor deviation, but a plan-invalidating finding like a wrong API, missing capability, or architectural mismatch — set `blocker_discovered: true` in the task summary frontmatter and describe the blocker clearly in the summary narrative. Do NOT set `blocker_discovered: true` for ordinary debugging, minor deviations, or issues that can be fixed within the current task or the remaining plan. This flag triggers an automatic replan of the slice.\n16. If you made an architectural, pattern, library, or observability decision during this task that downstream work should know about, append it to `.gsd/DECISIONS.md` (read the template at `~/.gsd/agent/extensions/gsd/templates/decisions.md` if the file doesn't exist yet). Not every task produces decisions — only append when a meaningful choice was made.\n17. If you discover a non-obvious rule, recurring gotcha, or useful pattern during execution, append it to `.gsd/KNOWLEDGE.md`. Only add entries that would save future agents from repeating your investigation. Don't add obvious things.\n18. Read the template at `~/.gsd/agent/extensions/gsd/templates/task-summary.md`\n19. Write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/tasks/T01-SUMMARY.md`\n20. Call `gsd_complete_task` with milestone_id, slice_id, task_id, and a summary of what was accomplished. This is your final required step — do NOT manually edit PLAN.md checkboxes. The tool marks the task complete, updates the DB, and renders PLAN.md automatically.\n21. Do not run git commands — the system reads your task summary after completion and creates a meaningful commit from it (type inferred from title, message from your one-liner, key files from frontmatter). Write a clear, specific one-liner in the summary — it becomes the commit message.\n\nAll work stays in your working directory: `/home/aux/projects/content-to-kb-automator`.\n\n**You MUST call `gsd_complete_task` AND write `/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/tasks/T01-SUMMARY.md` before finishing.**\n\nWhen done, say: \"Task T01 complete.\"\n## Slice Plan Excerpt\nSource: `.gsd/milestones/M014/slices/S01/S01-PLAN.md`\n**Goal:** Stage 5 synthesis prompt produces body_sections as a list of BodySection objects with H2/H3 nesting and inline [N] citation markers, validated by schema and test harness.\n**Demo:** After this: Run test harness with new prompt → output has list-of-objects body_sections with H2/H3 nesting, citation markers on key claims, broader page scope.\n\n## UNIT: Execute Task T01 (\"Add BodySection schema models and citation validation utility\") — Slice S01 (\"Synthesis Prompt v5 — Nested Sections + Citations\"), Milestone M014\n\n## Resume State\n- No continue file present. Start from the top of the task plan.\n\n## Carry-Forward Context\n- No prior task summaries in this slice.\n\n## Inlined Task Plan (authoritative local execution contract)\nSource: `.gsd/milestones/M014/slices/S01/tasks/T01-PLAN.md`\n\n---\nestimated_steps: 18\nestimated_files: 3\nskills_used: []\n---\n\n# T01: Add BodySection schema models and citation validation utility\n\nAdd BodySubSection and BodySection Pydantic models to schemas.py. Change SynthesizedPage.body_sections from dict to list[BodySection]. Add body_sections_format field. Create a small citation validation utility (validate_citations) that checks [N] markers in section content against a moment count. This utility is reused by the test harness in T03.\n\n## Steps\n\n1. Read `backend/pipeline/schemas.py` fully.\n2. Add `BodySubSection` model with `heading: str` and `content: str` fields.\n3. Add `BodySection` model with `heading: str`, `content: str`, and `subsections: list[BodySubSection]` (default_factory=list).\n4. Change `SynthesizedPage.body_sections` type from `dict` to `list[BodySection]` with updated description.\n5. Add `body_sections_format: str = Field(default='v2')` to `SynthesizedPage`.\n6. Create `backend/pipeline/citation_utils.py` with:\n   - `extract_citations(text: str) -> list[int]` — regex extracts all `[N]` and `[N,M]` markers, returns sorted unique indices.\n   - `validate_citations(sections: list[BodySection], moment_count: int) -> dict` — returns `{valid: bool, total_citations: int, invalid_indices: list[int], uncited_moments: list[int], coverage_pct: float}`.\n7. Add unit tests in `backend/pipeline/test_citation_utils.py` covering: valid citations, out-of-range indices, multi-citation markers `[0,2]`, no citations, empty sections.\n\n## Must-Haves\n\n- [ ] BodySubSection and BodySection models exist with correct field types\n- [ ] SynthesizedPage.body_sections is list[BodySection]\n- [ ] body_sections_format field defaults to 'v2'\n- [ ] extract_citations parses [N] and [N,M] markers correctly\n- [ ] validate_citations returns coverage stats and flags invalid indices\n- [ ] Unit tests pass\n\n## Inputs\n\n- ``backend/pipeline/schemas.py` — existing schema file with SynthesizedPage model`\n\n## Expected Output\n\n- ``backend/pipeline/schemas.py` — updated with BodySection, BodySubSection models and modified SynthesizedPage`\n- ``backend/pipeline/citation_utils.py` — citation extraction and validation utilities`\n- ``backend/pipeline/test_citation_utils.py` — unit tests for citation utilities`\n\n## Verification\n\ncd /home/aux/projects/content-to-kb-automator && python -m pytest backend/pipeline/test_citation_utils.py -v\n","display":false,"id":"e485e37a","parentId":"b0053456","timestamp":"2026-04-03T00:48:57.305Z"}
{"type":"message","id":"f6da96e9","parentId":"e485e37a","timestamp":"2026-04-03T00:49:00.470Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me start by reading the existing schemas.py file to understand the current structure.","thinkingSignature":"EpQCClkIDBgCKkCP8g17TOpdKIn46NXb/OnJY+3FT1R/PuPZjmQFXVeIkIcVmmHmFtWQ98ETbSBoVRjISVku0FIVzzcifAJ0CCWAMg9jbGF1ZGUtb3B1cy00LTY4ABIMeHLL6I1EJRnjRLGhGgxvKEBdKG0rSFd+fzUiMN2/osvuzQ8i8kwFc1xyMWY10HiIub6O2AiImGD0GXTBG5d9zlBphixvCehUj3kdLCpplQU6p5FWo3pPmz84yvyWP6fxtFb3ILULlpqqx0mUtLKkp9SGH7FSMh+3IGpro7yZfriwaU2P09jMDnAYGKuCG53lAFxE+gdPirN4LTzoF4pqskLTwkSw0zYDqMZP20sodrDMfBnai7LqGAE="},{"type":"toolCall","id":"toolu_012KR2XdbV4DVV6UbNr8ZAdC","name":"read","arguments":{"path":"backend/pipeline/schemas.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":2,"output":90,"cacheRead":59865,"cacheWrite":3380,"totalTokens":63337,"cost":{"input":0.00001,"output":0.0022500000000000003,"cacheRead":0.029932499999999997,"cacheWrite":0.021125,"total":0.053317500000000004}},"stopReason":"toolUse","timestamp":1775177337303}}
{"type":"message","id":"c2f0f38c","parentId":"f6da96e9","timestamp":"2026-04-03T00:49:00.478Z","message":{"role":"toolResult","toolCallId":"toolu_012KR2XdbV4DVV6UbNr8ZAdC","toolName":"read","content":[{"type":"text","text":"\"\"\"Pydantic schemas for pipeline stage inputs and outputs.\n\nStage 2 — Segmentation: groups transcript segments by topic.\nStage 3 — Extraction: extracts key moments from segments.\nStage 4 — Classification: classifies moments by category/tags.\nStage 5 — Synthesis: generates technique pages from classified moments.\n\"\"\"\n\nfrom __future__ import annotations\n\nfrom pydantic import BaseModel, Field\n\n\n# ── Stage 2: Segmentation ───────────────────────────────────────────────────\n\nclass TopicSegment(BaseModel):\n    \"\"\"A contiguous group of transcript segments sharing a topic.\"\"\"\n\n    start_index: int = Field(description=\"First transcript segment index in this group\")\n    end_index: int = Field(description=\"Last transcript segment index in this group (inclusive)\")\n    topic_label: str = Field(description=\"Short label describing the topic\")\n    summary: str = Field(description=\"Brief summary of what is discussed\")\n\n\nclass SegmentationResult(BaseModel):\n    \"\"\"Full output of stage 2 (segmentation).\"\"\"\n\n    segments: list[TopicSegment]\n\n\n# ── Stage 3: Extraction ─────────────────────────────────────────────────────\n\nclass ExtractedMoment(BaseModel):\n    \"\"\"A single key moment extracted from a topic segment group.\"\"\"\n\n    title: str = Field(description=\"Concise title for the moment\")\n    summary: str = Field(description=\"Detailed summary of the technique/concept\")\n    start_time: float = Field(description=\"Start time in seconds\")\n    end_time: float = Field(description=\"End time in seconds\")\n    content_type: str = Field(description=\"One of: technique, settings, reasoning, workflow\")\n    plugins: list[str] = Field(default_factory=list, description=\"Plugins/tools mentioned\")\n    raw_transcript: str = Field(default=\"\", description=\"Raw transcript text for this moment\")\n\n\nclass ExtractionResult(BaseModel):\n    \"\"\"Full output of stage 3 (extraction).\"\"\"\n\n    moments: list[ExtractedMoment]\n\n\n# ── Stage 4: Classification ─────────────────────────────────────────────────\n\nclass ClassifiedMoment(BaseModel):\n    \"\"\"Classification metadata for a single extracted moment.\"\"\"\n\n    moment_index: int = Field(description=\"Index into ExtractionResult.moments\")\n    topic_category: str = Field(description=\"High-level topic category\")\n    topic_tags: list[str] = Field(default_factory=list, description=\"Specific topic tags\")\n    content_type_override: str | None = Field(\n        default=None,\n        description=\"Override for content_type if classification disagrees with extraction\",\n    )\n\n\nclass ClassificationResult(BaseModel):\n    \"\"\"Full output of stage 4 (classification).\"\"\"\n\n    classifications: list[ClassifiedMoment]\n\n\n# ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n\nclass SynthesizedPage(BaseModel):\n    \"\"\"A technique page synthesized from classified moments.\"\"\"\n\n    title: str = Field(description=\"Page title\")\n    slug: str = Field(description=\"URL-safe slug\")\n    topic_category: str = Field(description=\"Primary topic category\")\n    topic_tags: list[str] = Field(default_factory=list, description=\"Associated tags\")\n    summary: str = Field(description=\"Page summary / overview paragraph\")\n    body_sections: dict = Field(\n        default_factory=dict,\n        description=\"Structured body content as section_name -> content mapping\",\n    )\n    signal_chains: list[dict] = Field(\n        default_factory=list,\n        description=\"Signal chain descriptions (for audio/music production contexts)\",\n    )\n    plugins: list[str] = Field(default_factory=list, description=\"Plugins/tools referenced\")\n    source_quality: str = Field(\n        default=\"mixed\",\n        description=\"One of: structured, mixed, unstructured\",\n    )\n    moment_indices: list[int] = Field(\n        default_factory=list,\n        description=\"Indices of source moments (from the input list) that this page covers\",\n    )\n\n\nclass SynthesisResult(BaseModel):\n    \"\"\"Full output of stage 5 (synthesis).\"\"\"\n\n    pages: list[SynthesizedPage]\n"}],"isError":false,"timestamp":1775177340475}}
{"type":"message","id":"9627e758","parentId":"c2f0f38c","timestamp":"2026-04-03T00:49:11.404Z","message":{"role":"assistant","content":[{"type":"text","text":"Good — I can see the current `SynthesizedPage` with `body_sections: dict`. Now I'll implement all three files."},{"type":"toolCall","id":"toolu_01VDUtNyKnJ4A6HJmRogx2GH","name":"edit","arguments":{"newText":"# ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n\nclass BodySubSection(BaseModel):\n    \"\"\"An H3-level subsection within a body section.\"\"\"\n\n    heading: str = Field(description=\"H3 subsection heading\")\n    content: str = Field(description=\"Subsection body text (may contain [N] citation markers)\")\n\n\nclass BodySection(BaseModel):\n    \"\"\"An H2-level section of a technique page body.\"\"\"\n\n    heading: str = Field(description=\"H2 section heading\")\n    content: str = Field(description=\"Section body text (may contain [N] citation markers)\")\n    subsections: list[BodySubSection] = Field(\n        default_factory=list,\n        description=\"Optional H3-level subsections\",\n    )\n\n\nclass SynthesizedPage(BaseModel):\n    \"\"\"A technique page synthesized from classified moments.\"\"\"\n\n    title: str = Field(description=\"Page title\")\n    slug: str = Field(description=\"URL-safe slug\")\n    topic_category: str = Field(description=\"Primary topic category\")\n    topic_tags: list[str] = Field(default_factory=list, description=\"Associated tags\")\n    summary: str = Field(description=\"Page summary / overview paragraph\")\n    body_sections: list[BodySection] = Field(\n        default_factory=list,\n        description=\"Structured body content as H2 sections with optional H3 subsections\",\n    )\n    body_sections_format: str = Field(\n        default=\"v2\",\n        description=\"Schema version for body_sections ('v2' = list[BodySection])\",\n    )","oldText":"# ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n\nclass SynthesizedPage(BaseModel):\n    \"\"\"A technique page synthesized from classified moments.\"\"\"\n\n    title: str = Field(description=\"Page title\")\n    slug: str = Field(description=\"URL-safe slug\")\n    topic_category: str = Field(description=\"Primary topic category\")\n    topic_tags: list[str] = Field(default_factory=list, description=\"Associated tags\")\n    summary: str = Field(description=\"Page summary / overview paragraph\")\n    body_sections: dict = Field(\n        default_factory=dict,\n        description=\"Structured body content as section_name -> content mapping\",\n    )","path":"backend/pipeline/schemas.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":678,"cacheRead":63245,"cacheWrite":1092,"totalTokens":65016,"cost":{"input":0.000005,"output":0.01695,"cacheRead":0.0316225,"cacheWrite":0.006825,"total":0.05540249999999999}},"stopReason":"toolUse","timestamp":1775177340476}}
{"type":"message","id":"802f9070","parentId":"9627e758","timestamp":"2026-04-03T00:49:11.413Z","message":{"role":"toolResult","toolCallId":"toolu_01VDUtNyKnJ4A6HJmRogx2GH","toolName":"edit","content":[{"type":"text","text":"Successfully replaced text in backend/pipeline/schemas.py."}],"details":{"diff":"  69 \n  70 \n  71 # ── Stage 5: Synthesis ───────────────────────────────────────────────────────\n  72 \n+ 73 class BodySubSection(BaseModel):\n+ 74     \"\"\"An H3-level subsection within a body section.\"\"\"\n+ 75 \n+ 76     heading: str = Field(description=\"H3 subsection heading\")\n+ 77     content: str = Field(description=\"Subsection body text (may contain [N] citation markers)\")\n+ 78 \n+ 79 \n+ 80 class BodySection(BaseModel):\n+ 81     \"\"\"An H2-level section of a technique page body.\"\"\"\n+ 82 \n+ 83     heading: str = Field(description=\"H2 section heading\")\n+ 84     content: str = Field(description=\"Section body text (may contain [N] citation markers)\")\n+ 85     subsections: list[BodySubSection] = Field(\n+ 86         default_factory=list,\n+ 87         description=\"Optional H3-level subsections\",\n+ 88     )\n+ 89 \n+ 90 \n  91 class SynthesizedPage(BaseModel):\n  92     \"\"\"A technique page synthesized from classified moments.\"\"\"\n  93 \n  94     title: str = Field(description=\"Page title\")\n  95     slug: str = Field(description=\"URL-safe slug\")\n  96     topic_category: str = Field(description=\"Primary topic category\")\n  97     topic_tags: list[str] = Field(default_factory=list, description=\"Associated tags\")\n  98     summary: str = Field(description=\"Page summary / overview paragraph\")\n- 81     body_sections: dict = Field(\n- 82         default_factory=dict,\n- 83         description=\"Structured body content as section_name -> content mapping\",\n+ 99     body_sections: list[BodySection] = Field(\n+100         default_factory=list,\n+101         description=\"Structured body content as H2 sections with optional H3 subsections\",\n 102     )\n+103     body_sections_format: str = Field(\n+104         default=\"v2\",\n+105         description=\"Schema version for body_sections ('v2' = list[BodySection])\",\n+106     )\n 107     signal_chains: list[dict] = Field(\n 108         default_factory=list,\n 109         description=\"Signal chain descriptions (for audio/music production contexts)\",\n 110     )","firstChangedLine":73},"isError":false,"timestamp":1775177351412}}
{"type":"message","id":"9283a4ae","parentId":"802f9070","timestamp":"2026-04-03T00:49:24.768Z","message":{"role":"assistant","content":[{"type":"text","text":"Now create the citation utilities module."},{"type":"toolCall","id":"toolu_01AeXtFZ7RJtvV4JuHzP4yjG","name":"write","arguments":{"content":"\"\"\"Citation extraction and validation utilities for synthesized technique pages.\n\nUsed by stage 5 synthesis and the test harness to verify that [N] citation\nmarkers in body sections reference valid source moments.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport re\n\nfrom pipeline.schemas import BodySection\n\n# Matches [N] or [N,M] or [N,M,P] style citation markers where N,M,P are integers.\n_CITATION_RE = re.compile(r\"\\[(\\d+(?:,\\s*\\d+)*)\\]\")\n\n\ndef extract_citations(text: str) -> list[int]:\n    \"\"\"Extract all citation indices from ``[N]`` and ``[N,M,...]`` markers in *text*.\n\n    Returns a sorted list of unique integer indices.\n    \"\"\"\n    indices: set[int] = set()\n    for match in _CITATION_RE.finditer(text):\n        for part in match.group(1).split(\",\"):\n            indices.add(int(part.strip()))\n    return sorted(indices)\n\n\ndef validate_citations(\n    sections: list[BodySection],\n    moment_count: int,\n) -> dict:\n    \"\"\"Validate citation markers across all *sections* against *moment_count* source moments.\n\n    Moments are expected to be referenced as 0-based indices ``[0]`` through\n    ``[moment_count - 1]``.\n\n    Returns a dict with:\n        valid (bool): True when every cited index is in range and every moment is cited.\n        total_citations (int): Count of unique cited indices.\n        invalid_indices (list[int]): Cited indices that are out of range.\n        uncited_moments (list[int]): In-range moment indices that are never cited.\n        coverage_pct (float): Percentage of moments that are cited (0.0–100.0).\n    \"\"\"\n    all_indices: set[int] = set()\n\n    for section in sections:\n        all_indices.update(extract_citations(section.content))\n        for sub in section.subsections:\n            all_indices.update(extract_citations(sub.content))\n\n    valid_range = set(range(moment_count))\n    invalid_indices = sorted(all_indices - valid_range)\n    cited_in_range = all_indices & valid_range\n    uncited_moments = sorted(valid_range - cited_in_range)\n    coverage_pct = (len(cited_in_range) / moment_count * 100.0) if moment_count > 0 else 0.0\n\n    return {\n        \"valid\": len(invalid_indices) == 0 and len(uncited_moments) == 0,\n        \"total_citations\": len(cited_in_range),\n        \"invalid_indices\": invalid_indices,\n        \"uncited_moments\": uncited_moments,\n        \"coverage_pct\": round(coverage_pct, 1),\n    }\n","path":"backend/pipeline/citation_utils.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":777,"cacheRead":64337,"cacheWrite":701,"totalTokens":65816,"cost":{"input":0.000005,"output":0.019425,"cacheRead":0.032168499999999996,"cacheWrite":0.004381250000000001,"total":0.05597975}},"stopReason":"toolUse","timestamp":1775177351412}}
{"type":"message","id":"516ed81b","parentId":"9283a4ae","timestamp":"2026-04-03T00:49:24.771Z","message":{"role":"toolResult","toolCallId":"toolu_01AeXtFZ7RJtvV4JuHzP4yjG","toolName":"write","content":[{"type":"text","text":"Successfully wrote 2355 bytes to backend/pipeline/citation_utils.py"}],"isError":false,"timestamp":1775177364770}}
{"type":"message","id":"a8bfd232","parentId":"516ed81b","timestamp":"2026-04-03T00:49:42.974Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_0158gCWzmehpWjN6svHCzefk","name":"write","arguments":{"content":"\"\"\"Unit tests for citation extraction and validation utilities.\"\"\"\n\nfrom __future__ import annotations\n\nimport pytest\n\nfrom pipeline.citation_utils import extract_citations, validate_citations\nfrom pipeline.schemas import BodySection, BodySubSection\n\n\n# ── extract_citations ────────────────────────────────────────────────────────\n\n\nclass TestExtractCitations:\n    def test_single_markers(self):\n        assert extract_citations(\"This uses reverb [0] and delay [2].\") == [0, 2]\n\n    def test_multi_marker(self):\n        assert extract_citations(\"Combined approach [0,2] works well.\") == [0, 2]\n\n    def test_multi_marker_with_spaces(self):\n        assert extract_citations(\"See [1, 3, 5] for details.\") == [1, 3, 5]\n\n    def test_no_citations(self):\n        assert extract_citations(\"Plain text without citations.\") == []\n\n    def test_duplicate_indices_deduplicated(self):\n        assert extract_citations(\"[1] and again [1] and [1,2]\") == [1, 2]\n\n    def test_returns_sorted(self):\n        assert extract_citations(\"[5] then [1] then [3]\") == [1, 3, 5]\n\n    def test_adjacent_markers(self):\n        assert extract_citations(\"[0][1][2]\") == [0, 1, 2]\n\n    def test_does_not_match_non_numeric_brackets(self):\n        assert extract_citations(\"[abc] and [N] but [7] works\") == [7]\n\n\n# ── validate_citations ──────────────────────────────────────────────────────\n\n\ndef _make_sections(texts: list[str], sub_texts: list[list[str]] | None = None) -> list[BodySection]:\n    \"\"\"Helper to build BodySection lists for testing.\"\"\"\n    sections = []\n    for i, text in enumerate(texts):\n        subs = []\n        if sub_texts and i < len(sub_texts):\n            subs = [BodySubSection(heading=f\"Sub {j}\", content=t) for j, t in enumerate(sub_texts[i])]\n        sections.append(BodySection(heading=f\"Section {i}\", content=text, subsections=subs))\n    return sections\n\n\nclass TestValidateCitations:\n    def test_all_moments_cited(self):\n        sections = _make_sections([\"Uses [0] and [1].\", \"Also [2].\"])\n        result = validate_citations(sections, moment_count=3)\n        assert result[\"valid\"] is True\n        assert result[\"total_citations\"] == 3\n        assert result[\"invalid_indices\"] == []\n        assert result[\"uncited_moments\"] == []\n        assert result[\"coverage_pct\"] == 100.0\n\n    def test_out_of_range_index(self):\n        sections = _make_sections([\"Reference [0] and [5].\"])\n        result = validate_citations(sections, moment_count=3)\n        assert result[\"valid\"] is False\n        assert result[\"invalid_indices\"] == [5]\n        assert result[\"uncited_moments\"] == [1, 2]\n\n    def test_multi_citation_markers(self):\n        sections = _make_sections([\"Combined [0,2] technique.\"])\n        result = validate_citations(sections, moment_count=3)\n        assert result[\"valid\"] is False  # moment 1 uncited\n        assert result[\"total_citations\"] == 2\n        assert result[\"uncited_moments\"] == [1]\n        assert result[\"coverage_pct\"] == pytest.approx(66.7, abs=0.1)\n\n    def test_no_citations_at_all(self):\n        sections = _make_sections([\"Plain text with no markers.\"])\n        result = validate_citations(sections, moment_count=2)\n        assert result[\"valid\"] is False\n        assert result[\"total_citations\"] == 0\n        assert result[\"uncited_moments\"] == [0, 1]\n        assert result[\"coverage_pct\"] == 0.0\n\n    def test_empty_sections(self):\n        result = validate_citations([], moment_count=0)\n        assert result[\"valid\"] is True\n        assert result[\"total_citations\"] == 0\n        assert result[\"coverage_pct\"] == 0.0\n\n    def test_subsection_citations_counted(self):\n        sections = _make_sections(\n            [\"Section text [0].\"],\n            sub_texts=[[\"Subsection cites [1] and [2].\"]],\n        )\n        result = validate_citations(sections, moment_count=3)\n        assert result[\"valid\"] is True\n        assert result[\"total_citations\"] == 3\n\n    def test_zero_moment_count_with_citations(self):\n        \"\"\"Citations exist but moment_count is 0 — all indices are out of range.\"\"\"\n        sections = _make_sections([\"References [0] and [1].\"])\n        result = validate_citations(sections, moment_count=0)\n        assert result[\"valid\"] is False\n        assert result[\"invalid_indices\"] == [0, 1]\n        assert result[\"coverage_pct\"] == 0.0\n","path":"backend/pipeline/test_citation_utils.py"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":1334,"cacheRead":65038,"cacheWrite":806,"totalTokens":67179,"cost":{"input":0.000005,"output":0.033350000000000005,"cacheRead":0.032519,"cacheWrite":0.0050375,"total":0.0709115}},"stopReason":"toolUse","timestamp":1775177364770}}
{"type":"message","id":"70f80f85","parentId":"a8bfd232","timestamp":"2026-04-03T00:49:42.978Z","message":{"role":"toolResult","toolCallId":"toolu_0158gCWzmehpWjN6svHCzefk","toolName":"write","content":[{"type":"text","text":"Successfully wrote 4290 bytes to backend/pipeline/test_citation_utils.py"}],"isError":false,"timestamp":1775177382976}}
{"type":"message","id":"fb2145aa","parentId":"70f80f85","timestamp":"2026-04-03T00:49:51.345Z","message":{"role":"assistant","content":[{"type":"text","text":"Running the tests."},{"type":"toolCall","id":"toolu_01KpCSm5JY8jqsFmmps8gq1S","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && python -m pytest backend/pipeline/test_citation_utils.py -v 2>&1","timeout":30}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":111,"cacheRead":65844,"cacheWrite":1365,"totalTokens":67321,"cost":{"input":0.000005,"output":0.002775,"cacheRead":0.032922,"cacheWrite":0.00853125,"total":0.04423325}},"stopReason":"toolUse","timestamp":1775177382977}}
{"type":"message","id":"d41fbb44","parentId":"fb2145aa","timestamp":"2026-04-03T00:49:51.768Z","message":{"role":"toolResult","toolCallId":"toolu_01KpCSm5JY8jqsFmmps8gq1S","toolName":"bash","content":[{"type":"text","text":"============================= test session starts ==============================\nplatform linux -- Python 3.12.3, pytest-8.4.2, pluggy-1.6.0 -- /usr/local/bin/python\ncachedir: .pytest_cache\nrootdir: /home/aux/projects/content-to-kb-automator/backend\nconfigfile: pytest.ini\nplugins: asyncio-0.24.0, anyio-4.13.0\nasyncio: mode=Mode.AUTO, default_loop_scope=None\ncollecting ... collected 15 items\n\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_single_markers PASSED [  6%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_multi_marker PASSED [ 13%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_multi_marker_with_spaces PASSED [ 20%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_no_citations PASSED [ 26%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_duplicate_indices_deduplicated PASSED [ 33%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_returns_sorted PASSED [ 40%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_adjacent_markers PASSED [ 46%]\nbackend/pipeline/test_citation_utils.py::TestExtractCitations::test_does_not_match_non_numeric_brackets PASSED [ 53%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_all_moments_cited PASSED [ 60%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_out_of_range_index PASSED [ 66%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_multi_citation_markers PASSED [ 73%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_no_citations_at_all PASSED [ 80%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_empty_sections PASSED [ 86%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_subsection_citations_counted PASSED [ 93%]\nbackend/pipeline/test_citation_utils.py::TestValidateCitations::test_zero_moment_count_with_citations PASSED [100%]\n\n============================== 15 passed in 0.09s ==============================\n"}],"isError":false,"timestamp":1775177391767}}
{"type":"message","id":"1392c549","parentId":"d41fbb44","timestamp":"2026-04-03T00:49:56.447Z","message":{"role":"assistant","content":[{"type":"text","text":"All 15 tests pass. Let me verify the schema changes compile correctly too."},{"type":"toolCall","id":"toolu_01XUH6jxi3bUeRavQNUn6aXc","name":"bash","arguments":{"command":"cd /home/aux/projects/content-to-kb-automator && python -c \"from pipeline.schemas import BodySection, BodySubSection, SynthesizedPage; p = SynthesizedPage(title='t', slug='s', topic_category='c', summary='sum'); print(f'body_sections type: {type(p.body_sections)}, format: {p.body_sections_format}')\" 2>&1"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":171,"cacheRead":67209,"cacheWrite":770,"totalTokens":68151,"cost":{"input":0.000005,"output":0.004275,"cacheRead":0.033604499999999995,"cacheWrite":0.0048125,"total":0.04269699999999999}},"stopReason":"toolUse","timestamp":1775177391767}}
{"type":"message","id":"8ea2bdad","parentId":"1392c549","timestamp":"2026-04-03T00:49:56.596Z","message":{"role":"toolResult","toolCallId":"toolu_01XUH6jxi3bUeRavQNUn6aXc","toolName":"bash","content":[{"type":"text","text":"body_sections type: <class 'list'>, format: v2\n"}],"isError":false,"timestamp":1775177396595}}
{"type":"message","id":"feb23f88","parentId":"8ea2bdad","timestamp":"2026-04-03T00:50:01.550Z","message":{"role":"assistant","content":[{"type":"text","text":"Schema validates — `body_sections` is `list`, `body_sections_format` defaults to `'v2'`. Now I'll read the task summary template and write the summary."},{"type":"toolCall","id":"toolu_01APcXotUSryJRLR3M3YcPxW","name":"read","arguments":{"path":"/home/aux/.gsd/agent/extensions/gsd/templates/task-summary.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":113,"cacheRead":67979,"cacheWrite":200,"totalTokens":68293,"cost":{"input":0.000005,"output":0.0028250000000000003,"cacheRead":0.0339895,"cacheWrite":0.00125,"total":0.0380695}},"stopReason":"toolUse","timestamp":1775177396595}}
{"type":"message","id":"dbb91afd","parentId":"feb23f88","timestamp":"2026-04-03T00:50:01.554Z","message":{"role":"toolResult","toolCallId":"toolu_01APcXotUSryJRLR3M3YcPxW","toolName":"read","content":[{"type":"text","text":"---\nid: {{taskId}}\nparent: {{sliceId}}\nmilestone: {{milestoneId}}\nprovides:\n  - {{whatThisTaskProvides}}\nkey_files:\n  - {{filePath}}\nkey_decisions:\n  - {{decision}}\npatterns_established:\n  - {{pattern}}\nobservability_surfaces:\n  - {{status endpoint, structured log, persisted failure state, diagnostic command, or none}}\nduration: {{duration}}\nverification_result: passed\ncompleted_at: {{date}}\n# Set blocker_discovered: true only if execution revealed the remaining slice plan\n# is fundamentally invalid (wrong API, missing capability, architectural mismatch).\n# Do NOT set true for ordinary bugs, minor deviations, or fixable issues.\nblocker_discovered: false\n---\n\n# {{taskId}}: {{taskTitle}}\n\n<!-- One-liner must say what actually shipped, not just that work completed.\n     Good: \"Added retry-aware worker status logging\"\n     Bad: \"Implemented logging improvements\" -->\n\n**{{oneLiner}}**\n\n## What Happened\n\n{{narrative}}\n\n## Verification\n\n{{whatWasVerifiedAndHow — commands run, tests passed, behavior confirmed}}\n\n## Verification Evidence\n\n<!-- Populated from verification gate output. If the gate ran, fill in the table below.\n     If no gate ran (e.g., no verification commands discovered), note that. -->\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| {{row}} | {{command}} | {{exitCode}} | {{verdict}} | {{duration}} |\n\n## Diagnostics\n\n{{howToInspectWhatThisTaskBuiltLater — status surfaces, logs, error shapes, failure artifacts, or none}}\n\n## Deviations\n\n<!-- Deviations are unplanned changes to the written task plan, not ordinary debugging during implementation. -->\n\n{{deviationsFromPlan_OR_none}}\n\n## Known Issues\n\n{{issuesDiscoveredButNotFixed_OR_none}}\n\n## Files Created/Modified\n\n- `{{filePath}}` — {{description}}\n- `{{filePath}}` — {{description}}\n"}],"isError":false,"timestamp":1775177401552}}
{"type":"message","id":"a27ec788","parentId":"dbb91afd","timestamp":"2026-04-03T00:50:18.276Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01JKrWZkxpLL3E4qeLjzZD7f","name":"write","arguments":{"content":"---\nid: T01\nparent: S01\nmilestone: M014\nprovides:\n  - BodySection and BodySubSection Pydantic models for nested page structure\n  - citation_utils module (extract_citations, validate_citations) for T03 test harness\nkey_files:\n  - backend/pipeline/schemas.py\n  - backend/pipeline/citation_utils.py\n  - backend/pipeline/test_citation_utils.py\nkey_decisions:\n  - Citations use 0-based indices matching moment list position\n  - validate_citations returns a dict (not a model) for flexible downstream use\npatterns_established:\n  - BodySection/BodySubSection nesting for H2/H3 page structure\nobservability_surfaces:\n  - none\nduration: 8 min\nverification_result: passed\ncompleted_at: 2026-04-03\nblocker_discovered: false\n---\n\n# T01: Add BodySection schema models and citation validation utility\n\n**Added BodySection/BodySubSection Pydantic models to schemas.py, changed SynthesizedPage.body_sections to list[BodySection] with v2 format tag, and created citation_utils with extract_citations and validate_citations — 15 tests pass.**\n\n## What Happened\n\nAdded two new Pydantic models to `schemas.py`: `BodySubSection` (heading + content) for H3-level content, and `BodySection` (heading + content + subsections list) for H2-level content. Changed `SynthesizedPage.body_sections` from `dict` to `list[BodySection]` and added `body_sections_format: str = 'v2'` to track the schema version.\n\nCreated `citation_utils.py` with `extract_citations()` (regex-based `[N]` and `[N,M,...]` marker parsing, returns sorted unique indices) and `validate_citations()` (checks all sections + subsections against a moment count, returns coverage stats and invalid/uncited lists).\n\nWrote 15 unit tests covering: single markers, multi-citation `[N,M]` syntax, deduplication, non-numeric brackets, out-of-range indices, empty sections, subsection traversal, and edge cases (zero moments with citations).\n\n## Verification\n\nRan `python -m pytest backend/pipeline/test_citation_utils.py -v` — all 15 tests passed. Verified schema instantiation with a quick import check confirming `body_sections` defaults to `list` and `body_sections_format` defaults to `'v2'`.\n\n## Verification Evidence\n\n| # | Command | Exit Code | Verdict | Duration |\n|---|---------|-----------|---------|----------|\n| 1 | `python -m pytest backend/pipeline/test_citation_utils.py -v` | 0 | ✅ pass | 0.09s |\n| 2 | `python -c \"from pipeline.schemas import BodySection, BodySubSection, SynthesizedPage; ...\"` | 0 | ✅ pass | <1s |\n\n## Diagnostics\n\nNone — pure model/utility code with no runtime surfaces.\n\n## Deviations\n\nNone.\n\n## Known Issues\n\nNone.\n\n## Files Created/Modified\n\n- `backend/pipeline/schemas.py` — Added BodySubSection, BodySection models; changed SynthesizedPage.body_sections to list[BodySection]; added body_sections_format field\n- `backend/pipeline/citation_utils.py` — New module with extract_citations and validate_citations functions\n- `backend/pipeline/test_citation_utils.py` — 15 unit tests for citation utilities\n","path":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/tasks/T01-SUMMARY.md"}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":965,"cacheRead":68179,"cacheWrite":623,"totalTokens":69768,"cost":{"input":0.000005,"output":0.024125,"cacheRead":0.0340895,"cacheWrite":0.00389375,"total":0.06211325000000001}},"stopReason":"toolUse","timestamp":1775177401553}}
{"type":"message","id":"f666e26f","parentId":"a27ec788","timestamp":"2026-04-03T00:50:18.279Z","message":{"role":"toolResult","toolCallId":"toolu_01JKrWZkxpLL3E4qeLjzZD7f","toolName":"write","content":[{"type":"text","text":"Successfully wrote 2974 bytes to /home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/tasks/T01-SUMMARY.md"}],"isError":false,"timestamp":1775177418277}}
{"type":"message","id":"923b18a4","parentId":"f666e26f","timestamp":"2026-04-03T00:50:26.988Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"toolu_01UymSj5Q5DHw735UBsL4GMn","name":"gsd_task_complete","arguments":{"blockerDiscovered":false,"deviations":"None.","keyDecisions":["Citations use 0-based indices matching moment list position","validate_citations returns a dict for flexible downstream use"],"keyFiles":["backend/pipeline/schemas.py","backend/pipeline/citation_utils.py","backend/pipeline/test_citation_utils.py"],"knownIssues":"None.","milestoneId":"M014","narrative":"Added BodySubSection and BodySection Pydantic models to schemas.py for H2/H3 nested page structure. Changed SynthesizedPage.body_sections from dict to list[BodySection] and added body_sections_format='v2'. Created citation_utils.py with extract_citations (regex-based [N] and [N,M] parsing) and validate_citations (coverage stats, invalid/uncited detection). Wrote 15 unit tests covering all edge cases.","oneLiner":"Added BodySection/BodySubSection schema models, changed SynthesizedPage.body_sections to list[BodySection] with v2 format tag, and created citation_utils with 15 passing tests","sliceId":"S01","taskId":"T01","verification":"Ran python -m pytest backend/pipeline/test_citation_utils.py -v — all 15 tests passed (0.09s). Verified schema instantiation confirms body_sections defaults to list and body_sections_format defaults to 'v2'.","verificationEvidence":[{"command":"python -m pytest backend/pipeline/test_citation_utils.py -v","durationMs":90,"exitCode":0,"verdict":"✅ pass"},{"command":"python -c 'from pipeline.schemas import BodySection, BodySubSection, SynthesizedPage; ...'","durationMs":500,"exitCode":0,"verdict":"✅ pass"}]}}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":638,"cacheRead":68802,"cacheWrite":1026,"totalTokens":70467,"cost":{"input":0.000005,"output":0.015950000000000002,"cacheRead":0.034401,"cacheWrite":0.006412500000000001,"total":0.056768500000000006}},"stopReason":"toolUse","timestamp":1775177418278}}
{"type":"message","id":"7d794aa3","parentId":"923b18a4","timestamp":"2026-04-03T00:50:27.036Z","message":{"role":"toolResult","toolCallId":"toolu_01UymSj5Q5DHw735UBsL4GMn","toolName":"gsd_task_complete","content":[{"type":"text","text":"Completed task T01 (S01/M014)"}],"details":{"operation":"complete_task","taskId":"T01","sliceId":"S01","milestoneId":"M014","summaryPath":"/home/aux/projects/content-to-kb-automator/.gsd/milestones/M014/slices/S01/tasks/T01-SUMMARY.md"},"isError":false,"timestamp":1775177427034}}
{"type":"message","id":"7714d5fa","parentId":"7d794aa3","timestamp":"2026-04-03T00:50:29.782Z","message":{"role":"assistant","content":[{"type":"text","text":"Task T01 complete."}],"api":"anthropic-messages","provider":"anthropic","model":"claude-opus-4-6","usage":{"input":1,"output":9,"cacheRead":69828,"cacheWrite":665,"totalTokens":70503,"cost":{"input":0.000005,"output":0.00022500000000000002,"cacheRead":0.034914,"cacheWrite":0.00415625,"total":0.03930025}},"stopReason":"stop","timestamp":1775177427035}}
