smithery/willoscar

outline-refiner

Planner-pass coverage + redundancy report for an outline+mapping, producing `outline/coverage_report.md` and `outline/outline_state.jsonl`.

Installation

$ npx skills add smithery/willoscar --skill outline-refiner

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More details

Agent compatibility

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Package contents

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  • skill md SKILL.md 3,317 B
  • docs SUMMARY.md 666 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Outline Refiner (Planner pass, NO PROSE)

Triggers & routing

  • Trigger: planner, dynamic outline, outline refinement, coverage report, 大纲迭代, 覆盖率报告.
  • Use when: you have outline/outline.yml + outline/mapping.tsv and want a verifiable, NO-PROSE planner pass before writing.

Goal: make the outline auditable by adding an explicit planner stage that answers:

  • Do we have enough mapped evidence per H3?
  • Are the same few papers reused everywhere?
  • Are subsection axes still generic/scaffold-y?
  • Is the outline likely to produce a paper-like structure (final ToC budget: ~6–8 H2; fewer, thicker H3s)?

This is a deterministic “planner” unit: it must not write survey prose.

Inputs

Required:

  • outline/outline.yml
  • outline/mapping.tsv

Optional (best-effort diagnosis; may be missing early in the pipeline):

  • outline/OUTLINEBUDGETREPORT.md (if present: explains recent merges; helps interpret mapping/coverage changes)
  • papers/paper_notes.jsonl (for evidence levels)
  • outline/subsection_briefs.jsonl (for axis specificity)
  • GOAL.md (for scope drift hints)

Outputs

  • outline/coverage_report.md (bullets + small tables; NO PROSE)
  • outline/outline_state.jsonl (append-only JSONL; one record per run)

Workflow (planner pass, NO PROSE)

  1. Parse outline/outline.yml to enumerate H2 sections + H3 subsections (section sizing / budget).

- If outline/OUTLINEBUDGETREPORT.md exists, use it as the merge/change log so the coverage report can explain why structure changed.

  1. Read outline/mapping.tsv and compute per-H3 coverage and reuse hotspots.
  2. If papers/paper_notes.jsonl exists, summarize evidence levels (fulltext/abstract/title) for mapped papers.
  3. If outline/subsection_briefs.jsonl exists, compute axis specificity (generic vs specific axes) per H3.
  4. Optionally use GOAL.md to flag obvious scope drift (keywords not reflected in outline).
  5. Write outline/coveragereport.md and append a run record to outline/outlinestate.jsonl.

Freeze policy

  • If outline/coveragereport.refined.ok exists, the script will not overwrite outline/coveragereport.md.

Script

Quick Start

  • uv run python .codex/skills/outline-refiner/scripts/run.py --help
  • uv run python .codex/skills/outline-refiner/scripts/run.py --workspace <workspace>

All Options

  • --workspace <dir>: workspace root
  • --unit-id <U###>: unit id (optional; for logs)
  • --inputs <semicolon-separated>: override inputs (rare; prefer defaults)
  • --outputs <semicolon-separated>: override outputs (rare; prefer defaults)
  • --checkpoint <C#>: checkpoint id (optional; for logs)

Examples

  • Planner-pass diagnostics after section-mapper:

- uv run python .codex/skills/outline-refiner/scripts/run.py --workspace <workspace>

Troubleshooting

Issue: report is missing evidence-level or axis-specificity columns

Cause:

  • Optional inputs are missing (no papers/papernotes.jsonl and/or no outline/subsectionbriefs.jsonl).

Fix:

  • Run paper-notes and/or subsection-briefs, then rerun outline-refiner.