Skill: willoscar/anchor-sheet (version 1.0.0)

--- name: anchor-sheet description: 'Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries. **Trigger**: anchor sheet, anchor facts, numeric anchors, evidence hooks, 写作锚点, 数字锚点, 证据钩子. **Use when**: `outline/evidence_drafts.jsonl` exists and you want stronger, evidence-anchored writing in `sections/*.md`. **Skip if**: evidence packs are incomplete (fix `evidence-draft` first). **Network**: none. **Guardrail**: NO PROSE; do not invent facts; only select from existing evidence snippets/highlights.' version: 0.1.0 metadata: openclaw: requires: anyBins: - python3 - python --- # Anchor Sheet (evidence → write hooks) [NO PROSE] Purpose: make “what to actually say” explicit: - select quantitative snippets (numbers/percentages) - select evaluation anchors (benchmarks/datasets/metrics) - select limitations/failure hooks This prevents the writer from producing paragraph-shaped but **content-poor** prose. ## Inputs - `outline/evidence_drafts.jsonl` - `citations/ref.bib` ## Outputs - `outline/anchor_sheet.jsonl` ## Output format (`outline/anchor_sheet.jsonl`) JSONL (one object per H3 subsection). Required fields: - `sub_id`, `title` - `anchors` (list; each anchor has `hook_type`, `text`, `citations`, and optional `paper_id/evidence_id/pointer`) ## Workflow 1. Read `outline/evidence_drafts.jsonl`. 2. Prefer anchors that contain: - a number (%, counts, scores) - an explicit benchmark/dataset/metric name - an explicit limitation/failure statement 3. Filter anchors to only citation keys present in `citations/ref.bib`. 4. Write `outline/anchor_sheet.jsonl`. ## Quality checklist - [ ] Every H3 has >=10 cite-backed anchors (A150++ hard target). - [ ] At least 1 anchor contains digits when the evidence pack contains digits. - [ ] No placeholders (`TODO`/`…`/`(placeholder)`). ## Consumption policy (for C5 writers) Anchors are intended to prevent “long but empty” prose. Treat them as **must-use hooks**, not optional ideas. Recommended minimums per H3 (A150++): - >=3 protocol anchors (benchmark/dataset/metric/budget/tool access) - >=3 limitation/failure hooks (concrete, not generic “future work”) - If digits exist in the evidence pack: include >=1 cited numeric anchor (digit + citation in the same paragraph) Note: - Anchor text is trimmed for readability and **does not** include ellipsis markers (to reduce accidental leakage into prose). ## Script ### Quick Start - `python scripts/run.py --help` - `python scripts/run.py --workspace workspaces/<ws>` ### All Options - `--workspace <dir>` - `--unit-id <U###>` - `--inputs <semicolon-separated>` - `--outputs <semicolon-separated>` - `--checkpoint <C#>` ### Examples - Default IO: - `python scripts/run.py --workspace workspaces/<ws>` - Explicit IO: - `python scripts/run.py --workspace workspaces/<ws> --inputs "outline/evidence_drafts.jsonl;citations/ref.bib" --outputs "outline/anchor_sheet.jsonl"` ### Refinement marker (recommended; prevents churn) When you are satisfied with anchor facts (and they are actually subsection-specific), create: - `outline/anchor_sheet.refined.ok` This is an explicit "I reviewed/refined this" signal: - prevents scripts from regenerating and undoing your work - (in strict runs) can be used as a completion signal before writing

path: tooling/__init__.py
content: 


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)