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Anchor Sheet Skill for Codex

by WILLOSCAR

| 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.

4k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
496
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository 
npx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill anchor-sheet

What comes with it

14 650 bytes besides the instruction
scripts/run.py

The instruction itself

12 sections, as written by the author

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

  • Read outline/evidence_drafts.jsonl.
  • Prefer anchors that contain:
  • a number (%, counts, scores)
  • an explicit benchmark/dataset/metric name
  • an explicit limitation/failure statement
  • Filter anchors to only citation keys present in citations/ref.bib.
  • 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

  • uv run python .codex/skills/anchor-sheet/scripts/run.py --help
  • uv run python .codex/skills/anchor-sheet/scripts/run.py --workspace <workspace>

All Options

  • --workspace <dir>
  • --unit-id <U###>
  • --inputs <semicolon-separated>
  • --outputs <semicolon-separated>
  • --checkpoint <C#>

Examples

  • Default IO:
  • uv run python .codex/skills/anchor-sheet/scripts/run.py --workspace <workspace>
  • Explicit IO:
  • uv run python .codex/skills/anchor-sheet/scripts/run.py --workspace <workspace> --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

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How to use it

Copy the folder

Take willoscar/anchor-sheet from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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