mcpField
A
anchor-sheet

anchor-sheet

github.com/willoscarProductivity51741 installsUpdated 3w ago
Repository

About anchor-sheet

Anchor Sheet is a writing skill that turns evidence drafts and bibliography entries into cited hooks for subsection writers. It prioritizes numbers, named benchmarks or metrics, and limitations, rather than drafting prose.

Key features

  1. 01Selects quantitative evidence hooks
  2. 02Captures benchmarks, datasets, and metrics
  3. 03Includes limitation and failure hooks
  4. 04Filters citations against the bibliography
  5. 05Writes JSONL anchors per subsection

Use cases

  1. 01Prepare evidence anchors before drafting
  2. 02Find cited numbers for subsection prose
  3. 03Gather benchmark and metric references

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/willoscar/research-units-pipeline-skills --skill anchor-sheet

After installing, type/anchor-sheetin Claude Code to confirm it loaded.

Bundled filesscripts/run.py

Details

From the project README

Anchor Sheet (evidence → write hooks) [NO PROSE]

Triggers & routing

  • 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.

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
  • 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

Comments

Markdown supported