How do I install the Anchor Sheet skill?

Run npx skillmds add majiayu000/anchor-sheet in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Anchor Sheet safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Anchor Sheet?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Anchor Sheet free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Anchor Sheet?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Anchor Sheet by majiayu000 — Agent Skill

Name: Anchor Sheet
Rating: 4.5 (4 reviews)
Author: majiayu000

Anchor Sheet

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.

majiayu000 1a1f4cd 2 files · 3.8 KB Updated Sep 9, 2026 567 repo stars

File contents

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 token
- 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 >=4 anchors (if evidence packs are rich).
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 (adjust for queries.md:draft_profile):

=1 evaluation anchor (benchmark/dataset/metric/protocol)
=1 limitation/failure hook (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 .codex/skills/anchor-sheet/scripts/run.py --help
python .codex/skills/anchor-sheet/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 .codex/skills/anchor-sheet/scripts/run.py --workspace workspaces/<ws>
Explicit IO:
- python .codex/skills/anchor-sheet/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

---name: anchor-sheetdescription: 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.--- # 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 token - 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 >=4 anchors (if evidence packs are rich). - [ ] 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 (adjust for `queries.md:draft_profile`): - >=1 evaluation anchor (benchmark/dataset/metric/protocol) - >=1 limitation/failure hook (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 .codex/skills/anchor-sheet/scripts/run.py --help` - `python .codex/skills/anchor-sheet/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 .codex/skills/anchor-sheet/scripts/run.py --workspace workspaces/<ws>` - Explicit IO: - `python .codex/skills/anchor-sheet/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

Frequently asked questions