anchor-sheet

Extract quantitative, evaluation, and limitation anchors from evidence drafts into JSONL.

497|38|Updated Jan 7, 2026
One-click install
npx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill anchor-sheet
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: anchor-sheet
Source: https://github.com/WILLOSCAR/research-units-pipeline-skills/tree/main/.codex/skills/anchor-sheet
Command: npx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill anchor-sheet

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill tackles the issue of vague or "content-poor" prose in research writing by forcing the inclusion of specific, evidence-backed details.

Core Features & Use Cases

  • Quantitative Anchors: Extracts specific numbers, percentages, and data points from evidence.
  • Evaluation Anchors: Identifies benchmarks, datasets, and metrics used in research.
  • Limitation Anchors: Pulls out explicit limitations, failures, or caveats mentioned in the evidence.
  • Use Case: When writing a literature review, this Skill ensures that claims are supported by concrete data or specific experimental results, rather than generic statements.

Quick Start

Use the anchor-sheet skill to extract anchor facts from the evidence drafts in the outline directory.

Frequently Asked Questions about anchor-sheet

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract concrete facts from evidence for research writing?

To extract concrete facts for research writing, process your evidence drafts and bibliography to pull out specific numbers, benchmarks, and limitations per subsection. This ensures your claims are supported by quantitative data rather than generic statements.

What are anchor facts in a literature review?

Anchor facts in a literature review are specific quantitative data points, evaluation metrics, and explicit limitations extracted directly from evidence. They force the inclusion of evidence-backed details to prevent vague or content-poor prose in your writing.

How do I ensure my literature review includes specific numbers and limitations?

To ensure your literature review includes specific numbers and limitations, filter your evidence drafts for quantitative data and experimental caveats. Prioritizing evaluation metrics and explicit limitations keeps your writing grounded in concrete research results.

Can I generate an anchor sheet from evidence drafts and bibliography files?

Yes, you can generate an anchor sheet by processing your evidence drafts and bibliography files together. The system filters the extracted facts for citations present in your provided bibliography, outputting a structured list of per-subsection anchor facts.

Does the anchor fact extraction process require a specific bibliography format?

The anchor fact extraction process requires a bibliography file to cross-reference citations present in your evidence. By filtering extracted facts against this bibliography, it guarantees that only properly cited quantitative data and limitations are included in the final output.

What is the best way to avoid vague prose when writing quantitative data sections?

The best way to avoid vague prose when writing quantitative data sections is to extract per-subsection anchor facts from your evidence beforehand. This forces the inclusion of specific percentages, datasets, and evaluation metrics directly into your research writing.