Claim Evidence Matrix Skill for Codex
| Build a section-by-section claim–evidence matrix (`outline/claim_evidence_matrix.md`) from the outline and paper notes.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/WILLOSCAR/research-units-pipeline-skills --skill claim-evidence-matrixWhat comes with it
10 610 bytes besides the instructionThe instruction itself
13 sections, as written by the authorClaim–Evidence Matrix
Make the survey’s claims explicit and auditable before writing prose.
This should stay bullets-only (NO PROSE). The goal is to make later writing *easy* and to prevent “template prose” from sneaking in.
Inputs
outline/outline.ymlpapers/paper_notes.jsonl- Optional:
outline/mapping.tsv
Output
outline/claim_evidence_matrix.md
Workflow (heuristic)
Uses: outline/outline.yml, outline/mapping.tsv.
- For each subsection, write 1–3 claims that are:
- specific (mechanism / assumption / empirical finding)
- falsifiable (“X reduces tool errors under Y evaluation”, not “X is important”)
- For each claim, list ≥2 evidence sources:
- prefer different styles of evidence (method paper + eval/benchmark paper, or two competing approaches)
- Keep it tight: claim → evidence → (optional) caveat/limitations.
- If evidence is weak or only abstract-level, say so explicitly (don’t overclaim).
- If
bibkeyexists inpapers/paper_notes.jsonl, include[@BibKey]next to evidence items to make later prose/LaTeX conversion smoother.
Quality checklist
- [ ] Every subsection has ≥1 claim.
- [ ] Each claim lists ≥2 evidence sources (or an explicit exception).
- [ ] Claims are not copy-pasted templates (avoid “围绕…总结…” boilerplate).
Helper script (optional)
Quick Start
uv run python .codex/skills/claim-evidence-matrix/scripts/run.py --helpuv run python .codex/skills/claim-evidence-matrix/scripts/run.py --workspace <workspace>
All Options
- See
--help(this helper is intentionally minimal)
Examples
- Generate a first-pass matrix, then refine manually:
- Run the helper once, then refine
outline/claim_evidence_matrix.mdby tightening claims and adding caveats when evidence is abstract-level.
Notes
- The helper generates a baseline matrix (claims + evidence) and never overwrites non-placeholder work; in
pipeline.py --strictit will be blocked only if placeholder markers remain.
Troubleshooting
Issue: claims are generic or read like outline boilerplate
Fix:
- Tighten each claim to a falsifiable statement and add an explicit caveat if evidence is abstract-only.
Issue: you cannot add [@BibKey] because keys are missing
Fix:
- Run
citation-verifierto generatecitations/ref.bib, then use the produced keys in the matrix.
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How to use it
Take willoscar/claim-evidence-matrix from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.