Research evidence
Skill sidiangongyuan/codex-skills-library/skills/research-evidence
Use when research writing, reviews, rebuttals, or related-work planning needs academic evidence. Searches literature, screens candidate papers, audits novelty and missing work, verifies DOI/BibTeX/reference metadata and citation authenticity, and checks whether sources support the stated claims.From its SKILL.md
npx -y skills add sidiangongyuan/codex-skills-library --skill research-evidenceAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
5.0 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Research Evidence
Overview
Use this skill as the shared evidence layer for paper writing, related work, review, and rebuttal work. It does not replace domain judgment: it finds and checks evidence, then reports support level, gaps, and risks.
Hard Boundaries
- Use public metadata, open-access PDFs, and user-provided local PDFs only.
- Do not use Sci-Hub or any route that bypasses access control.
- Do not write Markdown, JSON, CSV, or report files unless the user explicitly asks for saved artifacts.
- Run RefChecker in non-LLM mode by default. Enable LLM-assisted extraction or hallucination checks only when the user explicitly requests it and accepts the privacy/cost tradeoff.
- Treat tool output as evidence to inspect, not final truth. Mark weak coverage, metadata mismatches, and unsupported claims clearly.
Venue Defaults
Prefer these venues when the user does not specify otherwise:
- Computer Vision: CVPR, ICCV, ECCV.
- ML/AI: ICLR, NeurIPS/NIPS, ICML.
- Autonomous driving, robotics, and collaborative perception secondary venues: CoRL, ICRA, IROS, AAAI, IJCAI, T-ITS, RA-L.
Do not let secondary venues outrank the primary top-conference set unless the user's task or subfield demands it.
Workflows
Literature Search
- Translate the research question into compact queries with venue/year terms when useful.
- Use the dedicated tool environment from
references/tooling.md; start with arXiv metadata search for CV/ML topics. - Return a compact candidate list with title, source, year/date, identifier, URL, and why each candidate is relevant.
- Label coverage risk when search sources are unavailable, too broad, too recent, or missing known top-venue work.
Recent Literature / Novelty Risk Audit
Use this workflow when the user asks about novelty, recent work, missing related work, reviewer risk, rebuttal readiness, score prediction, first/SOTA/new benchmark claims, or whether a close paper conflicts with the current claim.
- Decompose the claim into axes before searching: domain/input, method family, task/output, evaluation protocol, dataset/benchmark, and reliability or failure mode.
- Expand the search across direct terms, synonyms, neighboring tasks, older terminology, and broad recent-work queries. Do not stop at the user's exact phrasing.
- For high-stakes checks, cross-check at least two evidence routes: direct
arXiv API or official venue metadata; local
reference/, PDF, BibTeX, or LaTeX sources; and the localpaper-searchwrapper as a smoke or secondary check. - Classify candidates after inspecting metadata and abstracts: direct competitor, claim limiter, table candidate, prose citation, background, or irrelevant.
- Report the search matrix, source-coverage limits, and claim-impact verdict. Never answer "not found" without stating which query families and sources were checked.
Read references/recent-literature-audit.md for the full checklist. Use
scripts/arxiv_query_matrix.py when a repeatable arXiv query matrix would make
the search less ad hoc.
Citation Check
- Prefer local PDF, LaTeX, BibTeX, or reference-list files supplied by the user.
- Run RefChecker without LLM flags unless explicitly requested.
- Summarize reference authenticity, metadata mismatches, missing fields, suspicious entries, and false-positive risk.
- Do not automatically rewrite references. Recommend exact follow-up checks or edits.
Claim Evidence Check
- Extract the claim and required support type: paper text, citation, experiment result, table/figure, code/log artifact, or user-confirmed fact.
- Search or verify only the minimum evidence needed for the claim.
- Report one of:
verified,likely,unsupported, orneeds user input. - Do not strengthen claims based on weak evidence. Recommend weakening, adding a citation, deleting the claim, or asking the user for missing evidence.
Output Shape
Default response shape:
query: search or verification intent.sources: tools/sources used and key records found.verdict:verified,likely,unsupported, orneeds user input.risks: source coverage, metadata mismatch, citation error, weak venue fit, or stale evidence.next action: write, weaken, cite, delete, continue search, or ask the user.
For novelty-risk audits, include:
search matrix: query families and evidence routes checked.candidate classification: direct competitor, claim limiter, table candidate, prose citation, background, or irrelevant.claim impact: keep, weaken, add citation/table row, revise positioning, or avoid first/SOTA language.residual risk: what the search still may have missed.
Tooling
Read references/tooling.md before running installed commands or changing tool behavior.
What ships with it: 5 files
15.8 KB alongside SKILL.md, 1 of them executable
agents/
- openai.yaml277 B
references/
- recent-literature-audit.md3.3 KB
- tooling.md2.9 KB
scripts/
- arxiv_query_matrix.pyruns8.3 KB
- LICENSE1.0 KB