Contest Literature

SkillSearch

Use when 高教社杯/CUMCM mathematical modeling papers need lightweight literature search, citation verification, method/background references, standards or policy sources, Chinese-English source routing, DOI/BibTeX checks, or claim-to-citation mapping without fabricated sources.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Contest Literature skill

What this skill tells your AI

The instructions your AI receives, as published by capwitf/my-mathmodeling-skills in math-literature/SKILL.md and read by ahel’s review.

Purpose

Plan lightweight source work, verify citations, map claims to references, and prevent fabricated or over-broad literature support in contest papers.

This skill is for citation and source verification in 高教社杯/CUMCM work. If the user needs literature to generate solution ideas or compare candidate model routes, return the source gap and route-search need to math-hub; do not reverse-cite a finished model.

国一候选门槛:引用工作应服务题目贴合、建模洞察、证据可信、可复现、边界清楚;这是提交质量门槛,不承诺获奖。

For a citation-backed paper_ready claim, final gate, or cross-module handoff, apply the current math-hub evidence rules. Local source triage can stay lightweight.

Source Routing

  • Official rules, policies, standards, datasets, and parameters require primary or authoritative sources.
  • Method background can use credible papers, textbooks, or official documentation.
  • Ordinary contest background can use compact verified notes when it does not carry a parameter, baseline, policy, or method-validity claim.
  • If current facts, policies, standards, prices, or public figures may have changed, verify online from primary sources.

Workflow

  1. State the claim needing support.
  2. Decide source tier and search language.
  3. Search or inspect provided sources.
  4. Verify metadata, DOI/BibTeX, publisher, date, and source status when relevant.
  5. Record in literature_search_log.csv and reference_registry.csv when the source supports paper claims.
  6. Create claim_citation_map.csv rows for parameter, standard, policy, baseline, public-data, or method-validity claims.
  7. Return unresolved source gaps to math-hub.

A verified source supports only the point it actually says. Do not widen the paper claim to sound stronger.

Keyword match alone is never bibliography-ready. A reference needs paper location, exact supported point, support boundary, and verified metadata before it can support final prose.

When a request is really "help me find ideas before modeling" rather than "verify this claim/source", return the active subquestion, evidence need, and current source gaps to math-hub for route selection.

Output Contract

Return:

  • search plan or verified sources;
  • source tier and support boundary;
  • literature_search_log.csv, reference_registry.csv, or claim_citation_map.csv rows when needed;
  • citation wording or BibTeX/DOI fixes;
  • unresolved gaps and route.

Return to hub: math-hub.

Red Lines

  • 不要编造论文、DOI、作者、期刊、标准或政策原文。
  • Do not cite search snippets as verified sources.
  • Do not use an unverified citation for a paper-ready claim.
  • Do not let a source support broader wording than it justifies.

Signals

GitHub stars
51
Forks
1
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
math-literature
Source
github.com/capwitf/my-mathmodeling-skills