Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add MrSGSA/math-modeling-skill-dify --skill paper-searchgit clone --depth 1 https://github.com/MrSGSA/math-modeling-skill-difyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mrsgsa/math-modeling-skill-dify/paper-search)<a href="https://agentmods.dev/skills/mrsgsa/math-modeling-skill-dify/paper-search"><img src="https://agentmods.dev/badge/skills/mrsgsa/math-modeling-skill-dify/paper-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mrsgsa/math-modeling-skill-dify/paper-search"><img src="https://agentmods.dev/badge/skills/mrsgsa/math-modeling-skill-dify/paper-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00599 |
| Opus 5 | $0.00016 | $0.00300 |
| Sonnet 5 | $0.00006 | $0.00120 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
paper-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
双引擎论文搜索
数据源
- OpenAlex：结构化学术元数据。
- AnySearch Academic：学术垂直搜索，支持当前 MCP Markdown 响应解析。
默认并行调用两个引擎。DOI 相同的记录直接交叉验证；无 DOI 时仅在标题高度相似且年份相容时合并。同一引擎中标题规范化后相同的预印本与正式出版记录也会折叠，并优先保留引用信息和元数据更完整的记录。交叉匹配结果、OpenAlex 独有结果和 AnySearch 独有结果分开输出。
融合时按查询词覆盖率过滤和重排，相关性优先于引用量，避免高被引但主题无关的论文挤占结果。包含多个专业术语时，候选文献至少命中两个有效查询词；这一阈值兼顾缺少摘要的元数据，不能代替人工核验。专业主题应组合使用研究对象、机理与模型名，例如 battery degradation Arrhenius state-space；结果过少时逐步放宽查询，不直接接受无关结果。
使用
python scripts/hybrid_scholar.py --query "robust optimization vehicle routing" --limit 10 --json
如 AnySearch 需要鉴权：
$env:ANYSEARCH_API_KEY = "<密钥>"
python scripts/hybrid_scholar.py --query "analytic hierarchy process" --limit 8
诊断单个引擎时可用 --openalex-only 或 --anysearch-only。正式文献检索默认运行两个引擎；若某一引擎因鉴权、网络或服务故障不可用，在记录失败原因后可降级使用另一真实数据源，并把结果标为未完成双引擎交叉验证，禁止伪造缺失引擎的命中。机器可读输出中的 stats.source_status、stats.source_errors、stats.degraded 和 stats.dual_engine_cross_validation_complete 必须随结果保留。
核验规则
- 搜索结果只用于发现候选文献。
- 引用前打开 DOI 或出版机构页面核对作者、题名、年份、期刊/会议、卷期页。
- 不把引用量当作正确性的证明。
- 不根据标题或摘要编造不存在的结论。
- 输出中保留
sources和cross_validated状态。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 39 lines · 32 tokens per session scan A add2ab8e2538
paper-search is a skill published in the GitHub repository MrSGSA/math-modeling-skill-dify (4 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 599 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
math-modeling-solver
A Chinese-language guide for solving mathematical modeling competition problems. It covers China’s CUMCM and America’s MCM/ICM, where teams use mathematics and code to answer real-world problem statements.
math-modeling-paper
A Chinese-language guide for writing papers for mathematical modelling competitions, where teams use mathematics and data to study a real-world problem.
ez-math-model
Use when solving CUMCM, MCM, ICM, or other mathematical modeling tasks that need contest problem intake, model selection, Python solving, figures, paper writing, quality audit, and packaged deliverables.
brainstorming
Use when EZmathmodel model selection is unclear after the modeling decision tree, the problem spans multiple domains, or modeler needs several candidate approaches before writing modelingplan.md.
scientific-slides
Use when the user explicitly asks EZmathmodel to create defense slides, academic presentation slides, Beamer slides, or PPT after the modeling paper has been packaged.
interpret-modeling-problems
A method for turning a mathematical modelling contest problem and its attachments into a checked plan for solving and documenting it.