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 woodfishhhh/EZ_math_model --skill paper_searchgit clone --depth 1 https://github.com/woodfishhhh/EZ_math_modelWrote 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/woodfishhhh/ez_math_model/paper_search)<a href="https://agentmods.dev/skills/woodfishhhh/ez_math_model/paper_search"><img src="https://agentmods.dev/badge/skills/woodfishhhh/ez_math_model/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/woodfishhhh/ez_math_model/paper_search"><img src="https://agentmods.dev/badge/skills/woodfishhhh/ez_math_model/paper_search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.00726 |
| Opus 5 | $0.00040 | $0.00363 |
| Sonnet 5 | $0.00016 | $0.00145 |
| Haiku 4.5 | $0.00008 | $0.00073 |
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
paper-search — 多源学术论文检索
何时使用
- writer 在 pipeline 04 写理论性章节（"为什么用 AHP" 等）
- modeler 在 pipeline 02 选择非教科书算法时找文献
- 任何需要"标题 → DOI → 摘要"的场景
入口脚本
scripts/openalex_scholar.py — OpenAlex 单源（首选，零配置）
scripts/aggregated_search.py — 多源聚合（OpenAlex + arXiv + S2 + CrossRef）
命令行用法
# 单源（推荐先试）
python scripts/openalex_scholar.py "AHP TOPSIS comprehensive evaluation" --top-k 5
# 多源聚合（更全但慢）
python scripts/aggregated_search.py "grey prediction GM(1,1)" --top-k 8
# 输出到文件（用于 writer 后续读取）
python scripts/aggregated_search.py "Sobol sensitivity analysis" --top-k 5 \
--out workdir/{task_id}/refs/sensitivity.json
输出格式（JSON 数组）
[
{
"title": "...",
"authors": ["...", "..."],
"year": 2022,
"doi": "10.1109/...",
"venue": "Journal / Conf",
"abstract": "...（≤ 500 字符）",
"cited_by_count": 132,
"url": "https://doi.org/...",
"source": "openalex | arxiv | s2 | crossref"
}
]
writer 取后插入 footnote 候选；每条文献全文唯一引用一次。
配置
| Env Var | 必需 | 用途 |
|---|---|---|
EZMM_OPENALEX_EMAIL |
否 | 提供邮箱可提升 OpenAlex 配额 |
EZMM_S2_API_KEY |
否 | Semantic Scholar 配额翻倍 |
不填仍可使用所有源的免费配额。
限速与重试
- 单源失败重试 1 次（指数退避 1s, 4s）
- 第 2 次失败 → 标记该源不可用，跳过
- 至少 1 个源成功就返回结果，不强求全部
失败诊断
| 情况 | 处理 |
|---|---|
| 全部源不可达（断网） | stdout 输出 []，stderr 给出诊断 |
| 单源限流 | 跳过；其他源继续 |
| 关键词太长 | 自动截至 200 字符 |
What ships with it
2 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 · 83 lines · 80 tokens per session scan A 6fa6aaff1c81
paper-search is a skill published in the GitHub repository woodfishhhh/EZ_math_model (41 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 726 once invoked, about $0.0004 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 2026-08-30.
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.
mathmodel-skill
An end-to-end workflow for mathematical-modeling competitions, including CUMCM, MCM/ICM, and the Electrical Cup. It guides teams from choosing a problem through modeling, solving, checking, writing, rule compliance, and final review.
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.
interpret-modeling-problems
A method for turning a mathematical modelling contest problem and its attachments into a checked plan for solving and documenting it.
1start-mathmodel
A workflow entry point for the Chinese national mathematical modelling competition. It coordinates problem analysis, modelling, programming, diagrams, paper writing, and verification.
math-modeling-finalizer
A finalization guide for mathematical-modeling projects after the main results are largely fixed.