Install
$ agentstack add skill-woodfishhhh-ez-math-model-paper-search ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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 |
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: woodfishhhh
- Source: woodfishhhh/EZmath_model
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.