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SKILL verified MIT Self-run

Paper Search

skill-woodfishhhh-ez-math-model-paper-search · by woodfishhhh

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Install

$ agentstack add skill-woodfishhhh-ez-math-model-paper-search

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No 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.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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How agent discovery & health will work →
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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.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.