--- id: gh-nature-academic-search name: "nature-academic-search" url: https://skills.yangsir.net/skill/gh-nature-academic-search author: yuan1z0825 domain: science tags: ["academic-search", "literature-review", "research", "citation-management", "data-retrieval"] install_count: 15000 rating: 4.50 (120 reviews) github: https://github.com/yuan1z0825/nature-skills/tree/main/plugins/nature-skills/skills/nature-academic-search --- # nature-academic-search > 此技能是 Claude Code 的学术搜索工具，能够集成 CrossRef、PubMed、arXiv 等多个文献数据库，实现多源并发搜索、按ID获取详情、格式化引用以及文献管理。它帮助研究人员高效地查找、整理和引用学术文献，大幅提升科研效率和文献调研的准确性。 **Stats**: 15,000 installs · 4.5/5 (120 reviews) ## Before / After 对比 ### 文献调研与管理效率 **Before**: 研究人员需要手动在不同的学术数据库中进行搜索，并逐一整理、格式化引用，耗费大量时间和精力，且容易出错。 **After**: 该 Skill 能够自动整合多源搜索结果，快速获取文献详情并按需格式化引用，显著减少了文献调研和管理的时间。 | Metric | Before | After | Change | |---|---|---|---| | 文献调研与管理时间 | 120分钟 | 15分钟 | -87% | ## Readme # Academic Search — Router This skill is split into two layers: - A **static layer** under `static/` that holds versioned, reusable content fragments (the MCP tool inventory and shared modules, and source routing plus operational rules). - A **dynamic layer** (this file plus `manifest.yaml`) that detects which workflow the user needs and loads that workflow, reaching for shared modules and scripts only when a step needs them. Do not try to apply the search logic from memory or from this router. Always load fragments from disk as described below. ## Routing protocol Follow these five steps every time the skill is invoked. ### 1. Load the manifest and the core layer Read [manifest.yaml](manifest.yaml). It declares the `workflow` axis, the allowed values, and the file paths each value maps to. Also read every file listed under `always_load`: - `static/core/tools.md` — the MCP tool inventory (core search, extended search, PubMed utilities) and the shared-module map. - `static/core/routing-and-ops.md` — the T1→T2→T3 source routing quick guide, environment setup, error handling, and limitations. ### 2. Detect the workflow Map the user's need to one or more `workflow` values: - `multi-source-search` — find literature across sources. - `citation-verification` — verify citations extracted from a document. - `mesh-strategy` — build a MeSH/PubMed search strategy. - `citation-file-mgmt` — convert/manage `.nbib`/`.ris`/`.bib` files. - `reference-mgmt` — BibTeX, related-article discovery, ID conversion. A combined request (for example search then export) may need more than one. State the detected workflow(s) in one short line before proceeding. ### 3. Load the matching workflow fragment(s) Read the file mapped for each detected workflow (under `references/workflows/`). Do **not** read every workflow. Each workflow file links to the shared modules it needs. ### 4. Run the workflow using the loaded material Apply the loaded material in this order: 1. Core tools and routing (`core/tools.md`, `core/routing-and-ops.md`) — which MCP tool for which need, and the T1→T2→T3 fallback chain that is the standard execution order across all workflows. 2. The workflow fragment — its specific steps. 3. Shared modules and scripts on demand (dedup, citation parser, search strategy, RIS/BibTeX format, format converter). Report specific tool failures and continue with remaining tools; broaden terms when there are no results; fall back to manual generation from MCP-fetched metadata if a script fails twice. ### 5. Reach for references only when needed The files under `references/` (and `scripts/`) are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest — for example `references/source-tiers.md` for the full reliability classification, `references/dedup-engine.md` / `references/citation-parser.md` / `references/search-strategy.md` / `references/ris-bibtex-format.md` for the shared modules, and `scripts/academic_search.py` (no-MCP fallback discovery search) / `scripts/format-converter.py` / `scripts/preflight.py` for the tooling. ## Why this split - The static layer is versioned and reviewable; the workflow files and shared modules were already factored this way. - The dynamic layer keeps each invocation cheap: only the workflow the user needs enters context, instead of all five plus every module. - The router itself is short on purpose. Update fragments and references, not this file, when adding scope. - This structure mirrors the other nature-* skills (`nature-writing`, `nature-polishing`, `nature-reader`, `nature-paper2ppt`, `nature-figure`, `nature-citation`, `nature-response`, `nature-data`). --- # Academic Search Claude Code 的学术搜索技能包，集成 CrossRef、PubMed、arXiv、Scopus、ScienceDirect 文献数据源。 ## 功能 - **多源并发搜索**: 默认查询 CrossRef / PubMed / arXiv，并合并返回结果 - **按 ID 获取详情**: 支持 DOI、PMID、arXiv ID 自动识别 - **格式化引用**: APA / Nature / IEEE / Vancouver 等风格 - **MeSH 词表查询**: 构建精准 PubMed 检索式 - **文献管理脚本**: .nbib / .ris / .bib / .enw 格式互转 - **Scopus / ScienceDirect**: 支持论文、作者、机构、期刊、引用概览、PlumX 指标和 ScienceDirect 元数据检索 ## MCP 运行 插件默认通过 uv 启动隔离运行环境： ```bash uv run --no-project --directory --with "mcp>=1.0.0,<2.0.0" --with "requests>=2.28.0,<3.0.0" --with "toml>=0.10.2,<2.0.0" --with "lxml>=4.9.0,<6.0.0" --with "pybliometrics>=4.4.1,<5.0.0" python academic_search_server.py ``` PubMed 需要在环境变量 `PUBMED_EMAIL` 或 `mcp-server/config.toml` 中配置邮箱。Scopus / ScienceDirect 是可选 provider，复用本机 `pybliometrics` 配置，默认读取 `~/.config/pybliometrics.cfg`；不要把 Elsevier API key 写入插件文件。`search_papers` 只有在 `sources` 显式包含 `scopus` / `sciencedirect` 时才会调用 Elsevier-backed provider，以避免无意消耗 Elsevier API 配额。 ## MCP Tools | Tool | 说明 | |------|------| | `search_papers` | 默认三源并发搜索；可显式添加 Scopus / ScienceDirect | | `get_paper_by_id` | 按 DOI/PMID/arXiv ID 获取详情 | | `get_citation` | 格式化引用生成 | | `lookup_mesh` | MeSH 词表查询 | | `search_scopus` | Scopus 高级检索 | | `get_scopus_abstract` | Scopus 摘要/详情元数据 | | `get_scopus_citation_overview` | Scopus 引用概览 | | `search_scopus_authors` / `get_scopus_author` | 作者检索与详情 | | `search_scopus_affiliations` / `get_scopus_affiliation` | 机构检索与详情 | | `search_scopus_serial_titles` / `get_scopus_serial_title` | 期刊/连续出版物检索与详情 | | `get_scopus_plumx_metrics` | PlumX 指标 | | `search_sciencedirect` | ScienceDirect 检索 | | `get_sciencedirect_article_metadata` | ScienceDirect 文章元数据 | --- *Source: https://skills.yangsir.net/skill/gh-nature-academic-search* *Markdown mirror: https://skills.yangsir.net/api/skill/gh-nature-academic-search/markdown*