nature-academic-search
Use when users ask to 找文献、做文献检索、查论文、查临床试验、核验引用、去重文献、设计 PubMed/MeSH 检索式、追踪上下游引文、解析 DOI/PMID/PMCID/arXiv/OpenAlex/Semantic Scholar/NCT ID, 或导出 RIS、BibTeX、NBIB、ENW;also use for multi-source academic search, citation verification, citation graphs, trial registration search, research workflows, or DeepSeek Harness academic-search MCP setup.
含まれるファイル(154)
- SKILL.md8.8 KB
- .agents/plugins/marketplace.json679 B
- .claude-plugin/marketplace.json692 B
- .github/dependabot.yml271 B
- .github/workflows/ci.yml1.3 KB
- .github/workflows/network-smoke.yml735 B
- .github/workflows/publish.yml2.1 KB
- .gitignore94 B
- config/mcp-snippet.json539 B
- config/settings-snippet.json59 B
- config/triggers-academic-search.toml558 B
- docs/assets/academic-search-citation-verification.png126.4 KB
- docs/assets/academic-search-pubmed-mesh.png119.5 KB
- docs/assets/academic-search-topic-scoping.png165.1 KB
- docs/community-growth.md5.0 KB
- docs/community-submissions.md5.2 KB
- docs/examples/citation-verification.md1.6 KB
- docs/examples/pubmed-mesh.md1.9 KB
- docs/examples/topic-scoping.md2.1 KB
- docs/installation.md5.7 KB
- docs/maintenance.md6.3 KB
- docs/plans/2026-07-15-academic-paper-search-brand-design.md3.8 KB
- docs/plans/2026-07-15-academic-paper-search-brand-implementation.md10.1 KB
- docs/plans/2026-07-15-pypi-plugin-redesign-design.md6.2 KB
- docs/plans/2026-07-15-pypi-plugin-redesign-implementation.md9.4 KB
- docs/plans/2026-07-15-readme-skill-star-conversion-design.md5.9 KB
- docs/plans/2026-07-15-readme-skill-star-conversion-implementation.md8.7 KB
- docs/plans/2026-07-20-academic-search-source-expansion-design.md18.6 KB
- docs/plans/2026-07-20-academic-search-source-expansion-implementation.md26.6 KB
- docs/plans/2026-07-31-community-discovery-growth-design.md4.1 KB
- docs/plans/2026-07-31-community-discovery-growth-implementation.md8.1 KB
- docs/plans/2026-08-16-readme-relay-promotion-design.md1.1 KB
- docs/plans/2026-08-16-readme-relay-promotion-implementation.md2.8 KB
- docs/plans/2026-08-24-evidence-grade-search-implementation.md9.9 KB
- docs/plans/2026-08-24-research-workflow-automation-design.md5.6 KB
- docs/plans/2026-08-24-research-workflow-implementation.md1.6 KB
- docs/plans/2026-08-24-smart-discovery-implementation.md1.8 KB
- docs/plans/2026-08-26-citation-graph-design.md2.3 KB
- docs/plans/2026-08-26-citation-graph-implementation.md2.8 KB
- docs/plans/2026-08-26-relay-visibility-design.md1.5 KB
- docs/plans/2026-08-26-relay-visibility-implementation.md2.2 KB
- docs/plans/2026-08-27-readme-skill-redesign-design.md1.9 KB
- docs/plans/2026-08-27-readme-skill-redesign-implementation.md3.3 KB
- docs/plans/2026-08-29-clarify-academic-search-skill.md1.6 KB
- docs/plans/2026-08-29-deepseek-harness-bundle-design.md2.5 KB
- docs/plans/2026-08-29-deepseek-harness-bundle-implementation.md4.8 KB
- docs/plans/2026-08-29-premium-readme-implementation.md1.4 KB
- docs/plans/2026-09-09-workflow-release-skill-fixes.md3.2 KB
- install.sh1.9 KB
- LICENSE1.0 KB
- mcp-server/academic_search_server.py548 B
- mcp-server/config.toml395 B
- mcp-server/README.md1.2 KB
- mcp-server/requirements.txt53 B
- mcp-server/sources/__init__.py394 B
- mcp-server/sources/arxiv.py234 B
- mcp-server/sources/crossref.py240 B
- mcp-server/sources/pubmed.py236 B
- mcp-server/tests/__init__.py40 B
- mcp-server/tests/test_sources.py26.8 KB
- mcp-server/utils/__init__.py359 B
- mcp-server/utils/config.py1.4 KB
- mcp-server/utils/errors.py359 B
- mcp-server/utils/logging.py1.1 KB
- plugins/nature-academic-search/.claude-plugin/plugin.json760 B
- plugins/nature-academic-search/.codex-plugin/plugin.json2.2 KB
- plugins/nature-academic-search/.mcp.json208 B
- plugins/nature-academic-search/skills/nature-academic-search/agents/openai.yaml497 B
- plugins/nature-academic-search/skills/nature-academic-search/references/citation-files.md1.9 KB
- plugins/nature-academic-search/skills/nature-academic-search/references/search-workflows.md9.0 KB
- plugins/nature-academic-search/skills/nature-academic-search/references/source-tiers.md3.2 KB
- plugins/nature-academic-search/skills/nature-academic-search/SKILL.md8.8 KB
- pyproject.toml2.4 KB
- README.md27.8 KB
- references/citation-files.md1.9 KB
- references/citation-parser.md2.7 KB
- references/dedup-engine.md1.4 KB
- references/pubmed-28344011.bib3.3 KB
- references/pubmed-28344011.nbib11.9 KB
- references/pubmed-28344011.ris3.4 KB
- references/ris-bibtex-format.md4.3 KB
- references/search-strategy.md1.5 KB
- references/search-workflows.md9.0 KB
- references/source-tiers.md3.2 KB
- references/workflows/wf1-multi-source-search.md1.6 KB
- references/workflows/wf2-citation-verification.md943 B
- references/workflows/wf3-mesh-strategy.md627 B
- references/workflows/wf4-citation-file-mgmt.md856 B
- references/workflows/wf5-reference-mgmt.md1.2 KB
- scripts/check_wheel.py7.9 KB
- scripts/converters.py327 B
- scripts/format-converter.py18.6 KB
- scripts/preflight.py586 B
- scripts/sync_skill.py1.8 KB
- src/nature_academic_search/__init__.py91 B
- src/nature_academic_search/__main__.py175 B
- src/nature_academic_search/citation.py18.3 KB
- src/nature_academic_search/cli.py6.3 KB
- src/nature_academic_search/config.py2.9 KB
- src/nature_academic_search/conversion/__init__.py279 B
- src/nature_academic_search/conversion/converters.py17.9 KB
- src/nature_academic_search/discovery.py298 B
- src/nature_academic_search/errors.py710 B
- src/nature_academic_search/filters.py9.1 KB
- src/nature_academic_search/graph.py9.9 KB
- src/nature_academic_search/http.py2.9 KB
- src/nature_academic_search/installer.py4.0 KB
- src/nature_academic_search/logging.py1.2 KB
- src/nature_academic_search/preflight.py9.6 KB
- src/nature_academic_search/provenance.py3.2 KB
- src/nature_academic_search/ranking.py3.9 KB
- src/nature_academic_search/relay.py6.5 KB
- src/nature_academic_search/search.py17.8 KB
- src/nature_academic_search/server.py17.6 KB
- src/nature_academic_search/sources/__init__.py506 B
- src/nature_academic_search/sources/arxiv.py11.1 KB
- src/nature_academic_search/sources/clinicaltrials.py5.8 KB
- src/nature_academic_search/sources/crossref.py10.2 KB
- src/nature_academic_search/sources/europe_pmc.py10.5 KB
- src/nature_academic_search/sources/openalex.py11.5 KB
- src/nature_academic_search/sources/pubmed.py14.6 KB
- src/nature_academic_search/sources/registry.py2.3 KB
- src/nature_academic_search/sources/semantic_scholar.py7.8 KB
- src/nature_academic_search/verification.py5.0 KB
- src/nature_academic_search/workflow.py25.0 KB
- tests/fixtures/sources/clinicaltrials-search.json1.7 KB
- tests/fixtures/sources/europe-pmc-search.json605 B
- tests/fixtures/sources/openalex-search.json1.1 KB
- tests/fixtures/sources/semantic-scholar-search.json731 B
- tests/test_cli.py9.2 KB
- tests/test_conversion.py946 B
- tests/test_discovery_source_queries.py2.7 KB
- tests/test_discovery.py5.3 KB
- tests/test_graph_sources.py5.4 KB
- tests/test_graph.py4.9 KB
- tests/test_http.py6.5 KB
- tests/test_installer.py4.1 KB
- tests/test_package_metadata.py1.3 KB
- tests/test_plugin_artifacts.py8.6 KB
- tests/test_provenance.py1.0 KB
- tests/test_relay.py1.7 KB
- tests/test_release_metadata.py13.3 KB
- tests/test_search.py20.4 KB
- tests/test_server.py14.0 KB
- tests/test_source_clinicaltrials.py4.5 KB
- tests/test_source_europe_pmc.py5.1 KB
- tests/test_source_openalex.py5.0 KB
- tests/test_source_pubmed.py2.2 KB
- tests/test_source_registry.py1.9 KB
- tests/test_source_semantic_scholar.py5.5 KB
- tests/test_sources.py1.5 KB
- tests/test_verification.py2.7 KB
- tests/test_wheel_smoke.py2.6 KB
- tests/test_workflow.py14.9 KB
SKILL.md(原文)
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Academic Paper Search
什么时候触发
用户提到找文献、文献检索、引用核验、引文图谱、MeSH、PubMed、预印本、临床试验、RIS/BibTeX
或 DOI/PMID/PMCID/arXiv/OpenAlex/Semantic Scholar/NCT 时触发本 skill。目标是论文时使用
entity_type="publication";目标是注册试验时使用 entity_type="trial",两者不能按题名合并。
任务路由
以下工具路由以实际工具输出为准;适配器存在不代表本次已经查询。
| 用户目标 | 入口 | 执行要求 |
|---|---|---|
| 找文献、综述前期检索 | search_papers | 按源检索、去重,报告 sources_queried / sources_succeeded / sources_skipped / errors |
| 核验已有引用 | get_paper_by_id + expected | 输出字段级 verified、mismatch、not_found 或 manual_needed |
| 追踪上下游引文 | get_paper_by_id(include_relations=true) | 默认 depth=1;需要二跳时显式 depth=2,保留图谱边和来源缺口 |
| 构建 PubMed 检索式 | lookup_mesh | 先核对 MeSH 词和 ID,再组合自由词;不要凭空猜主题词 |
| 生成单条引用 | get_citation | 只格式化已解析论文;NCT 注册不生成论文引用 |
| 批量导出或自动化 | CLI citation / workflow | 保留 run.json、核验状态和人工待处理清单 |
客户端可能给工具名添加 MCP 前缀;工具总数仍为四个,不新增专用图谱工具。
DeepSeek Harness 使用独立的
dsh-academic-paper-search
Bundle,通过官方 @deepseek-ai/dsh-mcp-client 映射为
mcp__academic_search__*;这是同一 MCP 运行时的客户端适配,不要在 DSH
中重写或假设额外的论文工具。
CLI 从 0.3.1 起可用 nature-academic-search search / verify 得到同一份 JSON;
旧版客户端先检查 --help,不要假设已安装包包含新命令。
最小成功路径
- 中文问题先
lookup_mesh或写出英文检索式;search_run.query_analysis.mesh_required为 true 时不得跳过。不要把中文整句直接当已核验检索。 search_papers(建议ranking="relevance");必须报告sources_queried/sources_succeeded/sources_skipped/errors。- 对拟引用记录(通常先 3 条)调用
get_paper_by_id+expected。 - 按
verified/mismatch/not_found/manual_needed分组交付。
正确:lookup_mesh("medical education") →
search_papers("generative AI medical education", ranking="relevance") →
对 DOI 做 expected 核验。
错误:只调用 search_papers("生成式AI医学教育"),并把返回题名当作已核验参考文献。
来源与边界
- 默认论文源:
crossref、pubmed、arxiv、openalex、europe_pmc。 semantic_scholar用于显式搜索、enrich或图谱;富化优先使用 DOI、PMID、arXiv 等强标识符。- OpenAlex 提供跨学科 references / cited_by;PubMed ELink 提供生物医学双向关系。
- Crossref 与 Europe PMC 主要提供 references;arXiv 目前只作为节点和版本线索。
clinicaltrials_gov只服务entity_type="trial",不是论文数据库。- 未连接 Google Scholar、Web of Science、Scopus、Embase、CNKI、万方,不得声称覆盖这些来源。
源失败、限流、缺少强标识符或不支持某方向时,保留成功结果并记录缺口;不能把未查询到解释成没有关系。
引文图谱契约
调用 get_paper_by_id 时可以传:
{
"include_relations": true,
"relation": "both",
"depth": 1,
"rows": 20,
"relation_sources": ["openalex", "crossref", "pubmed", "europe_pmc", "semantic_scholar"]
}
relation 是 references、cited_by 或 both。输出 citation_graph 必须保留:
nodes:合并后的 publication 节点和来源记录;edges:统一为 citing → cited,含relation与observed_by;sources_queried、sources_succeeded、sources_skipped、errors;truncated、truncation_reason、depth_completed。
references 表示种子指向被引用节点,cited_by 表示引用者指向种子。图谱是关系导航和审计数据,
不是证据质量、因果关系、影响力或研究结论评分。
标准执行顺序
- 明确主题、人群/系统、干预、结局、日期、文献类型、预印本政策和实体类型。
- 生物医学问题先用
lookup_mesh核验主题词,再组合题名/摘要自由词。含中文的问题必须先得到 MeSH 或英文检索式。 - 调用
search_papers;保存原查询、日期、请求源、结果数量和search_run。 - 按 DOI、PMID、PMCID、arXiv、OpenAlex、Semantic Scholar 或 NCT 强标识符去重;弱题名匹配保留冲突。
- 对拟引用记录调用
get_paper_by_id+expected,逐项核对题名、首位作者、年份、期刊和标识符。 - 需要时追加一跳引文图谱;二跳、
rows和源列表必须有明确研究目的和预算。 - 按 verified、mismatch、not_found、manual_needed、preprint、trial 分组交付;未核验记录不能静默导出。
- 批量任务使用 workflow,先生成
plan.json,获得批准后再检索,并保存run.json、results.json、verification.json、screening.csv、references.ris和可选graph.json。
Workflow 从 0.3.1 起默认按标识符回查并核验候选元数据。省略 verify 不会把候选视为已核验。
核验范围见 fields、lookup_id / lookup_id_type;来源无法提供的附加 ID 列入
unchecked_identifiers,不能称为已核验,RIS 不写入未匹配的 DOI / PMID。作者截断标记
et al. 不参与作者比较。原始候选和未核验附加 ID 保留在 results.json。
导出默认要求 verified;有 screen 时还要求筛选为 include,exclude、pending_manual、
缺失/无效决定和模型失败的待处理记录均不导出。无需模型筛选时使用
steps: [plan, search, verify, export]。保留人工待处理记录,报告 exported_count;
trial 只保留注册数据,不写成论文 RIS。citation CLI 只下载/转换格式,不自动做 expected 核验。
WPIRONMAN 中转
WPIRONMAN 是可选的 OpenAI-compatible 模型入口,当前 runner 用于摘要级 screen;
plan.json 根据 YAML 本地生成,研究计划或规则可先在客户端整理。
它不是论文来源、数据库、引用验证器,也不替代 Crossref、PubMed、OpenAlex、Europe PMC 或 Semantic Scholar。
export ACADEMIC_SEARCH_LLM_BASE_URL=https://api.wpironman.top/v1
export ACADEMIC_SEARCH_LLM_API_KEY=你的中转密钥
export ACADEMIC_SEARCH_LLM_MODEL=你的模型名
export ACADEMIC_SEARCH_LLM_PROTOCOL=responses_http
默认只发送标题、摘要、标识符和获准元数据;全文必须显式设置 privacy.allow_full_text: true。
密钥不得进入日志、manifest 或 prompt artifact。中转超时、限流或返回坏 JSON 时,
失败的模型步骤标记为 skipped,学术检索、核验和审计继续;待人工筛选记录不进入 RIS。
结果契约
每次成功的 search_papers 返回 search_run,至少保存 run_id、UTC 时间、请求参数、去重前后数量和
result_fingerprint。每条记录保留稳定 record_id、sources、source_records、conflicts、
citation_counts 和 citation_count_source。不得合成没有来源的“总引用数”。
统一 filters 支持日期、语言、作者、文献类型和强标识符;ranking 可设为 relevance 或 none。
相关性排序会写入 ranking_score、ranking_reasons 和 score_version,只表示检索相关性,不表示证据质量。
含中文的查询会在 query_analysis 中给出 contains_cjk、latin_terms、cjk_terms 和 mesh_required。
详细查询构建、来源分层、引用文件和工作流见:
证据规则
- 不编造元数据、摘要、引用次数、标识符、开放获取状态、全文结论或试验结果。
- 不把预印本描述为同行评审论文,不把 trial 注册描述为已发表研究。
- 不因为来源适配器存在就声称它本次已查询;以实际
sources_queried为准。 - 不把引用数量、图谱度数或模型排序当作证据质量或因果证据。
レビュー
まだレビューはありません。使ってみた感想をお寄せください。