Search SOP

Search SOP — 文献搜索标准操作规程

适用场景

Read this skill when the user's request involves any of:

• Searching for academic papers, preprints, or datasets
• Importing references from Zotero, EndNote, BibTeX, or RIS
• Importing a local PDF into the library
• Asking for "最新/latest/recent" papers (recency search)
• Requesting literature from a specific database (CNKI, Google Scholar, WoS, etc.)
• Multi-concept intersection queries (e.g., "PFAS + machine learning")
• Understanding which API tool to use for a specific academic domain

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1. Three-Layer Search Architecture

Literature search uses a priority fallback model. Start from Layer 0 for local imports; Layer 1 for search; escalate to Layer 2/3 when the previous layer cannot satisfy the request.

Layer 0 — Local Reference Manager Import (not search)

One-time or periodic import from user's existing reference manager. These are NOT search tools — they read local databases directly.

Zotero fallback chain (try in order):

1. SQLite direct — fastest, works offline, Zotero need not be running
2. Local API (localhost:23119) — Zotero must be running, read-only
3. Web API v3 (api.zotero.org) — needs API Key + User ID, full CRUD
4. Format export — library_export_bibtex/ris → guide user to import manually

EndNote fallback chain: SQLite direct → Format export (no API available).

Docker environment: SQLite and Local API unavailable (host filesystem isolated). Explain to user: use BibTeX/RIS export from source app, or mount host Zotero directory as Docker volume.

Reverse path (RC → Zotero/EndNote): If Zotero Web API Key configured → library_zotero_web_create (requires approval_card). Otherwise → library_export_bibtex + guide user to File > Import in their reference manager.

Other reference managers (Mendeley, ReadCube, JabRef, Citavi, etc.): No direct bridge. Guide user to export BibTeX/RIS → library_import_bibtex/library_import_ris.

Key behaviors: detect → available: false in Docker → explain host isolation, suggest BibTeX/RIS. Reverse write via Web API → approval_card (risk_level: medium). First detection → record in MEMORY.md ## Global > ### Environment.

Layer 1 — Built-in API Tools (free, no auth, structured data)

Always available, require NO API keys. Use as primary search method.

Layer 1.5 — web_fetch Direct Access (relaxed — any public academic URL)

Between L1 API tools and L2 browser, use web_fetch to directly access any publicly accessible academic URL (not limited to known URLs).

Allowed targets (non-exhaustive):

• arXiv RSS (latest by category): https://rss.arxiv.org/rss/{category} (e.g. cs.CV)
• arXiv API (structured): https://export.arxiv.org/api/query?search_query=ti:transformer&sortBy=submittedDate&sortOrder=descending&max_results=20
• Semantic Scholar API: https://api.semanticscholar.org/graph/v1/paper/search
• CORE API: https://api.core.ac.uk/v3/search/works
• OA full-text links — URLs returned by find_oa_version (Unpaywall)
• Author/lab homepages — publication lists, preprint links
• Conference proceedings pages — NeurIPS, ICML, ACL, AAAI proceedings
• Preprint servers — bioRxiv, medRxiv, SSRN landing pages
• PubMed RSS: subscribe URLs from PubMed search results
• Repository metadata — GitHub/GitLab README for research software

RESTRICTIONS (do NOT web_fetch):

• Pages requiring login/authentication
• Paywalled full-text (use find_oa_version first)
• Pages with anti-scraping measures that return empty content

When to use web_fetch: Any public academic URL; page is static HTML or API endpoint; extracting content from a specific page. When to use browser instead: Form interaction needed; JavaScript rendering required; multi-page navigation.

Layer 2 — Browser RPA (databases without public APIs)

When Layer 1 tools cannot reach the required database, use the browser tool.

Target databases: Google Scholar, CNKI / 万方 / 维普, Web of Science / Scopus, IEEE Xplore, ACM DL, SpringerLink, any user-specified database.

CNKI (中国知网) — delegate to the dedicated skills. For any CNKI task, do NOT hand-write browser steps here. Use the purpose-built cnki-* skills instead, which carry verified selectors, captcha/login detection, and single-call extraction: cnki-search / cnki-advanced-search (search), cnki-parse-results, cnki-paper-detail, cnki-journal-search / cnki-journal-index / cnki-journal-toc, cnki-navigate-pages, cnki-download (login required), cnki-export (Zotero). They are the primary path for Chinese-journal retrieval.

IMPORTANT: Never pass profile parameter — omit it to use the default managed browser.

Workflow: open url → snapshot mode=efficient (note targetId) → act kind=type (query) → act kind=click (submit) → snapshot mode=efficient (extract results) → library_add_paper or report → close.

Critical: Always use mode=efficient (~10K chars vs 80K default). Always pass targetId from snapshot into act calls.

Error recovery: "Element not found" → one fresh snapshot, retry once. "Tab not found" → browser action=tabs for active targetIds. Context overflow → extract from last snapshot and close.

Operational limits (revised):

• Max 8 browser snapshots per search session
• Pagination: allowed up to 3 pages of results
• Click into paper detail pages: allowed for extracting abstract, citation count, and metadata
• STILL FORBIDDEN: downloading PDFs, submitting forms, creating accounts, entering personal data (standard GDPR/cookie consent banners may be dismissed with a single click)
• MUST always close browser after search is complete

Layer 3 — API Key Required (optional, user configures)

Do NOT prompt users to register. Only use when the user has already configured.

Third-party keys (Serper, Tavily, etc.): user installs skill/MCP themselves. Never ask users to register for third-party API keys.

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2. Domain → Tool Routing

Domain routing below is a STARTING POINT, not a hard constraint. If primary tools return insufficient results, expand to other tools (see §15 Search Iteration Protocol). Do NOT send queries to the wrong domain's tool.

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3. Tool Filter Capability Matrix

What each tool CAN filter — determines routing decisions.

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4. Sort Parameters Quick Reference

When the user asks for "latest/最新" papers, you MUST pass date-based sort params.

Default sort is relevance for most tools. Never rely on the default when the user wants recent papers.

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5. Trigger Word Table

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6. Recency Search Protocol

When the user asks for "最新", "latest", "recent", or "past N months/weeks" papers, you MUST override default relevance sorting with date-based sorting.

Recency search workflow:

1. Determine time range: "最新" = last 3 months; "近期" = last 6 months; explicit range if stated.
2. Select 2+ sources by domain (see §2 Domain→Tool Routing).
3. Pass date-based sort and date filter where both are supported (see §4).
4. If API results are insufficient, escalate:
   • web_fetch arXiv RSS feed: https://rss.arxiv.org/rss/{category}
   • browser → Google Scholar with date filter (Tools → Custom range)
5. Never cite web_search / Brave Search unavailability as a reason to stop.

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7. Selection Logic Decision Tree

0. "latest/最新/recent"? → §6 Recency Protocol. MUST pass date sort.
1. Database NOT in L1 (CNKI, WoS, Scopus, GScholar)? → Layer 2 Browser.
2. Journal name specified? → search_crossref(journal=...) + search_europe_pmc(JOURNAL:...).
   Returns 0? → Layer 2 Browser.
3. Complex multi-filter? → Combine broadest tool + local filtering.
   Still insufficient? → Layer 2 Browser.
4. Simple keyword? → Route by domain (§2). Use 2+ sources for targeted/exhaustive.
5. L1 returns 0? → Suggest broadening keywords + offer L2/web_fetch.
   Do NOT retry same source. Do NOT cite "web_search not configured."
6. Multi-concept intersection? → §8 Decomposition.

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8. Multi-Concept Query Decomposition

When the user's topic spans multiple distinct concepts (e.g., "PFAS / microplastics / EDCs + machine learning"), a single combined query returns noisy results because text-based search engines match ANY keyword, not the intersection.

Decomposition strategy:

1. Identify the anchor concept — the methodological or thematic constant (e.g., "machine learning").
2. Split domain-specific concepts into separate sub-queries, each paired with the anchor.
3. Run each sub-query independently on the appropriate L1 tool(s) for the domain.
4. Merge and deduplicate results by DOI / title before presenting.
5. Use filters (from_year, has_abstract: true, sort: "published") on each sub-query.

Anti-patterns:

• Concatenating all keywords into one query string
• Using arXiv for non-CS/physics/math domains just because "machine learning" appears
• Reporting noisy results without filtering — always rate relevance before presenting

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9. L1 → L2 Escalation Rules

Use L2 when: user asks for CNKI/WoS/Scopus/Google Scholar, L1 returns 0 for journal query, need paywall fulltext, need faceted search or conference proceedings.

Do NOT use L2 for: simple keyword search (L1 faster), DOI resolution (resolve_doi), citation tracking (get_citations_open).

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10. Source Health Awareness

Tool responses include _source_health: { source, latency_ms }.

• Within session: 2+ errors (429/503/timeout) from a source → stop using it, switch to alternative (§2).
• Across sessions: 3+ consecutive sessions with failures → record in MEMORY.md: Source {name} unreliable since {date}: {pattern}. Prefer {alt}.
• Always use at least two sources for targeted/exhaustive scopes.

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11. Dynamic Tool Priority

User-configured API keys override defaults by elevating that service to L1:

• Record in MEMORY.md ## Global > ### Environment: "Wentor API: configured", etc.
• MUST-USE rule: User-configured API → call FIRST, then supplement with standard L1. Example: Wentor API configured → wentor_search FIRST, then arXiv/CrossRef.
• Brave API Key → web_search at L1. Zotero API Key → library_zotero_web_*.
• Never store actual API key values — only "configured" status.

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12. PDF Import Protocol

"导入PDF / import PDF" workflow:

1. Read the PDF (extract metadata: title, authors, DOI, abstract).
2. Verify via resolve_doi / search_arxiv (match title or DOI).
3. Dedup with library_search (check if already in library).
4. library_add_paper with source: "local_import" + pdf_path.
5. Never fabricate metadata — if extraction fails, ask the user.

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13. Post-Search Processing

1. Deduplicate — check DOI / arXiv ID against local library before adding.
2. Rate relevance — high / medium / low. Only add high + medium to library.
3. Batch import — use library_batch_add for 3+ papers.
4. Tag immediately — apply topic tags at import time for future retrieval.

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14. Paper Evaluation Criteria

Rate each paper high / medium / low based on: venue quality, citation count (adjusted for age), methodology soundness, reproducibility, and relevance to the user's question. Only add high + medium papers to the library unless user requests otherwise.

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15. Search Iteration Protocol

After every search execution, you MUST evaluate results before presenting them to the user. Do NOT treat one-shot search as final.

Evaluation Checklist (执行完每次搜索后必须评估)

1. Quantity: ≥5 relevant papers? If NO → broaden keywords OR switch source
2. Recency: Includes papers from last 2 years? If NO → add date filter
3. Coverage: Different methodologies/schools covered? If NO → cross-source search
4. Key papers: High-citation papers included? If NO → re-search with search_openalex(sort_by='cited_by_count') or search_crossref(sort='cited-by')

Iteration Rules

• Maximum 3 search iterations per topic
• Each iteration: use a different tool OR different keywords (NEVER repeat the same query)
• After each iteration, report a brief summary to the user (what was found, what is still missing)
• If 3 iterations exhausted and still insufficient → inform user and suggest web_fetch (L1.5), Layer 2 browser, or Layer 3 APIs

Cross-Source Search (supplements §2 domain routing)

§2 domain routing is a starting point. When primary results are insufficient:

1. Primary search: Use 1–2 tools from §2 domain routing
2. Supplementary search: If primary results fail the Evaluation Checklist → expand to other L1 tools or web_fetch
3. Merge & dedup: Deduplicate by DOI / title across all sources before presenting

Iteration Decision Flow

Search executed
  → Run Evaluation Checklist (4 criteria above)
  → ALL pass? → Present results, DONE
  → ANY fail?
      → Iteration count < 3?
          YES → Refine (different tool / keywords / filters) → re-search → re-evaluate
          NO  → Present best results + inform user of gaps + suggest next steps

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RC Local Tools Reference

library_* Call Patterns

search_* → library_* Integration

After search: present paper_card per result → user selects → library_add_paper or library_batch_add → auto task_link if active project → tag with search topic.

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Related Research-Plugins Skills

Browse these subcategory indexes for fine-grained methodology skills:

• literature/search/ — Boolean search, arXiv API, Semantic Scholar, citation chains
• literature/metadata/ — DOI resolution, OpenCitations, impact factors
• literature/fulltext/ — Unpaywall, OA strategies, preprint access
• literature/discovery/ — paper recommendation, trend monitoring
• tools/knowledge-graph/ — citation networks, knowledge graph construction
• tools/scraping/ — web scraping for academic sources
• tools/ocr-translate/ — OCR for scanned PDFs, multilingual translation
• domains/ — 16 discipline-specific subcategories (ai-ml, biomedical, chemistry, cs, ecology, economics, education, finance, geoscience, humanities, law, math, pharma, physics, social-science, business). Browse domains/{discipline}/ for domain-specific search strategies and database guides