literature-survey
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/literature-surveyConducts autonomous literature surveys using five research paradigms
- Solves the problem of efficiently gathering and analyzing academic literature
- Leverages search APIs, citation networks, and classification models
- Routes strategies based on research intent and budget constraints
- Delivers structured outputs including summaries, gaps, and thematic maps
SKILL.md
.github/skills/literature-surveyView on GitHub ↗
--- name: literature-survey description: Autonomous Literature Survey Campaign — 5 research paradigms (scoping, systematic, deep, narrative, snowball) with quantitative budget enforcement. Selects and executes the right survey paradigm based on research intent. execution: campaign used-by: knowledge-acquisition --- # Literature Survey Autonomous literature survey engine. Five research paradigms, each a self-contained playbook with quantitative budget enforcement. You provide a research question — it searches, screens, reads, categorizes, identifies gaps, and produces a structured survey output. ## Strategy Routing | Signal | Strategy | |--------|----------| | 新领域全景映射、broad overview、field mapping | → scoping-survey | | 穷尽式覆盖、PRISMA、systematic review | → systematic-survey | | 精确子问题、specific mechanism、deep dive | → deep-survey | | 理论驱动、argument building、narrative | → narrative-review | | 种子论文、citation chain、lineage tracing | → snowball | ## Manifest ### Strategies (5) - scoping-survey - systematic-survey - deep-survey - narrative-review - snowball ### Tactics (3) - prisma-screening - citation-chaining (shared: patent-mining, baseline-establishment) - narrative-framing ### Subagent SOPs (11) - survey-synthesis - define-search-protocol - categorize-papers (shared: meta-analysis, baseline-establishment) - extract-data - quality-assessment - seed-selection - saturation-detection (shared: patent-mining, benchmark-archaeology) - taxonomy-mapping - prisma-flowchart - thematic-coding - gap-identification (shared: benchmark-archaeology, baseline-establishment) ### Import SOPs (5, shared across all campaigns) - web-search - web-research - paper-overview - paper-search - paper-research ## Budget Table | Strategy | web-search | web-research | paper-overview | paper-search | paper-research | |----------|-----------|-------------|---------------|-------------|---------------| | scoping-survey | 100 | 10 | 100 | 20 | 0 | | systematic-survey | 50 | 5 | 60 | 40 | 30 | | deep-survey | 30 | 5 | 40 | 40 | 20 | | narrative-review | 80 | 15 | 50 | 40 | 20 | | snowball | 20 | 3 | 30 | 30 | 20 | All values ±10% flexibility. Deviations require explicit reasoning. ## MCP Tools | MCP Server | Tools | |------------|-------| | brave-search | brave_web_search, brave_news_search, brave_llm_context | | apify | rag-web-browser, google-scholar-scraper | | alphaxiv | discover_papers, get_paper_content, answer_pdf_queries, read_files_from_github_repository | | semantic-scholar | ss_paper, ss_paper_batch, ss_references, ss_citations, ss_recommendations, ss_relevance_search, ss_author, ss_author_papers | ## Context Management - Campaign start: context-init - After each strategy completes: context-checkpoint (append to literature-survey context file)