knowledge-acquisition

Research

Research Knowledge Acquisition Engine with 5 campaigns (literature-survey, patent-mining, benchmark-archaeology, meta-analysis, baseline-establishment). Use this skill whenever a user needs to systematically acquire research knowledge — academic literature, patent landscapes, benchmark evaluations, cross-study statistical synthesis, or SOTA performance baselines. Pre-condition: north-star-crystallization must be complete.

QUICK START

How to use this skill

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Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/knowledge-acquisition/SKILL.md

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Knowledge Acquisition

Systematic research knowledge acquisition engine. Five campaigns, each a self-contained autonomous research activity domain. You provide a research intent — the engine routes to the right campaign, selects a strategy, and executes autonomously with quantitative budget enforcement.

Pre-condition

North-star-crystallization must be complete before entering any campaign. Research intent must be fully crystallized.

Four-Level Hierarchy

ENTRY.md (this file)
  → Campaign (5): self-contained research activity domain
    → Strategy: selected by analysis purpose/intent
      → Tactic: multi-step orchestration pattern (reusable across strategies)
        → SOP: single operation (import or subagent)

Campaign Routing

Signal	Campaign
literature review, survey, paper search, PRISMA, snowball	→ literature-survey
patent analysis, prior art, white space, claims, IPC	→ patent-mining
benchmark analysis, evaluation methods, metric flaws, leaderboards, saturation	→ benchmark-archaeology
cross-study statistical synthesis, effect size, heterogeneity, publication bias, GRADE	→ meta-analysis
SOTA compilation, performance comparison, baseline reproduction, progress curves	→ baseline-establishment

Multi-Campaign Orchestration

Campaigns can be composed:

Serial: literature-survey → baseline-establishment (survey first, then collect performance data)
Parallel: patent-mining ∥ benchmark-archaeology (independent analyses on the same topic)
Conditional: literature-survey → IF gaps found → meta-analysis (evidence synthesis on identified gaps)

The orchestrator decides composition based on the crystallized North Star statement.

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 Integration

Campaign start: context-init (load/create campaign context file)
After each strategy completes: context-checkpoint (append findings to campaign context file)
One context file per campaign: all strategy outputs accumulate in a single campaign-scoped file

Dependencies

Dependency	What It Provides
web-browsing	web-search + web-research
literature-engine	literature-overview + literature-search + literature-research
subagent-spawning	Subagent dispatch conventions
context-management	Checkpoint protocol

Available Campaigns

Optional, no fixed order; the final leaf is always a sop.

Campaign	When to use
baseline-establishment	SOTA Performance Baseline Campaign — 5 strategies for systematically collecting, standardizing, and analyzing performance data across methods. Produces standardized comparison tables, progress curves, and headroom analysis.
benchmark-archaeology	Evaluation Methodology Archaeology Campaign — 5 strategies for systematic analysis of AI/ML benchmarks, metrics, and leaderboards. Reveals construct validity issues, saturation, data contamination, and evaluation protocol inconsistencies.
literature-survey	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.
meta-analysis	Cross-Study Statistical Synthesis Campaign — 5 strategies for systematic collection and methodological planning of multi-study evidence synthesis. Covers pairwise, network, cumulative meta-analysis, heterogeneity investigation, and bias detection. Stops at protocol design (no computation).
patent-mining	Systematic Patent Analysis Campaign — 5 strategies for patent landscape analysis, prior art search, white space identification, competitive intelligence, and claim analysis. Produces structured patent intelligence reports.