'Research Knowledge Acquisition Engine with 5 campaigns (literature-survey,
Scanned 9/5/2026
Install to Claude Code
npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill knowledge-acquisition --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: knowledge-acquisition
description: '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.'
dependencies:
campaigns:
- baseline-establishment
- benchmark-archaeology
- literature-survey
- meta-analysis
- patent-mining
---
# 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 |
<!-- BEGIN available-tables (generated) -->
## 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. |
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