900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer hierarchy (Campaign → Strategy → Tactic → SOP). Non-linear orchestration with backtracking, 6 MCP integrations. The AI is the researcher — you set the direction.
This repository also configures its own agents. See what de-anthropocentric-research-engine tells them →
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
What will competitors do? — Competitive method progress prediction and time window analysis.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Competitor perspective — design strategies to defeat this solution, then use attack vectors to improve it.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude Code
Tactic: Compile the feeding plan into an ARA via the external compiler, then run Level-2 rigor review over it.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Decompose system into functional components, identify dependencies, and surface trimming candidates.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Component-level surgical operations (subtract/multiply/divide/unify/redirect) from Systematic Inventive Thinking (SIT).
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Generate compressed conflicts (oxymorons) from problem contradictions and extract concrete idea directions from the symbolic tension.
yogsoth-ai/de-anthropocentric-research-engine
Skill Claude CodeCodex
Normalize results by compute budget (Pareto analysis).
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: