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@Pthahnix Pthahnix released this 11 Apr 07:24
v0.1.0
537bcc3

DARE is not a tool that helps you do research — it is the researcher. You set the direction; DARE searches, reads, discovers gaps, generates ideas, designs experiments, and executes them on GPUs. Autonomously. Iteratively. Without asking for permission.

This is the first public preview of the De-Anthropocentric Research Engine.

Highlights

  • 49 LLM micro-agent tools — each tool is a single-responsibility AI agent with its own system prompt and reasoning chain. When "debate-critic" runs, it genuinely tries to destroy the idea it's reviewing.
  • Autonomous literature survey — searches Google Scholar, downloads full papers (not just abstracts), reads them cover-to-cover with a three-pass Keshav protocol
  • 31 ideation methods across 5 categories — SCAMPER, component surgery, cross-domain collision, perspective forcing, structural deconstruction — filtered by MAP-Elites quality-diversity algorithm
  • Adversarial debate — Proposer-Critic-Judge architecture validates every gap, insight, and idea through structured multi-round debates
  • 7-step INSIGHT pipeline — root-cause drilling, stakeholder mapping, tension mining, question reformulation, abstraction laddering, assumption audit, and validation
  • Deep reference exploration — traces citation graphs via Semantic Scholar, enriches metadata from arXiv and Unpaywall

Architecture

DARE follows a four-layer military command hierarchy — each layer calls only the layer directly below it:

General  (Meta-Strategy)  ->  "Take that hill"         ->  WHAT to research
Colonel  (Strategy x8)    ->  "Flank from the east"    ->  WHEN and WHY
Captain  (Tactic x15)     ->  "Squad A cover, B move"  ->  HOW to combine
Sergeant (SOP x60)        ->  "Fire, reload, advance"  ->  HOW to execute
         (Tools x49+)     ->  atomic MCP operations    ->  WHAT to do

84 skills total. A Strategy never touches tools directly; a Tactic never decides research direction. Every component is independently testable, replaceable, and composable.

Under the Hood

Monorepo with 4 packages, 8 MCP servers, 85+ tests:

Server Tools Purpose
dare-agents 49 LLM micro-agent tools (ideation, debate, insight, method-evolve)
dare-scholar 5 Academic paper pipeline — search, fetch, read, reference
dare-web 2 Web page fetching and markdown caching
dare-session — Git-based context transfer to remote GPU pods
+ apify, brave-search, runpod, alphaxiv 13 External services

Built on pi-ai for LLM completions and the Model Context Protocol for tool orchestration. Designed to run inside Claude Code.

Get Started

git clone https://github.com/Pthahnix/De-Anthropocentric-Research-Engine.git
cd De-Anthropocentric-Research-Engine
npm install

See the README for full setup (API keys, MCP server configuration).

What's Next

  • Experiment execution — autonomous experiment design and GPU execution via RunPod
  • Method evolution — AlphaEvolve-inspired evolutionary improvement of DARE's own research methods (core tools already implemented)
  • Paper writing — end-to-end autonomous paper drafting from research findings
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