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v3.0.0 — Pure-Skill Architecture

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@Pthahnix Pthahnix released this 19 May 10:13

What's New

Complete architectural rewrite. DARE is now a pure-markdown skill system — 800+ skills, zero application code, CC as the runtime.

Architecture

  • 4-layer military hierarchy: Campaign (8) → Strategy (40+) → Tactic (100+) → SOP (600+)
  • 9 orchestrator skills as the control plane above the hierarchy
  • Non-linear execution with explicit backtrack conditions and ±10% deviation rules
  • Executable Research Specs with checkbox progress tracking and session recovery

Orchestration Flow

  1. North Star Crystallization (cold/warm/hot-start)
  2. Research Spec Generation (structured questioning → outline → full spec)
  3. Spec Execution (autonomous, stage-by-stage, with context checkpoints)

MCP Integrations (5 servers)

  • @yogsoth-ai/semantic-scholar-mcp — paper lookup, citations, recommendations
  • @yogsoth-ai/wiki-vault — research knowledge graph with BM25 search
  • @brave/brave-search-mcp-server — web search, news, LLM context
  • @apify/actors-mcp-server — web scraping, Google Scholar
  • alphaxiv (HTTP) — arXiv paper search, PDF queries

Design Philosophy

Arsenal, not pipeline. The AI has full cross-stage routing authority. Research Specs define when to backtrack, not just what order to execute. Every existing autonomous research system (AI Scientist v2, AI-Researcher, Dolphin, Agent Laboratory, ARIS) is a fixed pipeline — DARE is the first to implement non-linear agent-decided orchestration with explicit backtrack mechanisms.

Skills by Source

Source Count Coverage
north-star-crystallization ~30 Direction finding
knowledge-acquisition ~120 Literature, citation chaining
deep-insight ~80 Gap analysis, abstraction
hypothesis-formation ~60 Abductive/inductive/deductive
creative-ideation ~150 SCAMPER, TRIZ, biomimicry, morphological
convergence ~90 Multi-criteria scoring, Pareto, synthesis
stress-test ~70 Red-teaming, assumption destruction
experiment-execution ~50 Factor design, sensitivity analysis
infrastructure (4 repos) ~40 Web, literature, subagents, context

The orchestrator of the Yogsoth AI research ecosystem.