formated-results
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced…
KAOS-style recursive goal decomposition. AND decomposition for sub-goals
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill and-or-decompose --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/and-or-decomposeContext preview
The summary Claude sees to decide when to auto-load this skill.
KAOS-style recursive goal decomposition. AND decomposition for sub-goals
name: and-or-decompose description: KAOS-style recursive goal decomposition. AND decomposition for sub-goals that must ALL be satisfied. OR decomposition for alternative paths where any one suffices. Produces a GoalTree (DAG structure). execution: subagent prompt: ./prompt.md input: top_goal (string), actor_profile (string), obstacle_report (string) dependencies: sops: - spawn-agent
Recursively decompose the top goal into a structured GoalTree.
Subagent — spawned via `subagent-spawning/spawn-agent` skill.
GoalTree — DAG with AND/OR nodes, leaf nodes representing actionable sub-goals.
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Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |
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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Closing skill for the research-executor, loaded as the last step of formated-specs. Summarize the design just produced into one research-result JSON fenced…
Spec-slot skill for the research-executor. Emit the 4-layer DARE orchestration of the assigned topic as one research-graph JSON fenced block in your reply.…
Loss-1 judge (codex role). Given one sample's de-identified dialogue and its PolicyCard, decide axis-by-axis whether the user-simulator enacted the card's…
Loss-2 judge (codex role). Over one topic's 6 shuffled research-design samples, pairwise-rank by quality using the D1–D5 standard. Emit the pairwise log; the…
The optimizer brain for the ladder-foundry pretraining loop. Runs the two-level nested batch loop, delegates gating to gate_eval, attributes a failing batch to…
Tactic: Extract atomic units from one paper and score how much of a caller-supplied summary covers. Use for ACU-style binary or Nugget-style ternary recall…