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…
Produce final structured audit report
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill benchmark-synthesis --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/benchmark-synthesisContext preview
The summary Claude sees to decide when to auto-load this skill.
Produce final structured audit report
name: benchmark-synthesis description: Produce final structured audit report execution: subagent prompt: ./prompt.md input: all_analysis_results dependencies: sops: - spawn-agent
Synthesize all analysis results from a benchmark archaeology campaign into a final structured report with cross-cutting findings, prioritized recommendations, and actionable conclusions.
1. Aggregate findings across all analysis dimensions 2. Identify cross-cutting themes and systemic issues 3. Prioritize findings by impact and actionability 4. Produce executive summary and detailed report 5. Generate specific recommendations for benchmark users and creators
Final synthesis report suitable for publication or decision-making.
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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…