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…
Establish acceptability standards through RAND/UCLA Appropriateness Method
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill appropriateness-bounding --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/appropriateness-boundingContext preview
The summary Claude sees to decide when to auto-load this skill.
Establish acceptability standards through RAND/UCLA Appropriateness Method
name: appropriateness-bounding description: Establish acceptability standards through RAND/UCLA Appropriateness Method or Consensus Conference protocols. dependencies: tactics: - iterative-convergence-round - threshold-calibration sops: - consensus-synthesis
**Purpose:** Determine what is appropriate, acceptable, or indicated for a given context. Uses the RAND/UCLA Appropriateness Method (rating + discussion + re-rating) or Consensus Conference (citizen jury) format to establish boundaries of acceptability.
**When to use:**
| Parameter | Constraint | |-----------|-----------| | Rounds | 2 (rate → discuss → re-rate) | | Perspectives | ≥4 (ideally 7–15 for RAND/UCLA) | | Rating scale | 1–9 (inappropriate to appropriate) | | Agreement threshold | Median ≥7 without disagreement |
| Key | Type | Description | |-----|------|-------------| | indications | array | List of scenarios to rate | | perspectives | array | Panel member perspectives | | round_1_ratings | array | Initial ratings per indication | | discussion_notes | string | Key points from discussion | | round_2_ratings | array | Post-discussion ratings | | classifications | object | Appropriate/uncertain/inappropriate per item |
1. Define indications/scenarios clearly (clinical scenarios, use cases) 2. Collect Round 1 ratings (1–9 scale) with brief rationale 3. Distribute feedback showing distribution of ratings 4. Facilitate structured discussion of disagreements 5. Collect Round 2 ratings 6. Classify each indication: appropriate (median 7–9), uncertain (4–6), inappropriate (1–3) 7. Flag items with disagreement (where panel lacks agreement despite median)
classifications:
appropriate: [{indication, median, agreement_level}, ...]
uncertain: [{indication, median, agreement_level}, ...]
inappropriate: [{indication, median, agreement_level}, ...]
disagreement_items: [{indication, reason}, ...]
panel_size: <int>
method: RAND/UCLA | Consensus Conference<!-- BEGIN available-tables (generated) -->
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use | | --- | --- | | iterative-convergence-round | Execute one full Delphi round — collect judgments, distribute anonymous feedback, measure consensus, decide whether to continue. | | threshold-calibration | Systematically sweep consensus thresholds to observe which items achieve consensus at what level, producing a threshold-consensus curve. |
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use | | --- | --- | | consensus-synthesis | Synthesize all rounds into a final consensus report documenting agreements, dissent, and process. |
<!-- END available-tables (generated) -->
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
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