agentleFS
yogsoth-aiyogsoth-ai/convergence/skills/appropriateness-bounding/SKILL.md

appropriateness-bounding

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

Establish acceptability standards through RAND/UCLA Appropriateness Method or Consensus Conference protocols.

The file

Files
SKILL.md

Appropriateness Bounding

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:

  • Medical guideline development (appropriate indications)
  • Regulatory standard setting
  • Establishing acceptable thresholds for action
  • Any question of the form "is X appropriate when Y?"

Budget

ParameterConstraint
Rounds2 (rate → discuss → re-rate)
Perspectives≥4 (ideally 7–15 for RAND/UCLA)
Rating scale1–9 (inappropriate to appropriate)
Agreement thresholdMedian ≥7 without disagreement

State Ledger

KeyTypeDescription
indicationsarrayList of scenarios to rate
perspectivesarrayPanel member perspectives
round_1_ratingsarrayInitial ratings per indication
discussion_notesstringKey points from discussion
round_2_ratingsarrayPost-discussion ratings
classificationsobjectAppropriate/uncertain/inappropriate per item

Available Tactics

  • iterative-convergence-round — Two-round rate-discuss-rerate cycle
  • threshold-calibration — Determine where appropriateness boundaries fall

Available SOPs

  • judgment-collection
  • feedback-distribution
  • consensus-measurement
  • round-decision
  • threshold-sweep
  • consensus-classification
  • consensus-synthesis

Execution Guidance

  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)

Output Format

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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.