AHRQ PiCMe Assessment
SkillDev toolsSOP: Use the AHRQ PiCMe framework to systematically assess a research gap across 6 dimensions
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the AHRQ PiCMe Assessment skill
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/ahrq-picme-assessment/SKILL.md and read by ahel’s review.
Use the AHRQ PiCMe framework to systematically assess a research gap across 6 dimensions.
HARD-GATE
Pipeline
- Precondition check: verify completeness of the input GapRecord; confirm the domain field is valid
- Population (P): identify the target population/system/dataset the gap concerns; assess clarity of definition (1-5)
- Intervention (I): identify the proposed intervention/method/solution; assess operationalizability (1-5)
- Comparator (C): identify the comparison baseline (existing SOTA, no intervention, alternative approach); assess baseline reasonableness (1-5)
- Metrics (M): identify the evaluation metrics; assess their measurability and relevance (1-5)
- Evidence (E): assess the strength of existing evidence supporting the existence of the gap (1-5)
- Overall verdict: judge overall quality from the mean of the 5 dimensions (strong ≥ 3.5 / moderate 2.5-3.4 / weak < 2.5); generate a research question draft
- Output: return the PiCMeAssessment object
Output Format
{
"gap_id": "gap_001",
"dimensions": {
"population": { "score": 4, "description": "Target population description", "rationale": "..." },
"intervention": { "score": 3, "description": "Intervention/method description", "rationale": "..." },
"comparator": { "score": 3, "description": "Comparison baseline description", "rationale": "..." },
"metrics": { "score": 4, "description": "Evaluation metric description", "rationale": "..." },
"evidence": { "score": 4, "description": "Evidence strength description", "rationale": "..." }
},
"mean_score": 3.6,
"overall_verdict": "strong",
"research_question_draft": "Research question draft (1 sentence)",
"improvement_suggestions": ["Suggestion 1", "Suggestion 2"]
}
Signals
- GitHub stars
- 469
- Forks
- 37
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
ahrq-picme-assessment- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine