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数据与研究 · SKILL.md

Compare

Compare

【数据与研究】Rigorous comparisons with confidence parity, weighted criteria, and research depth tracking.

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技能说明

GitHub

name: Compare slug: compare version: 1.0.0 description: Rigorous comparisons with confidence parity, weighted criteria, and research depth tracking. homepage: https://clawic.com/skills/compare metadata: clawdbot: emoji: ⚖️ displayName: Compare

Core Principle

Comparisons fail when confidence is uneven. Only as reliable as the weakest-researched dimension.

Protocol

Criteria → Research Parity → Confidence Check → Score → Present

1. Criteria

  • Load domain defaults (domains.md)
  • Overlay user preferences from memory
  • If unknown: "What matters most here?"
  • Output: Ranked criteria with weights (sum = 100%)

2. Research Parity (Critical)

Research each item to equivalent depth before scoring.

Track: | Criterion | Item A sources | Item B sources |

5 reviews for A but 1 for B? Research more for B first. Never score unbalanced data.

3. Confidence Check

Verify before presenting:

  • Each item researched equally
  • Each criterion researched equally
  • Source quality comparable
  • Data recency comparable

Fail any? Research more OR caveat explicitly.

4. Score

Final = Σ(criterion_score × weight) — Show the math.

5. Present

🆚 [A] vs [B]
📊 CRITERIA: [ranked by weight]
📈 SCORES: [table + confidence per row]
🎯 RESULT: [Winner] by [margin]
⚠️ CAVEATS: [imbalances]
💡 IF [X] MATTERS MORE: [alt winner]

After

Note which criteria user focused on. Update preferences.md by category.

Decline When

Research parity impossible, priorities unclear, or time insufficient. Partial > misleading.

References: domains.md, confidence.md, traps.md, preferences.md

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