| name | overconfidence-prevention |
| description | Detect and reduce overconfident reasoning in analysis, plans, estimates, reviews, and recommendations. Use when conclusions may be based on weak evidence, hidden assumptions, premature certainty, or insufficient exploration of alternatives. |
| when_to_use | when an answer, plan, estimate, or review needs calibration against evidence strength, uncertainty, assumptions, and plausible alternatives |
| version | 1.0.0 |
| domain | reasoning-calibration |
| inputs | [{"claim_or_recommendation":"the conclusion, plan, estimate, or assertion to calibrate"},{"evidence":"observations, sources, tests, or constraints supporting the claim"},{"decision_context":"what decision depends on the claim"},{"alternatives":"competing explanations or options already considered"}] |
| outputs | [{"selected_workflow":"one of {calibrate-confidence}"},{"calibration_report":"evidence-strength assessment and confidence recommendation"},{"assumptions":"explicit assumptions with confidence and validation method"},{"missing_evidence":"information that would materially change confidence"},{"safer_rewrite":"calibrated wording or decision framing"}] |
Overconfidence Prevention Skill
This skill helps an agent avoid sounding more certain than the evidence supports. It does not force indecision; it makes confidence proportional to evidence, risk, and reversibility.
Workflow Selection
Use workflows/calibrate-confidence.md for any conclusion that needs a confidence check before it informs a decision.
Calibration Checks
- Evidence strength: Is the conclusion based on direct evidence, inference, analogy, or guesswork?
- Coverage: Did the analysis inspect the relevant cases, files, stakeholders, or failure modes?
- Alternatives: What else could explain the same observations?
- Assumptions: Which premises are unstated, unverified, or inherited from prior work?
- Reversibility: How costly is it if the conclusion is wrong?
- Wording: Does the answer distinguish fact, inference, recommendation, and uncertainty?
Confidence Labels
- High: Direct evidence covers the important cases; alternatives are weak or ruled out.
- Medium: Evidence is credible but partial; alternatives remain plausible.
- Low: Evidence is indirect, sparse, stale, or highly assumption-dependent.
Output Standard
Always separate:
- What is known
- What is inferred
- What is assumed
- What remains uncertain
- What would change the recommendation
