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thinking-kepner-tregoe

Use when a selective defect needs IS/IS-NOT difference analysis or a consequential option choice needs must/want weighting and adverse-consequence comparison.

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Repository
tjboudreaux/cc-thinking-skills
Letzte Quellaktivität
17. Juli 2026 um 01:39
Erkannte Sprache von SKILL.md
Englisch
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1.323
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159

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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
thinking-kepner-tregoe
description
Use when a selective defect needs IS/IS-NOT difference analysis or a consequential option choice needs must/want weighting and adverse-consequence comparison.
disable-model-invocation
true
# Kepner-Tregoe Analysis **Core rule:** Diagnose deviations by testing causes against both IS and IS-NOT. Compare consequential choices by screening MUSTs, weighting WANTs, and exposing adverse consequences before selecting. ## When to Use - A defect affects some objects, places, times, or cohorts but not comparable others. - Several candidate causes remain and the contrast boundary can discriminate them. - A consequential option choice has explicit non-negotiables, competing objectives, and risks that should be compared consistently. ## When NOT to Use - A uniform failure has no meaningful IS-NOT contrast, or the cause is already confirmed. - One cheap observation settles the cause or one option plainly dominates every requirement. - The criteria cannot be made operational; clarify them before assigning weights. - The task is forward failure discovery for a planned change rather than diagnosis or option selection. ## Procedure 1. **Choose the mode.** Use Problem Analysis for a deviation from expected behavior; use Decision Analysis for a choice among options. State the target and do not mix scores with causal evidence. 2. **Frame the target.** For a deviation, record object, defect, location, time, extent, and impact. For a choice, state the decision, alternatives, constraints, and deadline. 3. **Problem Analysis — build IS/IS-NOT.** For WHAT, WHERE, WHEN, and EXTENT, record IS, closest comparable IS-NOT, and the distinction unique to the IS side. List changes near the first occurrence. 4. **Problem Analysis — difference-test causes.** Generate candidates from distinctions and changes. A candidate survives only if it explains both IS and IS-NOT. Run the cheapest discriminating check; stop when one verified cause explains the full boundary. 5. **Decision Analysis — screen and score.** Define pass/fail MUSTs and weighted WANTs (1–10 importance) before scoring. Eliminate options that fail any MUST; score survivors against each WANT and calculate weighted totals using the same scale. 6. **Decision Analysis — test downside and sensitivity.** For leading options, list adverse consequences with probability × impact and identify assumptions or weight changes that would reverse the ranking. Do not let a high total conceal a ruinous failure mode. 7. **Decide or expose the gap.** Return the verified cause or highest-ranked acceptable option, the evidence/score behind it, residual risk, and next verification. If no cause verifies or no option passes MUSTs, return open/none rather than force a winner. ## Output Return one mode-specific decision artifact: - **Problem Analysis:** problem statement; IS/IS-NOT matrix with distinctions; nearby changes; candidate-vs-boundary tests; confirmed cause or next discriminating check. - **Decision Analysis:** decision statement; alternatives; MUST screen; weighted WANT matrix; adverse-consequence table; sensitivity/reversal conditions; selected option or none. ## Verification - **Falsify/stop:** reject a cause that cannot explain both sides of the boundary. Reject a choice if it fails a MUST, depends on inconsistent scoring, or loses under a plausible weight/risk change that was hidden. - **Over-application guard:** skip the full matrix for an obvious cause, trivial choice, or one-shot check. Stop when the cause verifies or the option is robust enough for the stated stakes; extra rows are ceremony.
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