thinking-kepner-tregoe

Original：🇺🇸 English

Translated

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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Sourcetjboudreaux/cc-thinking-skills

Added on2026-08-14

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npx skill4agent add tjboudreaux/cc-thinking-skills thinking-kepner-tregoe

SKILL.md Content

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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

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.
Frame the target. For a deviation, record object, defect, location, time, extent, and impact. For a choice, state the decision, alternatives, constraints, and deadline.
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.
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.
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.
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.
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.