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thinking-model-router

When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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SKILL.md(원문)

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Model Router

Core rule: Prefer NONE or one primary skill. Route by mechanism fit, not habit. Combine only when roles are distinct and necessary.

When to Use

  • The right thinking skill is unclear and you would otherwise guess or stack tools.
  • Several catalog skills seem plausible and you need a single primary (or explicit NONE).
  • High-stakes work where a wrong frame is costly and a quick domain×type match helps.

When NOT to Use

  • The match is already known or obvious ("where's the bottleneck?" → theory-of-constraints) — invoke that skill directly; do not route for show.
  • The task is routine implementation with no analytical unknown — reason directly (NONE).
  • You are mid-execution of an agreed plan and only need the next concrete step.
  • The ask is outside this catalog (pure coding syntax, tool ops with no judgment call) — NONE.

Invoking a Model (Skill IDs)

The router outputs bare slugs (e.g. id: five-whys-plus). Invoke a routed skill with the Skill tool using the exact ID thinking-skills:thinking-<slug> — never invent a slug not cited in Procedure. NONE means no invocation.

Procedure

  1. Short-circuit. If one skill clearly fits by mechanism, return that skill alone. If no skill clearly improves the work, return NONE and reason directly. Stop.
  2. Characterize. Record domain (coding, architecture, product, strategy, personal, abstract, risk, innovation) and problem type (diagnose, decide, understand, create, evaluate, predict, optimize). Note constraints: time, information, stakes, reversibility, complexity.
  3. Candidate by type defaults (override when constraints demand). Keep only active catalog skills:
    • Diagnose → five-whys-plus or scientific-method (kepner-tregoe if IS/IS-NOT matrix needed)
    • Decide → reversibility first; then opportunity-cost or probabilistic
    • Understand → systems (map-territory if model-vs-reality gap; cynefin if approach domain unclear)
    • Create → first-principles (triz for contradictions; effectuation for means-driven; via-negativa for remove-first)
    • Evaluate → steel-manning (socratic if assumptions/definitions are the unknown)
    • Predict → probabilistic
    • Optimize → theory-of-constraints (ooda under time pressure; bounded-rationality for search stop)
    • Risk / "what fails?" → pre-mortem or red-team; margin-of-safety for buffers
    • Product "what to build?" → jobs-to-be-done
    • Competence / durability → circle-of-competence, lindy-effect
    • Controlled hypothetical → thought-experiment
    • Multi-lens only after one primary fails a blind-spot check → model-combination
  4. Select with criteria (satisficing). Score only if 2+ candidates remain or stakes make a forced default unsafe. Rate each criterion 1–5 (1 = absent/wrong fit; 3 = usable with gaps; 5 = direct fit): problem fit (30%), available inputs (20%), time to apply (15%), stakeholder usability (15%), competence to apply correctly (20%). A route must score problem fit ≥4 and weighted total ≥3.5; otherwise return NONE. For totals within 0.25, prefer fewer inputs and shorter execution; if still tied, choose NONE unless the skills answer distinct complementary questions.
  5. Multi-skill only as exception. Add a second or third skill only when each has a distinct complementary role the primary leaves open. Cap at three. Prefer sequential over parallel. Near-neighbors and synonyms do not stack. For composition patterns, hand off to model-combination after naming the primary.
  6. Exit. State abandon signals (forced fit, ignored factors, no insight ~15 minutes). On mismatch, re-route once or fall back to NONE — never force a frame.

Domain cheat-map (primary first; still default to one or NONE):

Domain signalPrefer
Bug / root cause / flakyfive-whys-plus, scientific-method, systems
Architecture / tech choicereversibility, systems, lindy-effect, opportunity-cost
Feature / roadmap / engagementjobs-to-be-done, opportunity-cost, theory-of-constraints
Strategy / competition / growthcynefin, systems, red-team, second-order
Personal / career commitmentopportunity-cost, reversibility, circle-of-competence, pre-mortem
Argument / belief updatesteel-manning, probabilistic, socratic, first-principles
Security / disaster / ruinpre-mortem, red-team, margin-of-safety, via-negativa
Innovation / contradiction / simplifyfirst-principles, triz, effectuation, via-negativa

Output

outcome: NONE | one | multi
routes:
  - id: <primary skill id or NONE>
    role: <job this skill performs>
    unique_question: <question only this route answers>
  - id: <secondary skill id, only for multi>
    role: <distinct complementary job>
    unique_question: <distinct open question>
  - id: <tertiary skill id, only for multi>
    role: <distinct complementary job>
    unique_question: <distinct open question>
domain: <domain>
problem_type: <type>
constraints: <time/info/stakes/reversibility>
rationale: <mechanism fit in one sentence>
blind_spots: <what primary still ignores, if any>
exit: <when to abandon or re-route>

Default fill: outcome: NONE with one id: NONE route, or outcome: one with one route. Use multi only when every listed skill has a distinct role and unique question.

Verification

  • Falsify / stop: If the route is habit or familiarity rather than mechanism fit, discard and re-score or return NONE. If multi-skill entries lack distinct roles, collapse to the single best primary. If no candidate clearly helps, NONE is correct — do not invent a route.
  • Over-application guard: Do not route when the skill is already obvious. Do not return more than three skills. Do not cite deleted or non-catalog names. Do not treat the router as a prerequisite for leaf skills invoked directly.

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같은 저장소의 스킬

Use when search or investigation could run forever. Set an explicit good-enough threshold first, then stop at the first option that clears it.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

Use when a specific claim may lack grounding. Check evidence boundary, size wrongness cost, then answer, fetch, or abstain — never confabulate.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

When the right response mode is unclear, classify the cause-effect domain first; decompose disorder.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

When a constraint is treated as fixed, separate physics from convention, keep only independently supported primitives, and rebuild the simplest solution that satisfies real constraints.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tjboudreaux/cc-thinking-skills1.7천2026년 8월 8일 업데이트

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