tjboudreaux/cc-thinking-skills

thinking-bounded-rationality

Use when search or investigation could run forever.

Ver código-fonte

Como usar

  1. Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
  2. Consulte no original as ferramentas, credenciais e ambientes necessários.
  3. Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-bounded-rationality

Antes de começar

  • A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
  • Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill

Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.

Bounded Rationality

Under finite tool, context, and time budgets, stop at the first option that meets a predeclared aspiration level. Optimize only when the good-to-best gap is worth the remaining budget.

When to Use

  • Search or option comparison has no natural endpoint and could consume the turn budget.
  • Multiple options would clear the requirement and further comparison has diminishing returns.
  • The decision is reversible or low-stakes relative to more search.
  • You are gathering context beyond what the decision needs to ship.

When NOT to Use

  • Irreversible or high-stakes choices (data loss, security, migrations, public commitments) where the good-to-best gap is material.
  • Correctness gates: tests, security checks, and "did the fix work?" need the right answer, not a sufficient-looking one.
  • One cheap lookup would settle the fact — do it; do not satisfice past it.
  • The aspiration level cannot be stated — clarify the requirement first.

Procedure

  1. State decision and budget. Name the choice, residual tool/context/time budget, and reversibility.
  2. Set aspiration before searching. Write concrete pass/fail criteria for "good enough." Do not evaluate until the threshold is explicit.
  3. Search sequentially. Score options in encounter order against the threshold only. Skip full matrices unless step 1 marked high-stakes/irreversible.
  4. Stop at first adequate. When an option clears every criterion, select it immediately.
  5. Handle search failure without moving the goalposts. If nothing clears after the pre-set cap, preserve the threshold and report no adequate option. Relax only a criterion predeclared as non-load-bearing, record the relaxation, and resume within a new cap; never raise the bar after failure.
  6. Commit. Record choice and residual uncertainty; spend remaining budget on execution, not re-ranking.

Stop condition: First option meets the predeclared aspiration level, or the search cap is exhausted with none adequate.

Output

text
Decision: <choice>
Aspiration: <pass/fail criteria>
Search: evaluated N; stopped at first adequate | cap exhausted
Selected: <option or none>
Residual risk: <what further search might change>
Next spend: <execution step>

Verification

  • Falsify if you kept comparing after an option cleared the threshold, or invented the threshold after seeing winners.
  • Falsify if a correctness gate or irreversible decision was treated as satisficeable.
  • Over-application guard: if one cheap check settles a fact, look it up — do not invoke this skill.
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