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thinking-bounded-rationality

thinking-bounded-rationality

github.com/tjboudreauxAgent workflows1.7k571 installsUpdated 12w ago
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About thinking-bounded-rationality

A decision skill for agents working within limited time, context, and tool budgets. It sets a concrete acceptance threshold, then stops at the first option that meets it, while reserving exhaustive checks for high-stakes or correctness-critical decisions.

Key features

  1. 01Sets an explicit adequacy threshold
  2. 02Searches options sequentially
  3. 03Stops at the first adequate option
  4. 04Preserves criteria when search fails
  5. 05Excludes high-stakes and correctness gates

Use cases

  1. 01Choosing among suitable low-stakes options
  2. 02Limiting open-ended research
  3. 03Managing decisions within a fixed budget

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-bounded-rationality

After installing, type/thinking-bounded-rationalityin Claude Code to confirm it loaded.

Details

From the project README

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

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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