Bounded Rationality
SkillSearchUse when search or investigation could run forever. Set an explicit good-enough threshold first, then stop at the first option that clears it.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Bounded Rationality skill
What this skill tells your AI
The instructions your AI receives, as published by tjboudreaux/cc-thinking-skills in skills/thinking-bounded-rationality/SKILL.md and read by ahel’s review.
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
- State decision and budget. Name the choice, residual tool/context/time budget, and reversibility.
- Set aspiration before searching. Write concrete pass/fail criteria for "good enough." Do not evaluate until the threshold is explicit.
- Search sequentially. Score options in encounter order against the threshold only. Skip full matrices unless step 1 marked high-stakes/irreversible.
- Stop at first adequate. When an option clears every criterion, select it immediately.
- 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.
- 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.
Signals
- GitHub stars
- 1k
- Forks
- 158
- Last commit
- Aug 2026
Advanced
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- Gateway key
thinking-bounded-rationality- Source
- github.com/tjboudreaux/cc-thinking-skills