thinking-bounded-ratio…
Use when search or investigation could run forever. Set an explicit good-enough threshold first, then stop at the first option…
Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves.
Claude Code
$ npx -y skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation --agent claude-code
Codex
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a codex -y
Cursor
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a cursor -y
Gemini CLI
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a gemini-cli -y
GitHub Copilot
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a github-copilot -y
OpenCode
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a opencode -y
Windsurf
$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-effectuation -a windsurf -y
name: thinking-effectuation description: Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves. disable-model-invocation: true
Under Knightian uncertainty, start from available means and affordable loss—not a fixed goal and predicted return. Create the path through controllable action and real commitments.
1. **Inventory means only.** List who you are (skills, constraints, values), what you know (domain, tools, data), and who you know (reachable partners, users, resources). Reject "what would be needed for an ideal plan" as input. 2. **Cap affordable loss.** State the maximum time, money, reputation, and opportunity cost you can lose and still continue. If the proposed step exceeds any cap, redesign the step smaller or stop. 3. **Choose one controllable next action.** Prefer the smallest action that can yield either (a) a real commitment from someone else or (b) discriminating information. Act inside the loss cap; do not optimize expected return. 4. **Seek commitments, not opinions.** Share the working means-based offer. Anyone who commits resources, access, or work becomes a co-creator and may reshape the goal. Discard non-committing feedback as non-binding. 5. **Leverage contingencies.** Treat surprises as new means: failed hires, competitor moves, off-roadmap requests. Ask "how can this expand control?" not "how do we restore the old plan?" 6. **Update means and goal, then stop or loop.** Fold new means and commitments into the inventory; restate the emerging goal. Stop when a viable path is controlled enough to execute, the loss cap is exhausted without traction, or uncertainty collapses into a predictable plan (then switch to causal planning).
Emit an effectuation brief:
28 portable Agent Skills for structured reasoning in Claude Code, GitHub Copilot, Codex, Cursor, and other compatible tools Claude Code Thinking Skills is a public catalog of Agent Skills.
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