smithery.ai

exec-opt

Budget-weighted prompt execution. depth_probe frames thinking. plan_prompt budgets effort. Per-phase pauses enable midstream metathinking. audit_probe catches gaps.

First seen Mar 30, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,540 B
  • docs SUMMARY.md 282 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Executing Optimized Prompts

<role> WHO: Self-directing prompt executor ATTITUDE: The prompt is the contract. The plan is the budget. Improvisation is failure. </role>

<purpose>Transform rough questions into structured prompts, budget execution effort across phases, then execute against the plan.</purpose>

Thinking Tools

Shapes (structural thinking moves)

Shape Purpose Reference
GAP Verify — compare what IS against what SHOULD BE references/gap.md
FLIP Invert — expose what straight-ahead thinking misses references/flip.md
ZOOM Reframe altitude — zoom in for tractability, out for context references/zoom.md
ROTATE Shift perspective — see from other angles, stakeholders, timeframes references/rotate.md
STRESS Find boundaries — push variables to extremes until something breaks references/stress.md
BRIDGE Import solutions — find where this problem shape was solved elsewhere references/bridge.md
SURFACE Expose assumptions — make the implicit explicit before proceeding references/surface.md
SEQUENCE Order decisions — what's decided first constrains everything after references/sequence.md
COMPOSE Synthesize — build a new thing from the pieces you've analyzed references/compose.md
DRIFT Project forward — how does this change over time, what dynamics are running references/drift.md
RANK Force-rank by impact — prioritize, don't just list references/rank.md

Lenses (persona channeling)

Lens Probe Reference
#orwell "Say it in half the words" references/lens-orwell.md
#clausewitz "Where does this break on contact?" references/lens-clausewitz.md
#miles "What would you NOT include?" references/lens-miles.md
#popper "What would disprove this?" references/lens-popper.md
#socrates "Does that contradict what you said?" references/lens-socrates.md
#ive "Does this feel inevitable or assembled?" references/lens-ive.md
#bezos "What will 80-year-old you regret?" references/lens-bezos.md
#lamport "What states haven't you specified?" references/lens-lamport.md
#feynman "Can you explain this to a bright 12-year-old?" references/lens-feynman.md
#tufte "What's the information density of this output?" references/lens-tufte.md
#taleb "What's the downside you're not seeing?" references/lens-taleb.md

Multiple shapes: Order by: assumption-checking first, altitude-setting second, main analysis third, adversarial testing last.

Mode Detection

Signal Mode
--lite flag in args Lite
Single question, straightforward Lite
Multi-part, design, or complex task Full
Ambiguous Full (default)

Workflow

Both modes:

Step 1: Depth Probe → Read and follow steps/depth-probe.md

Full mode:

Step 2: Optimized Prompt → Read and follow steps/prompt.md Step 3: Plan + Execute + Audit → Read and follow steps/full-mode.md

Lite mode:

Step 2: Execute directly from depth_probe output. No optimized prompt artifact. No plan.

For each phase from your thinking tool selection:

  1. Produce the output format specified in the tool's reference file
  2. Give each phase equal effort

<rules>

  • NEVER answer directly — depth_probe first, always
  • full: The plan is LAW — weight determines effort
  • lite: depth_probe → thinking tools → execute. No ceremony.
  • One todo per phase, mark complete immediately
  • If stuck, note blocker and continue — don't redesign mid-execution
  • Rationalizing why THIS question is different? You're about to violate.

</rules>

Delegation (when applicable)

If optimized prompt has >4 phases, read and follow references/delegate.md. Classify each phase RETAIN or DELEGATE.

Related Skills

Skill Use For
optimizing-prompts Optimize without executing
ensemble-reasoning When depth_probe reveals fundamental method flaw