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Prompt optimization

Skill shinpr/rashomon/plugins/rashomon/skills/prompt-optimization

Measure prompt and skill improvements with blind A/B comparison.

Install
npx -y skills add shinpr/rashomon --skill prompt-optimization

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Analyzes and optimizes prompts using BP-001~008 patterns and a gated 3-step flow. Use when "optimize this prompt", "review prompt quality", "analyze prompt issues", or creating/reviewing rashomon skill content.

SKILL.md

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Prompt Optimization Skill

Purpose

Improve prompts while preserving user intent.

Core Principles

  1. Procedural Gates: Complete analysis, optimization, and balance in order. Each phase has observable pass conditions that control the next transition.
  2. Intent Preservation: Record the original requirements before changing wording, structure, context, constraints, or examples.
  3. Necessary and Sufficient Context: Include the information needed for a decision, action, or verification result. Condense or omit information that does not affect one of them.
  4. Traceable Changes: Connect every change to a finding or project-specific source.
  5. Self-Contained Execution: Require no temporary artifacts or additional agents.

Required References

Load references at the phase where their rules become necessary:

PhaseConditionRequired reference
AnalysisEvery promptreferences/patterns.yaml
AnalysisTarget is a SKILL.md, agent, or skill referencereferences/skills.md
BalanceEvery promptreferences/execution-quality.yaml

Record the loaded path and covered rule IDs in the phase's reference_coverage. A phase passes only when its required references and rule coverage are present.

Output Mode

Select the output mode before analysis. An explicit output_mode of interactive or machine takes priority; for any other value, ask the caller to choose one. When it is absent, use Machine mode only if the caller explicitly requests the Machine Output Contract as the response format; otherwise use Interactive mode. Apply the same rule to human and LLM callers.

Keep output_mode outside the target prompt and analysis.original_prompt.

Pattern Detection

Evaluate every pattern and record issue, already_satisfied, or not_applicable.

PriorityIDPatternDecision goal
P1BP-001Negative InstructionsLead with the required behavior; retain explicit prohibitions for narrow irreversible boundaries
P1BP-002Vague InstructionsResolve an outcome-relevant ambiguity with the least-restrictive sufficient criterion
P1BP-003Missing Output FormatDefine the shape needed by the output consumer
P2BP-004Unstructured PromptMake priority and relationships visible when structure reduces ambiguity
P2BP-005Missing or Excess ContextSupply decision-sufficient context without distractors or duplication
P2BP-006Missing Procedural GatesSplit sequential work into steps with completion evidence
P3BP-007Unnecessary or Biased ExamplesUse examples only for non-obvious mappings, then control their bias
P3BP-008Missing Uncertainty HandlingDefine evidence, escalation, and stopping behavior for unresolved inputs

Gated 3-Step Flow

Maintain one complete phase-state object in the current invocation. Complete each phase and its gate before generating the next phase; use the transition table as the control rule. Serialize the object only in Machine mode.

Step 1: Analysis

  1. Load the analysis references required for the target type.
  2. Preserve the original prompt verbatim.
  3. Record the prompt's intended outcome and requirements that later phases must preserve.
  4. Evaluate BP-001 through BP-008. Record every distinct issue in findings with a unique finding_id, pattern, severity, location, and quoted evidence. A BP-002 finding represents one decision required by the intended outcome whose plausible interpretations would materially change correctness, requested scope, downstream usability, or verification.
  5. Record missing inputs under unresolved_inputs.

analysis_gate passes when:

  • all required analysis references are covered;
  • BP-001 through BP-008 each have one summary whose finding_ids match its findings;
  • every distinct issue has one finding with evidence, location, pattern, and severity;
  • preservation requirements are explicit; and
  • no unresolved input prevents a faithful optimization.

Step 2: Optimization

Start this step when analysis_gate.status is pass.

  1. Resolve every finding as applied or skipped with a reason. For BP-002, choose the least-restrictive clarification that supplies the required precision and base the reason on its precision contribution and constraint cost.
  2. Apply Structural and Context Addition changes that improve task execution.
  3. Consolidate redundant changes and preserve requirements recorded in Step 1.
  4. Produce the candidate optimized prompt.

optimization_gate passes when:

  • every finding has exactly one resolution;
  • every change traces to a finding or named project source;
  • all preservation requirements remain represented;
  • added constraints remove a real ambiguity or protect a real requirement; and
  • every applied BP-002 clarification identifies an observable precision contribution and preserves the valid solutions allowed by the original intent.

Step 3: Balance

Start this step when optimization_gate.status is pass.

  1. Load references/execution-quality.yaml.
  2. Evaluate intent preservation, decision sufficiency, information density, constraint necessity, and traceability.
  3. Apply balance adjustments and record each adjustment.
  4. Produce the final prompt and final status.

balance_gate passes when every applicable balance check has evidence and no blocking check remains. Use original_sufficient when the analysis found no beneficial change.

State Transitions

Gate resultRequired transition
passPopulate the next phase and its gate
blockedKeep later workflow phases and their gates null, set result.status to blocked, and format the result in the selected output mode
Final balance pass with changesSet result.status to optimized
Final balance pass without changesSet result.status to original_sufficient

Interactive Output Contract

Format the user-facing result by status:

  • For optimized, return ## Final Prompt with the optimized prompt, followed by ## Changes with one bullet per applied change and its reason.
  • For original_sufficient, return ## Final Prompt with the original prompt, followed by ## Changes stating that no beneficial change was found and the original is already sufficient.
  • For blocked, return only ## Required Input with one bullet per missing item needed to continue.

Machine Output Contract

In Machine mode, return exactly one valid JSON object in this key order. Populate phases sequentially; later phases remain null until their preceding gate passes.

{
  "analysis": {
    "original_prompt": "verbatim input",
    "target_type": "general_prompt | skill_content",
    "intended_outcome": "observable outcome",
    "reference_coverage": [{"path": "references/patterns.yaml", "rule_ids": ["BP-001", "BP-002", "BP-003", "BP-004", "BP-005", "BP-006", "BP-007", "BP-008"]}],
    "pattern_coverage": {
      "BP-001": {"status": "issue | already_satisfied | not_applicable", "finding_ids": ["F-001"], "evidence": ["summary evidence or applicability reason"]},
      "BP-002": {"status": "issue | already_satisfied | not_applicable", "finding_ids": ["F-002", "F-003"], "evidence": ["summary evidence or applicability reason"]},
      "BP-003": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]},
      "BP-004": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]},
      "BP-005": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]},
      "BP-006": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]},
      "BP-007": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]},
      "BP-008": {"status": "issue | already_satisfied | not_applicable", "finding_ids": [], "evidence": ["summary evidence or applicability reason"]}
    },
    "findings": [{"finding_id": "F-001", "pattern_id": "BP-001", "severity": "P1", "location": "section or line", "evidence": ["verbatim issue evidence"]}, {"finding_id": "F-002", "pattern_id": "BP-002", "severity": "P1", "location": "first vague instruction", "evidence": ["verbatim evidence"]}, {"finding_id": "F-003", "pattern_id": "BP-002", "severity": "P1", "location": "second vague instruction", "evidence": ["verbatim evidence"]}],
    "preservation_requirements": ["requirement"],
    "unresolved_inputs": []
  },
  "analysis_gate": {"status": "pass | blocked", "missing": []},
  "optimization": {"finding_resolutions": [{"finding_id": "F-001", "decision": "applied | skipped", "reason": "reason", "change": "change or null", "source": "finding | project path"}], "candidate_prompt": "optimized candidate"},
  "optimization_gate": {"status": "pass | blocked", "missing": []},
  "balance": {
    "reference_coverage": [{"path": "references/execution-quality.yaml", "rule_ids": ["intent_preservation", "decision_sufficiency", "information_density", "constraint_necessity", "traceability"]}],
    "checks": [
      {"check_id": "intent_preservation", "status": "pass | blocked", "evidence": "comparison evidence"},
      {"check_id": "decision_sufficiency", "status": "pass | blocked", "evidence": "execution evidence"},
      {"check_id": "information_density", "status": "pass | blocked", "evidence": "context evidence"},
      {"check_id": "constraint_necessity", "status": "pass | blocked", "evidence": "constraint trace"},
      {"check_id": "traceability", "status": "pass | blocked", "evidence": "finding or source mapping"}
    ],
    "adjustments": []
  },
  "balance_gate": {"status": "pass | blocked", "missing": []},
  "result": {"status": "optimized | original_sufficient | blocked", "final_prompt": "prompt or null"}
}

Field types are fixed: analysis and analysis_gate are objects; optimization fields become objects only after analysis passes; balance fields become objects only after optimization passes. Otherwise later phases are null. result.final_prompt is a string for optimized or original_sufficient, and null for blocked.

Example of an analysis-blocked transition:

{
  "analysis": {"original_prompt": "verbatim input", "target_type": "skill_content", "intended_outcome": "observable outcome", "reference_coverage": [], "pattern_coverage": {}, "findings": [], "preservation_requirements": [], "unresolved_inputs": ["required skill reference unavailable"]},
  "analysis_gate": {"status": "blocked", "missing": ["references/skills.md"]},
  "optimization": null,
  "optimization_gate": null,
  "balance": null,
  "balance_gate": null,
  "result": {"status": "blocked", "final_prompt": null}
}

Conditional Rules

BP-001: Negative Instructions

State the desired action or allowed state first. Preserve an explicit prohibition when the violation is an irreversible operational action, the caller cannot normally recover it, and a positive-only rewrite would blur the boundary. Pair the prohibition with the safe alternative and the condition that authorizes crossing the boundary.

BP-004: Structure

Add structure when the prompt contains multiple instructions, sequential dependencies, or implicit section boundaries. Preserve lightweight prose for a single clear action.

BP-005: Context

For each context item, identify the decision, action, or verification it controls. Add missing items that change one of those outcomes. Condense duplicated items and items with no downstream effect.

BP-006: Decomposition

Use ordered steps when the task has sequential dependencies or when an early result must be verified before later work. Give each step observable completion evidence and a next-state rule.

BP-007: Examples

Default to concise rules or consumer-required output shapes for generally known behavior. Add an example when it conveys a domain-, product-, or organization-specific mapping, a non-obvious exception, or a boundary that a rule cannot express. Connect every example to the ambiguity it removes and keep the smallest set that covers those ambiguities.

Code and Repository Tasks

When the target requires a code or repository change:

  • Treat source, tests, configuration, interfaces, and callers as project artifacts that can supply required decisions.
  • Derive compatibility and verification criteria from the repository's existing contracts and workflows.
  • Require evidence from the relevant established checks before claiming completion.

Improvement Classification

ClassificationDefinitionInterpretation
StructuralChanges to organization, criteria, gates, or output shapePrompt writing technique
Context AdditionProject-specific information added from a traceable sourceInformation advantage
ExpressiveDifferent phrasing with equivalent executable meaningNeutral
VarianceDifference without an attributable requirement or execution effectOriginal prompt sufficient

References

  • references/patterns.yaml - Detailed BP-001 through BP-008 decision rules
  • references/execution-quality.yaml - Balance checks and comparison criteria
  • references/skills.md - Skill-specific BP adaptations and progressive disclosure

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