| name | prompt-refinement |
| description | This skill should be used when the user provides a vague request, asks to clarify requirements, structure a task, or refine a prompt for multi-agent orchestration. |
Prompt Refinement
Overview
Prompt refinement transforms ambiguous or incomplete user requests into clear, structured task specifications suitable for multi-agent orchestration. This skill bridges natural language input and the precise specifications required by downstream agents.
Purpose
Ensure tasks entering the orchestration pipeline have:
- Clear Objectives: A single, well-defined goal that can be verified
- Actionable Steps: Concrete actions that agents can execute
- Measurable Outcomes: Success criteria that verification agents can check
- Appropriate Scope: Boundaries that prevent scope creep
When to Use This Skill
Apply prompt refinement when:
- User input contains ambiguous terms ("fix it", "make it better")
- The request lacks specific targets (files, components, systems)
- Multiple interpretations of the request are possible
- Pre-processing is required for
/orchestrate or /plan commands
Key Principles
- Ask First, Act Second: When genuinely ambiguous, clarify before proceeding
- One Question at a Time: Never overwhelm users with multiple clarification requests
- Provide Options: Give concrete choices to speed up clarification
- Default Gracefully: Make reasonable assumptions when users don't respond
- Preserve Intent: Refinement should clarify, not change the user's goal
Refinement Template
Standard Format
**Goal**: <one-sentence objective stating what will be accomplished>
**Description**: <2-3 sentences providing context and scope>
**Actions**:
1. <specific, atomic action with clear target>
2. <specific, atomic action with clear target>
3. ...
**Constraints**: <what must not be broken, changed, or violated>
**Assumptions**: <what is taken for granted — surfaces risks early>
Template Guidelines
| Field | Requirements | Example |
|---|
| Goal | Single sentence, verb-first, specific outcome | "Implement rate limiting on /api/users endpoint" |
| Description | Context, scope boundaries | "Add rate limiting to prevent API abuse. Limit to 100 req/min per IP." |
| Actions | Numbered, ordered, atomic steps | "1. Explore existing middleware patterns" |
| Constraints | Non-negotiable requirements; what must stay intact | "Must not alter existing auth cookie format" |
| Assumptions | Preconditions taken for granted | "Redis is already provisioned" |
After capturing all five fields, the orchestrator classifies task_complexity (trivial/exploratory/implementation/complex/research) and persists the structured intent to the state file via --set-intent-goal, --set-intent-description, --set-intent-actions, --set-intent-constraints, --set-intent-assumptions, and --set-task-complexity. These values are passed verbatim (no re-summarization) to all downstream agents.
Action Step Pattern
- Explore: Investigate existing code, patterns, dependencies
- Plan: Design approach based on exploration
- Implement: Execute the core changes
- Test: Add or update tests
- Verify: Confirm implementation meets requirements
Ambiguity Detection
Quick Detection Checklist
A prompt likely needs clarification if:
Ambiguity Signals
| Signal | Example | Issue |
|---|
| Missing scope | "fix the bug" | Which bug? Where? |
| Vague outcome | "make it better" | Better how? |
| Multiple meanings | "update the API" | Which endpoint? What change? |
| Implicit assumptions | "deploy it" | Where? How? |
For detailed ambiguity detection, see references/ambiguity-detection.md.
Clarification Strategy
Question Format
Before I proceed, I need to clarify:
<single focused question>
Options:
A) <most likely option>
B) <second most likely>
C) <third option if applicable>
D) Something else (please specify)
Clarification Rules
| Rule | Rationale |
|---|
| Single question | Reduces cognitive load |
| Concrete options | Speeds up response |
| Max two rounds | Avoids frustration |
| Include escape hatch | Prevents forced incorrect choice |
When to Clarify vs. Assume
Always Clarify:
- Could cause data loss
- Affects security
- Mutually exclusive interpretations
- Production system impact
Safe to Assume:
- Obvious default exists
- Context suggests intent
- Low-risk, reversible operations
For detailed clarification strategies, see references/clarification-strategies.md.
Orchestration Detection
Prompts Requiring Orchestration
| Category | Example |
|---|
| Multi-file changes | "Add authentication to all routes" |
| Feature implementations | "Implement dark mode" |
| Bug investigation | "Fix the login issue" |
| Refactoring | "Refactor user service" |
| Integration | "Integrate Stripe" |
Pass-Through Prompts
| Category | Example |
|---|
| Questions | "What does this function do?" |
| Single-file edits | "Add comment to line 42" |
| Git operations | "Commit these changes" |
| Documentation lookups | "Show API endpoints" |
Quick Decision
Is it a question about existing code? -> Pass through
Does it require code changes? -> If no, pass through
Is target explicit AND single file? -> Pass through
Otherwise -> Refine for orchestration
For detailed orchestration detection, see references/orchestration-detection.md.
Refinement Process
Step 1: Classify Prompt
Is it orchestration-related?
├── NO -> Pass through unchanged
└── YES -> Continue to Step 2
Step 2: Detect Ambiguity
Check ambiguity signals
├── High ambiguity -> Go to Step 3 (Clarify)
└── Low ambiguity -> Go to Step 4 (Refine)
Step 3: Request Clarification
- Identify primary ambiguity
- Formulate single focused question
- Provide 3-4 concrete options
- Wait for response (max 2 rounds)
Step 4: Apply Template
- Extract Goal (single sentence, specific)
- Build Description (context, scope, constraints)
- Decompose Actions (atomic, ordered steps)
- Validate completeness
Quick Reference
Ambiguity Score Quick Guide
| Score | Action |
|---|
| 0-2 | Proceed with refinement |
| 3-4 | State assumption and proceed |
| 5+ | Ask clarifying question |
Short imperative with a concrete target → state assumption and proceed, do not ask.
Refinement Decision Matrix
| Prompt Type | Action |
|---|
| Clear + orchestration | Refine to template |
| Ambiguous + orchestration | Clarify then refine |
| Clear + non-orchestration | Pass through |
| Ambiguous + non-orchestration | Minimal clarification |
Additional Resources
Reference Files
Examples
Related Skills
- task-classification: Receives refined prompts for complexity assessment
- agent-behavior-constraints: Ensures refinement stays within agent boundaries
- verification-gates: Uses refined specifications for verification criteria