Agent skill

refining-specifications

Improves specification quality through completeness checks, clarity verification, and structured feedback. Use when specifications lack detail, have ambiguities, or need quality improvement.

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Install this agent skill to your Project

npx add-skill https://github.com/bacchus-labs/wrangler/tree/main/skills/refining-specifications

SKILL.md

Refining Specifications

Execution Steps

  1. Load the current spec file
  2. Perform structured ambiguity & coverage scan using taxonomy below
  3. For each category, mark status: Clear / Partial / Missing
  4. Produce internal coverage map used for prioritization (do not output raw map unless no questions will be asked)

Taxonomy for Ambiguity & Coverage Scan

Functional Scope & Behavior

  • Core user goals & success criteria
  • Explicit out-of-scope declarations
  • User roles / personas differentiation

Domain & Data Model

  • Entities, attributes, relationships
  • Identity & uniqueness rules
  • Lifecycle/state transitions
  • Data volume / scale assumptions

Interaction & UX Flow

  • Critical user journeys / sequences
  • Error/empty/loading states
  • Accessibility or localization notes

Non-Functional Quality Attributes

  • Performance (latency, throughput targets)
  • Scalability (horizontal/vertical, limits)
  • Reliability & availability (uptime, recovery expectations)
  • Observability (logging, metrics, tracing signals)
  • Security & privacy (authN/Z, data protection, threat assumptions)
  • Compliance / regulatory constraints (if any)

Integration & External Dependencies

  • External services/APIs and failure modes
  • Data import/export formats
  • Protocol/versioning assumptions

Edge Cases & Failure Handling

  • Negative scenarios
  • Rate limiting / throttling
  • Conflict resolution (e.g., concurrent edits)

Constraints & Tradeoffs

  • Technical constraints (language, storage, hosting)
  • Explicit tradeoffs or rejected alternatives

Terminology & Consistency

  • Canonical glossary terms
  • Avoided synonyms / deprecated terms

Completion Signals

  • Acceptance criteria testability
  • Measurable Definition of Done style indicators

Misc / Placeholders

  • TODO markers / unresolved decisions
  • Ambiguous adjectives ("robust", "intuitive") lacking quantification

Question Generation Guidelines

For each category with Partial or Missing status, add a candidate question opportunity unless:

  • Clarification would not materially change implementation or validation strategy
  • Information is better deferred to the planning phase (note internally)

Question Prioritization

Generate (internally) a prioritized queue of candidate clarification questions (maximum 5). Apply these constraints:

  • Maximum of 5 total questions across the whole session
  • Each question must be answerable with EITHER:
    • A short multiple-choice selection (2–5 distinct, mutually exclusive options), OR
    • A one-word / short-phrase answer (explicitly constrain: "Answer in <=5 words")
  • Only include questions whose answers materially impact architecture, data modeling, task decomposition, test design, UX behavior, operational readiness, or compliance validation
  • Ensure category coverage balance: attempt to cover the highest impact unresolved categories first; avoid asking two low-impact questions when a single high-impact area (e.g., security posture) is unresolved
  • Exclude questions already answered, trivial stylistic preferences, or plan-level execution details (unless blocking correctness)
  • Favor clarifications that reduce downstream rework risk or prevent misaligned acceptance tests
  • If more than 5 categories remain unresolved, select the top 5 by an Impact × Uncertainty heuristic

Output Format

Add your questions to a new section at the bottom of the spec titled "Open Questions for Clarification".

Update the specification file with:

markdown
## Open Questions for Clarification

### Question 1: [Category - Brief Topic]
**Question**: [Clear, specific question]
**Options** (if multiple choice):
- A: [Option description]
- B: [Option description]
- C: [Option description]

**Impact**: [Why this matters for implementation]

---

### Question 2: [Category - Brief Topic]
**Question**: [Clear, specific question (answer in <=5 words)]

**Impact**: [Why this matters]

---

[... up to 5 questions total]

Integration with Workflow

Natural Progression

  1. writing-specifications - Create initial spec
  2. refining-specifications - Detect and resolve ambiguity
  3. writing-plans - Create detailed implementation plan
  4. Execute implementation

When to Use

After spec creation: Run refinement to catch gaps before planning Before implementation: Ensure all decisions are clear After feedback: Incorporate stakeholder input and re-check for gaps

Use Cases

Ambiguous Requirements

User: "Review the auth spec for gaps" You: Scan taxonomy, identify missing error handling approach, unclear session timeout, ambiguous "secure" requirement, generate 3-5 questions

Pre-Planning Review

User: "Is this spec ready for planning?" You: Check completeness across taxonomy, identify missing acceptance criteria, unclear performance requirements, add questions section

Post-Feedback Refinement

User: "We got feedback on the spec, check for new gaps" You: Re-scan with new information, identify areas still ambiguous, prioritize remaining questions

Quality Criteria

A good refinement session:

✅ Identifies genuine ambiguities that would cause implementation confusion ✅ Asks questions that materially impact design decisions ✅ Prioritizes high-impact uncertainties ✅ Limits questions to 5 most critical ✅ Makes questions easy to answer (multiple choice or short phrase) ✅ Focuses on what can't be deferred to planning phase

Related Skills

  • writing-specifications - Create specifications (use before refinement)
  • validating-roadmaps - Check consistency across multiple specs (use for projects with many specs)
  • writing-plans - Create implementation plans (use after refinement)

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