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speckit-clarify

Clarify an existing feature specification before implementation planning. The skill prioritizes consequential gaps, asks focused questions one at a time, updates the specification with accepted answers, and summarizes unresolved decisions and recommended next steps.

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Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

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适用场景

  • Resolving unclear requirements before implementation planning
  • Defining error behavior and measurable completion criteria
  • Recording agreed answers directly in a specification

包含的文件(1)

  • SKILL.md11.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Speckit Clarify Skill

User Input

$ARGUMENTS

You MUST consider the user input before proceeding (if not empty).

Outline

Goal: Detect and reduce ambiguity or missing decision points in the active feature specification and record the clarifications directly in the spec file.

Note: This clarification workflow is expected to run (and be completed) BEFORE invoking /speckit.plan. If the user explicitly states they are skipping clarification (e.g., exploratory spike), you may proceed, but must warn that downstream rework risk increases.

Execution steps:

  1. Run .specify/scripts/powershell/check-prerequisites.ps1 -Json -PathsOnly from repo root once (combined --json --paths-only mode / -Json -PathsOnly). Parse minimal JSON payload fields:

    • FEATURE_DIR
    • FEATURE_SPEC
    • (Optionally capture IMPL_PLAN, TASKS for future chained flows.)
    • If JSON parsing fails, abort and instruct user to re-run /speckit.specify or verify feature branch environment.
    • For single quotes in args like "I'm Groot", use escape syntax: e.g 'I'''m Groot' (or double-quote if possible: "I'm Groot").
  2. Load the current spec file. Perform a structured ambiguity & coverage scan using this taxonomy. For each category, mark status: Clear / Partial / Missing. Produce an internal coverage map used for prioritization (do not output raw map unless no questions will be asked).

    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

    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 planning phase (note internally)
  3. Generate (internally) a prioritized queue of candidate clarification questions (maximum 5). Do NOT output them all at once. Apply these constraints:

    • Maximum of 10 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 (Impact * Uncertainty) heuristic.
  4. Sequential questioning loop (interactive):

    • Present EXACTLY ONE question at a time.

    • For multiple‑choice questions:

      • Analyze all options and determine the most suitable option based on:
        • Best practices for the project type
        • Common patterns in similar implementations
        • Risk reduction (security, performance, maintainability)
        • Alignment with any explicit project goals or constraints visible in the spec
      • Present your recommended option prominently at the top with clear reasoning (1-2 sentences explaining why this is the best choice).
      • Format as: **Recommended:** Option [X] - <reasoning>
      • Then render all options as a Markdown table:
      OptionDescription
      A<Option A description>
      B<Option B description>
      C<Option C description> (add D/E as needed up to 5)
      ShortProvide a different short answer (<=5 words) (Include only if free-form alternative is appropriate)
      • After the table, add: You can reply with the option letter (e.g., "A"), accept the recommendation by saying "yes" or "recommended", or provide your own short answer.
    • For short‑answer style (no meaningful discrete options):

      • Provide your suggested answer based on best practices and context.
      • Format as: **Suggested:** <your proposed answer> - <brief reasoning>
      • Then output: Format: Short answer (<=5 words). You can accept the suggestion by saying "yes" or "suggested", or provide your own answer.
    • After the user answers:

      • If the user replies with "yes", "recommended", or "suggested", use your previously stated recommendation/suggestion as the answer.
      • Otherwise, validate the answer maps to one option or fits the <=5 word constraint.
      • If ambiguous, ask for a quick disambiguation (count still belongs to same question; do not advance).
      • Once satisfactory, record it in working memory (do not yet write to disk) and move to the next queued question.
    • Stop asking further questions when:

      • All critical ambiguities resolved early (remaining queued items become unnecessary), OR
      • User signals completion ("done", "good", "no more"), OR
      • You reach 5 asked questions.
    • Never reveal future queued questions in advance.

    • If no valid questions exist at start, immediately report no critical ambiguities.

  5. Integration after EACH accepted answer (incremental update approach):

    • Maintain in-memory representation of the spec (loaded once at start) plus the raw file contents.
    • For the first integrated answer in this session:
      • Ensure a ## Clarifications section exists (create it just after the highest-level contextual/overview section per the spec template if missing).
      • Under it, create (if not present) a ### Session YYYY-MM-DD subheading for today.
    • Append a bullet line immediately after acceptance: - Q: <question> → A: <final answer>.
    • Then immediately apply the clarification to the most appropriate section(s):
      • Functional ambiguity → Update or add a bullet in Functional Requirements.
      • User interaction / actor distinction → Update User Stories or Actors subsection (if present) with clarified role, constraint, or scenario.
      • Data shape / entities → Update Data Model (add fields, types, relationships) preserving ordering; note added constraints succinctly.
      • Non-functional constraint → Add/modify measurable criteria in Non-Functional / Quality Attributes section (convert vague adjective to metric or explicit target).
      • Edge case / negative flow → Add a new bullet under Edge Cases / Error Handling (or create such subsection if template provides placeholder for it).
      • Terminology conflict → Normalize term across spec; retain original only if necessary by adding (formerly referred to as "X") once.
    • If the clarification invalidates an earlier ambiguous statement, replace that statement instead of duplicating; leave no obsolete contradictory text.
    • Save the spec file AFTER each integration to minimize risk of context loss (atomic overwrite).
    • Preserve formatting: do not reorder unrelated sections; keep heading hierarchy intact.
    • Keep each inserted clarification minimal and testable (avoid narrative drift).
  6. Validation (performed after EACH write plus final pass):

    • Clarifications session contains exactly one bullet per accepted answer (no duplicates).
    • Total asked (accepted) questions ≤ 5.
    • Updated sections contain no lingering vague placeholders the new answer was meant to resolve.
    • No contradictory earlier statement remains (scan for now-invalid alternative choices removed).
    • Markdown structure valid; only allowed new headings: ## Clarifications, ### Session YYYY-MM-DD.
    • Terminology consistency: same canonical term used across all updated sections.
  7. Write the updated spec back to FEATURE_SPEC.

  8. Report completion (after questioning loop ends or early termination):

    • Number of questions asked & answered.
    • Path to updated spec.
    • Sections touched (list names).
    • Coverage summary table listing each taxonomy category with Status: Resolved (was Partial/Missing and addressed), Deferred (exceeds question quota or better suited for planning), Clear (already sufficient), Outstanding (still Partial/Missing but low impact).
    • If any Outstanding or Deferred remain, recommend whether to proceed to /speckit.plan or run /speckit.clarify again later post-plan.
    • Suggested next command.

Behavior rules:

  • If no meaningful ambiguities found (or all potential questions would be low-impact), respond: "No critical ambiguities detected worth formal clarification." and suggest proceeding.
  • If spec file missing, instruct user to run /speckit.specify first (do not create a new spec here).
  • Never exceed 5 total asked questions (clarification retries for a single question do not count as new questions).
  • Avoid speculative tech stack questions unless the absence blocks functional clarity.
  • Respect user early termination signals ("stop", "done", "proceed").
  • If no questions asked due to full coverage, output a compact coverage summary (all categories Clear) then suggest advancing.
  • If quota reached with unresolved high-impact categories remaining, explicitly flag them under Deferred with rationale.

Context for prioritization: $ARGUMENTS

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