Structured clarification workflow for underspecified requirements.

Apache-2.0Auto-check passedDevelopment

Install Speckit Clarify

skills CLI
$ npx skills add foryourhealth111-pixel/Vibe-Skills --skill speckit-clarify -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install foryourhealth111-pixel/Vibe-Skills speckit-clarify --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/bundled/skills/speckit-clarify .claude/skills/speckit-clarify && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
speckit-clarify
GitHub stars
3.6k
Token cost
~2.9k tokens
SKILL.md length
1,345 words
Files
1
Skills in repo
81
Repo updated
First seen
Licence
Apache-2.0

At a glance

Structured clarification workflow for underspecified requirements.

  • Works in 8 steps: Run… → Load the current spec file. Perform a… → Generate (internally) a prioritized… → …
  • Tasks that involve Spec-driven development
  • SKILL.md covers User Input and Outline
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Speckit Clarify is an agent skill from foryourhealth111-pixel/Vibe-Skills. Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires spec-kit project structure with .specify/ directory

It sits in Development, covering Spec-driven development. The repository describes itself as: Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Spec-driven development

Example prompts

  • “/speckit-clarify”

Requirements

  • Compatibility (from SKILL.md): Requires spec-kit project structure with .specify/ directory

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Run .specify/scripts/powershell/check-prerequisites.ps1 -Json -PathsOnly from repo root once (combined --json --paths-only mode / -Json…
  2. Load the current spec file. Perform a structured ambiguity & coverage scan using this taxonomy. For each category, mark status: Clear /…
  3. Generate (internally) a prioritized queue of candidate clarification questions (maximum 5). Do NOT output them all at once. Apply these…
  4. Sequential questioning loop (interactive)
  5. Integration after EACH accepted answer (incremental update approach)
  6. Validation (performed after EACH write plus final pass)
  7. Write the updated spec back to FEATURE_SPEC.
  8. Report completion (after questioning loop ends or early termination)

What it can do on your machine

Read from SKILL.md and the folder at commit ddcaa2a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires spec-kit project structure with .specify/ directory

    From compatibility in the SKILL.md frontmatter.

Context cost

Speckit Clarify loads about 2.9k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 1,345 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from foryourhealth111-pixel/Vibe-Skills at commit ddcaa2a, republished under its Apache-2.0 licence (© foryourhealth111-pixel). 1,345 words, ~2,856 tokens.

Download SKILL.mdSave it as .claude/skills/speckit-clarify/SKILL.md (or your agent's skills folder).
name
speckit-clarify
description
Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.
compatibility
Requires spec-kit project structure with .specify/ directory
metadata.author
github-spec-kit
metadata.source
templates/commands/clarify.md

Speckit Clarify Skill

User Input

text
$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.
Show full SKILL.md (117 more words)Show less

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

© foryourhealth111-pixel, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in bundled/skills/speckit-clarify of foryourhealth111-pixel/Vibe-Skills.

Open the folder on GitHubat commit ddcaa2a

Compare with similar skills

Speckit Clarify next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Speckit Clarify compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Speckit Clarify this skillforyourhealth111-pixel/Vibe-Skills3.6k—~2.9kAutomated safety check: PassApache-2.0
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Speckit ConstitutionWeihanLi/WeihanLi.Common24212 repos~2.1kAutomated safety check: PassApache-2.0
Speckit Plankunstmusik/blue15419 repos~2.1kAutomated safety check: PassGPL-3.0
Speckit Specifykunstmusik/blue15419 repos~4.7kAutomated safety check: PassGPL-3.0
Review Spdzhu1090093659/spec_driven_develop987—~1.5kAutomated safety check: PassMIT

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Categories

Questions about Speckit Clarify

What does Speckit Clarify do?

Structured clarification workflow for underspecified requirements. Speckit Clarify is an agent skill from foryourhealth111-pixel/Vibe-Skills. Structured clarification workflow for underspecified requirements.

When should I use Speckit Clarify?

Speckit Clarify fits situations like: tasks that involve Spec-driven development.

How do I install Speckit Clarify in Claude Code?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill speckit-clarify -a claude-code`. Or copy the skill folder (bundled/skills/speckit-clarify in foryourhealth111-pixel/Vibe-Skills) into .claude/skills/speckit-clarify in your project. Claude Code loads it when a task matches its description.

How do I install Speckit Clarify in Codex?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill speckit-clarify -a codex`. Or copy the skill folder (bundled/skills/speckit-clarify in foryourhealth111-pixel/Vibe-Skills) into .agents/skills/speckit-clarify in your project. Codex loads it when a task matches its description.

Can I use Speckit Clarify in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill speckit-clarify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/speckit-clarify, .gemini/skills/speckit-clarify, .github/skills/speckit-clarify and .opencode/skills/speckit-clarify in your project.

What does Speckit Clarify need to run?

SKILL.md names no scripts, command-line tools or credentials: Speckit Clarify is instructions for the agent only. Compatibility (from SKILL.md): Requires spec-kit project structure with .specify/ directory.

Does Speckit Clarify access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Speckit Clarify safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Speckit Clarify use?

Speckit Clarify is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Speckit Clarify use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Speckit Clarify?

Skills that share tags, products or a category with Speckit Clarify: OpenSpec Bulk Change Archiver (Fission-AI/OpenSpec, 72k stars), Speckit Constitution (WeihanLi/WeihanLi.Common, 242 stars), Speckit Plan (kunstmusik/blue, 154 stars) and Speckit Specify (kunstmusik/blue, 154 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Speckit Clarify?

foryourhealth111-pixel (a GitHub user) maintains it in foryourhealth111-pixel/Vibe-Skills, which has 3,627 GitHub stars. The repository holds 81 skills in this directory. The repository was last updated on August 31, 2026.

Source: foryourhealth111-pixel/Vibe-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.