speckit.clarify

A clarification command that scans a project specification for missing or unclear details, including behavior, data, quality, and integration needs.

In plain words
What is it for?
Use it to review a specification, identify ambiguity, and ask focused questions about scope, users, data, security, and integrations.
Why use it?
It helps reveal important unanswered questions before development begins.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/github/spec-kit-copilot/speckit.clarify
Clone the repo
git clone --depth 1 https://github.com/github/spec-kit-copilot
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 385 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00385
Opus 5 $0.00000 $0.00192
Sonnet 5 $0.00000 $0.00077
Haiku 4.5 $0.00000 $0.00038

Measured 2d ago against content hash c8dd81993200, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

speckit.clarify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

spec-kit-presets/copilot-sub-agents/commands/speckit.clarify.md · 21 lines

What it actually says

Sub-Agent Delegation

When executing this command, delegate independent work to parallel sub-agents to reduce total execution time.

How to dispatch sub-agents in Copilot:

  • VS Code: Use the runSubagent tool to spawn each sub-agent in an isolated context.
  • CLI: Delegate to a sub-agent process — Copilot CLI automatically manages subsidiary sub-agent execution. You can also target custom agents defined in .github/agents/ or ~/.copilot/agents/.

Parallel Ambiguity Scan

When performing the structured ambiguity & coverage scan (step 2), dispatch independent scan categories as parallel sub-agents:

  1. Sub-agent: Functional & Domain scan — "Analyze the spec for ambiguity in: Functional Scope & Behavior (core goals, out-of-scope, user roles) and Domain & Data Model (entities, identity rules, state transitions, scale). Mark each category Clear/Partial/Missing. Return the coverage map and candidate questions."

  2. Sub-agent: Quality & Integration scan — "Analyze the spec for ambiguity in: Non-Functional Quality Attributes (performance, scalability, reliability, observability, security, compliance) and Integration & External Dependencies (external services, data formats, protocols). Mark each category Clear/Partial/Missing. Return the coverage map and candidate questions."

  3. Sub-agent: UX & Edge Cases scan — "Analyze the spec for ambiguity in: Interaction & UX Flow (user journeys, error/loading states, a11y), Edge Cases & Failure Handling (negative scenarios, rate limiting, conflicts), Constraints & Tradeoffs, Terminology & Consistency, and Completion Signals. Mark each category Clear/Partial/Missing. Return the coverage map and candidate questions."

Merge the coverage maps from all sub-agents and prioritize the combined candidate questions into the final queue of up to 5 questions.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 21 lines · 0 tokens per session scan A c8dd81993200

Subscribe to this mod's changes

speckit.clarify is a command published in the GitHub repository github/spec-kit-copilot (11 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 385 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.