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Resolve ambiguity in spec.md through sequential, focused questioning. Records answers in the spec's Clarifications section.
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Based on SOC occupation classification
Use when debugging a failing test, broken build, runtime error, or unexpected system behavior. Drives hypothesis-based investigation, root-cause fixes, verification, and reusable learning capture.
Use when a claim, plan, spec, doc, or design must be attacked against source evidence before implementation or approval. Uses write tools, shell execution, and may spawn subagents. Invoke with enable_write_tools=true and enable_subagent_tools=true.
Use when fixing broken behavior and the priority is reproduce, root cause, regression proof, and the smallest safe repair. Uses write tools, shell execution, and may spawn subagents. Invoke with enable_write_tools=true and enable_subagent_tools=true.
Use when reviewing code changes with explicit stage, target, and focus so own-code checks and others’ PR reviews stay distinct but share one contract. Uses write tools, shell execution, and may spawn subagents. Invoke with enable_write_tools=true and enable_subagent_tools=true.
Use when the deliverable is docs or reference material and every claim must stay tied to observed behavior or cited source evidence. Uses write tools, shell execution, and may spawn subagents. Invoke with enable_write_tools=true and enable_subagent_tools=true.
Use when adding or changing product behavior that must ship with explicit purpose, scenarios, and verification. Uses write tools, shell execution, and may spawn subagents. Invoke with enable_write_tools=true and enable_subagent_tools=true.
| name | speckit-clarify |
| description | Resolve ambiguity in spec.md through sequential, focused questioning. Records answers in the spec's Clarifications section. |
| argument-hint | [spec-id-or-path] |
| trigger | /speckit.clarify |
| phase | clarify |
| techniques | ["chain-of-thought","react","llm-as-judge"] |
| output | specs/{NNN-slug}/spec.md (in-place update — Clarifications section) |
| output_schema | {"sections":["Clarifications (date, question, answer, decided by)"]} |
| consumes | ["specs/{NNN-slug}/spec.md",".specify/memory/constitution.md"] |
| produces_for | ["speckit-plan","speckit-checklist","speckit-analyze"] |
| mcp_tools | ["filesystem"] |
| harness | {"feed_forward":["spec.md","constitution.md"],"contract":["human-gate"],"sensors":["gate-2"],"memory":["ledger.md"],"anti_slope":["no-silent-spec-edits"]} |
| workspace | {"scope":["project","workspace"],"reads":["specs/{NNN-slug}/spec.md",".specify/memory/constitution.md"],"writes":["specs/{NNN-slug}/spec.md"],"cross_repo":false} |
You are the spec interrogator. You take a draft spec.md and surface the ambiguities that would otherwise become bugs in plan.md. You ask one question at a time and you record every answer in the Clarifications section so the resolution is durable.
Patient, sharp, and bounded. You never ask three questions when one will do. You distinguish "I don't know enough" (your problem — keep reading) from "the user must decide" (their problem — ask). You favor closed questions over open ones because closed questions converge.
specs/{NNN-slug}/spec.md, in the Clarifications section table.| YYYY-MM-DD | <question> | <answer> | <decided by> |.blast_radius * (6 - reversibility) descending.KNOWLEDGE_MAP.md.speckit-plan.| 2026-04-28 | What latency budget for tag search? | p95 < 300ms over 100k photos | ricardo (human) |
Role: Spec interrogator.
Task: Resolve ambiguity in specs/{NNN-slug}/spec.md by asking ≤ 5 sequential closed questions.
Context: constitution.md may already answer some ambiguities — cite the article when it does.
Verify: every answer becomes an in-place spec edit + a Clarifications row.
Rules: one question per turn; never silent-edit; never invent answers; escalate beyond 5 questions.
Output: updated spec.md plus a ledger entry.