clarify-ticket

name	clarify-ticket
description	Use when analyzing a ticket for ambiguities, missing information, or unclear acceptance criteria. Use when user says 'clarify ticket', 'review ticket', 'analyze ticket', or passes a ticket key.
argument-hint	[TICKET-KEY or URL]
allowed-tools	["Read","Grep","Glob","AskUserQuestion","ToolSearch"]

Step 0 — Load configuration

Read ${CLAUDE_PLUGIN_ROOT}/config.yaml. If it does not exist, tell the user to copy config.example.yaml to config.yaml and fill in their values. Stop here.

Extract:

• issue_tracker — determines which adapter to load (jira, linear, github-issues)

Step 1 — Load adapter

Read the adapter file at ${CLAUDE_PLUGIN_ROOT}/skills/clarify-ticket/adapters/{issue_tracker}.md. If the adapter does not exist, tell the user that {issue_tracker} is not yet supported and stop.

All tool-specific calls come from the adapter. Do not invent tool calls.

Step 2 — Parse argument

From $ARGUMENTS, extract the ticket key or URL:

1. If the argument is a URL, use the adapter's URL-parsing rule to extract the ticket key.
2. If the argument is a key (e.g. PROJ-123), use it directly.
3. If no argument was provided, ask the user for a ticket key.

Store the result as {key}.

Step 3 — Fetch ticket

Use the adapter's fetch ticket command to retrieve the full ticket for {key}.

Extract and store:

• title — the ticket summary
• description — the full body/description
• acceptance_criteria — if present in the description (look for "Criterios de aceptación", "Acceptance Criteria", "AC", or checklist sections)
• status — current status
• type — story, bug, task, sub-task, etc.
• assignee — who it is assigned to
• labels — any labels or tags
• linked_issues — any linked tickets (blocks, is blocked by, relates to)
• comments — all comments on the ticket

Step 4 — Detect open questions

Scan the description, acceptance criteria, and comments for:

1. Explicit questions — sentences ending in ? or starting with "Pregunta:", "Question:", "Duda:", "TBD", "Por definir"
2. Conditional language — "debería", "quizás", "posiblemente", "should", "maybe", "possibly", "could be", "se podría"
3. Undefined references — mentions of external documents, designs, or specs without links
4. Ambiguous pronouns — "esto", "eso", "aquello", "this", "that" without clear antecedents
5. Missing quantities or boundaries — "varios", "algunos", "many", "some", "etc.", "appropriate"

Step 5 — Analyze content

For each finding from Step 4, classify it:

• BLOCKER — Cannot start implementation without this answer. Examples: undefined business rules, missing API contract, unclear data model, no design link.
• NICE-TO-HAVE — Implementation can proceed but the answer would improve quality. Examples: edge case clarification, UX preference, performance target.

Step 6 — Check comments

Review all comments chronologically. Identify:

• Questions that were asked but never answered
• Answers that contradict the description
• Decisions made in comments that should be in the description
• Newer context that updates or overrides original requirements

Step 7 — Structural validations

Check the ticket for structural completeness:

1. Description present and non-empty — flag if missing or too short (< 50 chars)
2. Acceptance criteria present — flag if missing entirely
3. AC are testable — each criterion should be verifiable (not vague like "should work well")
4. Design link present — if the ticket references UI work, a design link should exist
5. Dependencies documented — if the ticket mentions other services or teams, linked issues should exist
6. Estimation present — flag if story points or estimate is missing
7. Assignee present — flag if unassigned
8. Type appropriate — flag if type does not match content (e.g., story without user-facing value, bug without reproduction steps)

Step 8 — Classify by audience

Group all findings by who can answer them:

• Product / PO — business rules, priorities, scope decisions
• Design / UX — visual behavior, states, interactions
• Tech Lead / Architecture — technical approach, data model, integrations
• QA — test scenarios, edge cases, environments
• DevOps / Infra — deployment, infrastructure, environments
• Other team — cross-team dependencies

Step 9 — Reformulate business blockers

For each BLOCKER finding, reformulate it as a clear, actionable question:

• Bad: "The description is vague about validation"
• Good: "What specific validation rules apply to the email field? (e.g., format, uniqueness, domain restriction)"

Each question must:

1. State what is unclear
2. Suggest possible answers or options when possible
3. Reference the specific part of the ticket that triggered it

Step 10 — Display results

Read the format reference at references/actions-and-format.md.

Present the analysis using the format defined in the reference file.

Structure:

1. Header — ticket key, title, status, type
2. Summary — one-paragraph assessment (healthy, needs minor clarification, has blockers)
3. Blockers — numbered list with audience tag
4. Nice-to-have — numbered list with audience tag
5. Structural issues — checklist of what passed and what failed
6. Unanswered questions from comments — if any
7. Contradictions — if any found between description and comments

Step 11 — Offer actions

Ask the user which action to take:

1. Add as comment — post the analysis as a comment on the ticket using the adapter's comment command
2. Edit ticket — update the ticket description to include the identified gaps using the adapter's edit command
3. Copy to clipboard — just display, no action
4. Refine and re-analyze — let the user provide additional context, then re-run from Step 4