docs-ticket-readiness

name	docs-ticket-readiness
description	Assess JIRA ticket readiness for the docs-orchestrator workflow. Checks description quality (via LLM), PR/source linkage, metadata completeness, and relationship context (2-level graph traversal). Outputs structured JSON verdict with actionable gaps. Use when you want to check if a JIRA ticket has enough information before starting a docs workflow.
model	claude-haiku-4-5@20251001
argument-hint	<ticket> [--jql <query>] [--output-dir <path>] [--max-results <n>] [--skip-description-check] [--comment]
allowed-tools	Read, Bash, Glob, Grep

Ticket Readiness Assessment

Standalone skill that evaluates whether a JIRA ticket has sufficient information for the docs-orchestrator workflow to succeed. Checks four dimensions and produces a structured verdict.

Parse arguments

• $1 — JIRA ticket key (e.g., PROJ-123). Mutually exclusive with --jql.
• --jql <query> — JQL query for batch mode. Mutually exclusive with positional ticket key.
• --output-dir <path> — Write per-ticket markdown reports to this directory.
• --max-results <n> — Max tickets for JQL mode (default: 10).
• --skip-description-check — Skip LLM description quality assessment (mechanical checks only).
• --comment — Post readiness verdict as a JIRA comment after assessment.
• --ready-statuses <list> — Comma-separated JIRA statuses considered docs-ready (default: Done, Closed, Resolved, In Review, Code Review, Release Pending).

Determine mode:

• If first arg looks like a JIRA key (matches ^[A-Z][A-Z0-9]+-\d+$): single ticket mode with --issue <key>.
• If --jql is present: batch mode.
• If neither: ask the user for a ticket key.

Step 1: Run mechanical checks

Run the readiness script to fetch JIRA data and perform Dimensions 2–4 (PR linkage, metadata, relationships):

uv run --script ${CLAUDE_SKILL_DIR}/scripts/ticket_readiness.py \
  --issue <TICKET_KEY> \
  --plugin-root ${CLAUDE_PLUGIN_ROOT} \
  [--ready-statuses <list>]

For batch mode:

uv run --script ${CLAUDE_SKILL_DIR}/scripts/ticket_readiness.py \
  --jql "<JQL_QUERY>" \
  --max-results <N> \
  --plugin-root ${CLAUDE_PLUGIN_ROOT} \
  [--ready-statuses <list>]

Capture the JSON output. If the output contains an "error" key at the top level, report the error to the user and STOP.

Step 1.5: PR relevance assessment

If PRs were discovered in Step 1 (i.e., dimensions.pr_source_linkage.checks.git_links_present.status is pass or warn), assess whether each PR is actually relevant to the JIRA ticket.

1. Collect all PR URLs from the Step 1 JSON. Look in:

   • dimensions.pr_source_linkage.checks.git_links_present.detail (parse PR URLs)
   • relationship_map.children[].pr entries
   • relationship_map.documented_by[].pr entries

2. For each unique PR URL, dispatch a subagent (using the Agent tool) in parallel (all Agent calls in one message). Each subagent should:

   a. Run the git PR reader to fetch PR info:

   uv run --script ${CLAUDE_PLUGIN_ROOT}/skills/git-pr-reader/scripts/git_pr_reader.py info <PR_URL>
   

   b. Compare the PR title and description against the JIRA ticket summary and description (from description_text in the Step 1 JSON).

   c. Return a single-line JSON verdict:

   {"url": "<PR_URL>", "relevant": true, "reason": "PR adds OpenClaw deployment manifests matching the ticket's scope"}
   

   or:

   {"url": "<PR_URL>", "relevant": false, "reason": "PR is a CI pipeline fix unrelated to the feature"}
   

3. Collect all subagent verdicts and merge into the output:

   • Add dimensions.pr_source_linkage.checks.pr_relevance with:
     • status: pass if all PRs relevant, if any irrelevant, if no PRs to check

Step 2: Description quality assessment (Dimension 1)

If --skip-description-check was passed, set description_quality to {"status": "skipped"} for all tickets and skip to Step 3.

Otherwise, for each ticket in the output where dimensions.description_quality is null:

1. Extract description_text from the JSON.
2. If description_text is empty or very short (under 20 characters), set:

   {"status": "fail", "score": 1, "gaps": ["Description is empty or a one-liner"]}
   

3. Otherwise, assess the description against this rubric:

Rubric for description quality assessment:

Signal	Weight	Pass	Warn	Fail
Specificity	High	Describes a concrete change/feature with technical detail	Vague but has some context	One-liner or empty
User impact	Medium	Explains what users need to know or do differently	Implied but not stated	No user-facing context
Acceptance criteria	Medium	Has explicit ACs or clear definition of done	Some criteria but informal	None present
Scope clarity	Low	Clear boundaries of what's in and out of scope	Partially bounded	Unbounded or ambiguous

Produce a verdict as JSON with this exact structure:

{"status": "pass|warn|fail", "score": 1-5, "gaps": ["gap description 1", "gap description 2"]}

Rules:

• Score 4-5 → status "pass"
• Score 3 → status "warn"
• Score 1-2 → status "fail"
• gaps should list specific, actionable gaps (e.g., "No acceptance criteria specified", "User impact not described"). Empty array if status is "pass".

4. Merge the verdict into the ticket's JSON under dimensions.description_quality.

Step 3: Compute overall verdict

For each ticket, compute overall_status from all four dimensions:

• ready — no fails in any dimension
• ready_with_warnings — no fails, but at least one warning
• not_ready — at least one fail in any dimension

Dimensions with status null, skipped, or info do not count toward the verdict.

Step 4: Post JIRA comment (if --comment)

If --comment was passed:

For batch mode (multiple tickets): First confirm with the user:

"This will post readiness comments to N JIRA tickets. Continue?"

If the user declines, skip comment posting.

Post comments: Pipe the final merged JSON (with description_quality filled in) into the script's --post-comment mode:

echo '<MERGED_JSON>' | uv run --script ${CLAUDE_SKILL_DIR}/scripts/ticket_readiness.py --post-comment

Report the comment posting results to the user.

Step 5: Write markdown reports (if --output-dir)

If --output-dir was passed, run the script with the output-dir flag. The script writes per-ticket markdown reports to <output-dir>/<TICKET>-readiness.md.

Alternatively, if the script was already run with --output-dir in Step 1, the reports are already written. Confirm the output path to the user.

Step 6: Present results

Single ticket — formatted summary:

## PROJ-123: Add widget API documentation

**Verdict: READY** (or READY WITH WARNINGS / NOT READY)

| Dimension | Status | Details |
|-----------|--------|---------|
| Description quality | PASS (4/5) | — |
| PR/source linkage | PASS | 2 PRs found (2/2 relevant) |
| Metadata | WARN | Release note type not set |
| Relationships | PASS | Parent: PROJ-100 (Epic) |

### Relationship Map
- Parent: PROJ-100 (Epic: Widget Platform)
  - PROJ-123 (Story: Add widget API documentation) ← this ticket
  - PROJ-458 (Story: Widget docs) — sibling
- Children:
  - PROJ-456 (Sub-task: Widget API endpoints) — PR: github.com/org/repo/pull/55
  - PROJ-457 (Sub-task: Widget UI components)
- Documented by:
  - PROJ-789 (Task: Update API reference) — PR: github.com/org/repo/pull/60

Batch — summary table:

## Readiness Assessment: N tickets

| Ticket | Summary | Verdict | Gaps |
|--------|---------|---------|------|
| PROJ-123 | Add widget API | READY | — |
| PROJ-456 | Fix auth bug | NOT READY | No PRs, missing fix version |
| PROJ-789 | Update config | READY (warnings) | Release note type not set |

**Summary:** 1 ready, 1 ready with warnings, 1 not ready

Remove description_text from the JSON before displaying — it is internal data used for agent assessment, not for the user.