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opendatahub-ioopendatahub-io/docs-skills/skills/docs-ticket-readiness/SKILL.md

docs-ticket-readiness

Skill4 starsChanged 4 months agoApache-2.0View on GitHub

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.

The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 3 are distinctive, and 9 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 9

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If first arg looks like a JIRA key (matches ^[A-Z][A-Z0-9]+-\d+$): single ticket mode with --issue <key>.

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  2. Very specific:

    If --jql is present: batch mode.

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  3. Distinctive:

    If neither: ask the user for a ticket key.

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  4. Distinctive:

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

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  5. Very specific:

    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 …

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  6. Very specific:

    If a subagent fails (e.g., PR is private or token missing), set that PR's verdict to {"url": "...", "relevant": null, "reason": "Could not …

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  7. Very specific:

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

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  8. Very specific:

    If description_text is empty or very short (under 20 characters), set:

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  9. Very specific:

    If --comment was passed:

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  10. Distinctive:

    If the user declines, skip comment posting.

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  11. Very specific:

    If --output-dir was passed, run the script with the output-dir flag.

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  12. Very specific:

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

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≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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, warn if any irrelevant, info if no PRs to check
      • detail: summary (e.g., "2/2 PRs relevant" or "1/3 PRs irrelevant: github.com/org/repo/pull/99")
      • verdicts: array of the per-PR verdict objects
  4. If a subagent fails (e.g., PR is private or token missing), set that PR's verdict to {"url": "...", "relevant": null, "reason": "Could not fetch PR info"} and do not count it toward pass/warn.

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:

SignalWeightPassWarnFail
SpecificityHighDescribes a concrete change/feature with technical detailVague but has some contextOne-liner or empty
User impactMediumExplains what users need to know or do differentlyImplied but not statedNo user-facing context
Acceptance criteriaMediumHas explicit ACs or clear definition of doneSome criteria but informalNone present
Scope clarityLowClear boundaries of what's in and out of scopePartially boundedUnbounded 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".
  1. 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.

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