version: "1.0.0" name: headless-enrich-ticket description: > Headless ticket enrichment that gathers organizational context and attaches findings to an issue before work begins. Use when an agent should autonomously enrich a Jira, Linear, GitHub, or any issue tracker ticket with related PRs, code paths, historical context, and prior attempts. Two modes: engineering (code-focused) and support (user/product-focused). Does not solve the ticket — only enriches it so whoever picks it up starts with full context.

Ticket Enrichment

Autonomous ticket enrichment for headless execution. Apply this to the ticket in the user's prompt. Produces a structured enrichment document — does not solve the ticket.

Gotchas

• Solving the ticket instead of enriching it. The output is context, not a fix.
• Context without citations. Every piece of context must reference its source — a PR number, Slack thread, decision, or doc.
• Assuming engineering mode. Read the ticket first. User-reported behavior or product questions need support mode.
• Enriching without the ticket contents. Always fetch or parse the full ticket first. The ticket text drives what to research.

How This Works

1. Get the ticket via context_get_urls (URL), context_search_issues or context_research (ticket ID like PROJ-123), or from the prompt. Extract summary, affected system, severity, reporter, labels, and linked items.
2. Classify mode from ticket content — engineering (code change, bug, feature, technical task) or support (user-reported behavior, product question, escalation). If the prompt specifies a mode, use that.
3. Gather context via context_research:

• Common (effort: medium): "How does [affected system] work, what decisions have been made, and has this been reported or attempted before? Include recent PRs, related issues, constraints."
• Engineering add-on (effort: medium): "Code paths for [affected functionality]? Team patterns for [area]? Prior attempts? File paths, utilities, entry points."
• Support add-on (effort: medium): "Expected user-facing behavior for [feature]? Known limitations? Similar reports and resolutions? Workarounds?"
• If the ticket has an error message, run a targeted context_research (effort: low) anchored on the error text.

1. Synthesize the enrichment document matching the classified mode.

Engineering Enrichment

• Affected systems — components, services, code paths with file references
• Relevant code — key files, entry points, utilities
• Related work — PRs, tickets, decisions with summaries
• Historical context — prior attempts, rejected approaches, constraints
• Suggested direction — based on team patterns, just orientation

Support Enrichment

• Product behavior — how the feature works, known limitations
• User impact — scope, workarounds
• Related incidents — similar reports and resolutions
• Resolution history — how the team has handled this before
• Ownership — which team, domain experts

Abort Conditions

• Can't fetch or parse the ticket — stop and report.
• No relevant context — produce minimal enrichment noting low confidence and what was searched.

Tool Selection

Fine-grained tools (context_search_issues, context_search_prs, context_search_code, etc.) are available in the Unblocked CLI. On MCP, fall back to context_research with a steering instruction.