Jira Feature Documentation Generator

Jira Feature Documentation Generator

This skill provides detailed step-by-step implementation guidance for the /jira:generate-feature-doc command, which generates comprehensive feature documentation by recursively analyzing a Jira feature and all its related issues and GitHub pull requests.

IMPORTANT FOR AI: This is a procedural skill - when invoked, you should directly execute the implementation steps defined in this document. Do NOT look for or execute external scripts. Follow the step-by-step instructions below, starting with Step 1.

When to Use This Skill

This skill is automatically invoked by the /jira:generate-feature-doc command and should not be called directly by users.

Prerequisites

• MCP Jira server configured and running (required - see plugins/jira/README.md for setup)
• GitHub CLI (gh) installed and authenticated (for analyzing PRs)
• User has read access to Jira issues (including private issues via MCP authentication)
• User has read access to linked GitHub repositories
• Working directory has .work/jira/feature-doc/ for output (will be created if needed)

Implementation Steps

Step 1: Initialize and Fetch Main Feature Issue

Objective: Set up environment and fetch main feature issue.

Actions:

1. Save initial directory: INITIAL_DIR=$(pwd) (save at start, before any cd commands)

2. Check prerequisites: Verify jq and gh CLI are installed and authenticated

   • If missing, display error with installation instructions

3. Create output directory: WORK_DIR=$INITIAL_DIR/.work/jira/feature-doc/<feature-key> (use mkdir -p)

4. Fetch main feature: Use MCP Jira tool to get issue with all fields:

   mcp__atlassian__jira_get_issue(issue_key=<feature-key>, fields="*all")
   

   • If MCP unavailable, display error pointing to plugins/jira/README.md

5. Parse response: Extract key, summary, description, issuetype, status

   • If fetch fails, display error and exit

6. Display progress: Show feature summary and type

Step 2: Analyze Each GitHub PR

Important: This step expects PR data as input from the jira:extract-prs skill (invoked by the command file). The input is structured JSON containing all discovered PRs with their metadata.

Input Format:

{
  "pull_requests": [
    {
      "url": "https://github.com/org/repo/pull/123",
      "state": "MERGED",
      "title": "PR title",
      "isDraft": false,
      "sources": ["remote_link", "description"],
      "found_in_issues": ["ISSUE-123"]
    }
  ]
}

Objective: Fetch and analyze PR details to extract implementation information.

Important: This command is for documenting completed features. Only analyze PRs that have been MERGED. Skip OPEN, DRAFT, WIP, or CLOSED (but not merged) PRs.

Actions:

1. Filter for MERGED PRs: Only analyze PRs with state == "MERGED" AND isDraft == false

   • Skip OPEN PRs (work in progress)
   • Skip PRs with isDraft == true (not ready for review)
   • Skip CLOSED PRs (not merged)

2. For each MERGED PR, fetch detailed data:

   • Parse PR URL to extract org/repo/number
   • Fetch metadata: gh pr view {number} --repo {org}/{repo} --json title,body,mergedAt,author,commits,files
   • Fetch diff: gh pr diff {number} --repo {org}/{repo}
   • Fetch comments: gh pr view {number} --repo {org}/{repo} --json comments

3. Extract key information:

   • From body: Purpose, approach, breaking changes
   • From commits: Implementation steps, testing
   • From diff: New APIs, architectural changes, config updates
   • From comments: Design decisions, rationale, considerations

4. Handle errors: If PR inaccessible (403, 404), log warning and continue

5. Save data: Store metadata, diff, and comments to ${WORK_DIR}/pr-{org}-{repo}-{number}.*

Step 3: Synthesize Documentation Structure

Objective: Organize information into structured outline.

Available sections (calling command specifies which to generate):

1. Overview: Jira link, status, counts, dates, authors (from main issue + PR metadata)
2. Background and Goals: Description from main issue (clean Jira formatting)
3. Architecture and Design: High-level changes, components, design decisions (from PRs)
4. Implementation Details: Core changes, API changes, configuration (from PR diffs, code snippets)
5. Usage Guide: Prerequisites, basic/advanced usage (from README updates, PR descriptions)
6. Testing: Test coverage, strategies, key test PRs
7. Related Resources: Can include external links, issue tables, PR tables, dependency graphs

Step 4: Generate Documentation Content

Objective: Fill in the outline with actual content based on command requirements.

Section generation guidelines:

1. Overview: Extract from main issue + PR metadata (Jira link, status, counts, dates, authors)
2. Background: Clean Jira formatting from main issue description
3. Architecture: Synthesize from PR descriptions and comments (high-level overview, components, decisions with PR links)
4. Implementation: Group by core changes, API changes, configuration (include code snippets, link to PRs, list key files)
5. Usage: Extract from README updates and PR descriptions (prerequisites, YAML/CLI examples)
6. Testing: Summarize by category (unit, E2E, CI), list key test PRs
7. Related Resources: Format depends on command requirements (external links, tables, graphs)

Note: Only generate sections specified by the calling command. Check the command file for exact requirements.

Step 5: Output

Objective: Save documentation and display summary.

Actions:

1. Write documentation: Save to ${WORK_DIR}/feature-doc.md with footer:

   ---
   *Generated by `/jira:generate-feature-doc` on <timestamp>*
   *Source: <feature-key> and <count> related issues*
   

2. Save metadata: Store analysis log with timestamps, counts, output files, errors/warnings

3. Display summary:

   • Success message with file location
   • Statistics: issues analyzed, PRs analyzed, commits, files changed, doc lines
   • Warnings if any (inaccessible PRs, missing descriptions)
   • Additional files for debugging

Error Handling

Issue Not Found (404, 403, network error):

• Display error with verification steps (issue key format, permissions, MCP config)
• Exit gracefully without creating files

No PRs Found:

• Display warning (feature not implemented, PRs not linked, or small feature)
• Generate documentation from main issue only

GitHub Rate Limit:

• Display error with progress and reset time
• Offer options: wait, generate from partial data, or cancel

Large Feature (>50 PRs):

• Display warning with estimated time and API calls
• Offer options: continue or cancel

Malformed Issue Data:

• Log warning about missing/invalid fields
• Continue with remaining issues (don't fail entire process)

Performance Optimization

Parallel PR Analysis:

• For >10 PRs, use parallel processing (xargs -P 5)
• Limit to ~5 concurrent requests to avoid rate limits

Smart Diff Analysis:

• Use --stat to identify key files
• Skip vendor/, generated files, test fixtures
• Fetch full diff only for critical files

Best Practices for AI Implementation

1. Progress feedback: Show progress after each major step (discovery, PR analysis, etc.)

2. Error resilience: Don't fail the entire process if one PR is inaccessible

3. Smart synthesis: Don't just concatenate PR descriptions - synthesize into coherent narrative

4. Context awareness: Understand the codebase domain (e.g., Kubernetes, OpenShift) to better interpret changes

5. Structured output: Use consistent markdown formatting with proper headers, code blocks, tables

6. Link preservation: Always provide clickable links to Jira issues and GitHub PRs

7. Timestamp tracking: Note when PRs were merged to understand timeline

8. Author attribution: Credit authors of PRs and issues where relevant

9. Code examples: Include actual code snippets from PRs to illustrate changes

10. Visual hierarchy: Use tables, lists, and headers to make documentation scannable

Example Workflow

User runs: /jira:generate-feature-doc OCPSTRAT-1612

1. Initialize
   - Fetch main feature issue (OCPSTRAT-1612)
   - Create working directory (.work/jira/feature-doc/OCPSTRAT-1612/)
   - Verify prerequisites (jq, gh CLI)

2. Extract PRs (via extract-prs skill)
   - Discover descendants using childIssuesOf() JQL → 3 issues total
   - Extract PRs from remote links (primary) + text (backup) → 7 PRs
   - Fetch PR state from GitHub → 5 MERGED, 1 OPEN, 1 CLOSED

3. Analyze MERGED PRs
   - Filter for MERGED PRs → 5 PRs to analyze
   - For each: fetch metadata + diff + comments
   - Extract implementation details, design decisions

4. Generate Documentation
   - Synthesize sections: Overview, Architecture, Implementation, Usage, Testing
   - Create tables for issues and PRs
   - Write to feature-doc.md

5. Display Results
   ✅ Documentation generated successfully!
   📄 File: .work/jira/feature-doc/OCPSTRAT-1612/feature-doc.md
   📊 3 issues, 5 MERGED PRs, ~380 lines generated

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