Jira Pull Request Extractor

Jira Pull Request Extractor

This skill recursively discovers Jira issues and extracts all associated GitHub Pull Request links.

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 (like extract_prs.py). Follow the step-by-step instructions in the "Implementation" section below.

When to Use This Skill

Use this skill when you need to:

• Discover all GitHub PRs associated with a Jira feature and its subtasks
• Extract PR metadata without analyzing PR content
• Build a complete map of PRs for documentation or release notes

Key characteristics:

• ✅ Always recursive: Automatically discovers all descendant issues via childIssuesOf() JQL
• ✅ PR-only: Extracts only Pull Request URLs (ignores Issue and Commit URLs)
• ✅ Dual-source: Extracts from both changelog remote links and text content (description/comments)
• ✅ Structured output: Returns JSON with PR metadata and deduplication across sources

Prerequisites

• MCP Jira server configured and running (required - see plugins/jira/README.md for setup)
• jq installed for JSON parsing
• GitHub CLI (gh) installed and authenticated for fetching PR metadata
• User has read permissions for target Jira issues (including private issues via MCP authentication)
• User has read access to linked GitHub repositories

Output Format

Purpose: This skill returns structured JSON that serves as an interface contract for consuming skills and commands.

Delivery Method:

• Primary: Output JSON directly to the response (no file writes, no user prompts)
• Secondary: Only save to .work/extract-prs/{issue-key}/output.json if user explicitly requests to save results

Schema Version: 1.0

Structure

{
  "schema_version": "1.0",
  "metadata": {
    "generated_at": "2025-11-24T10:30:00Z",
    "command": "extract_prs",
    "input_issue": "OCPSTRAT-1612"
  },
  "pull_requests": [
    {
      "url": "https://github.com/openshift/hypershift/pull/6444",
      "state": "MERGED",
      "title": "Add support for custom OVN subnets",
      "isDraft": false,
      "sources": ["comment", "description", "remote_link"],
      "found_in_issues": ["CNTRLPLANE-1201", "OCPSTRAT-1612"]
    }
  ]
}

Fields:

• schema_version: Format version ("1.0")
• metadata: Generation timestamp, command name, and input issue
• pull_requests: Array of PR objects with url, state, title, isDraft, sources, and found_in_issues

Implementation

The skill operates in three main phases:

🔍 Phase 1: Descendant Issue Discovery

Discovers all descendant issues using Jira's childIssuesOf() JQL function (automatically recursive).

Implementation:

1. Fetch issue metadata using MCP Jira tool:

   mcp__atlassian__jira_get_issue(
     issue_key=<issue-key>,
     fields="summary,description,issuetype,status,comment",
     expand="changelog"
   )
   

   • Extract fields.description - for text-based PR URL extraction
   • Extract fields.comment.comments - for PR URLs mentioned in comments
   • Extract changelog.histories - for remote link PR URLs from RemoteIssueLink field changes

2. Search for ALL descendant issues using JQL:

   mcp__atlassian__jira_search(
     jql="issue in childIssuesOf(<issue-key>)",
     fields="key",
     limit=100
   )
   

   • Important: childIssuesOf() is already recursive - returns ALL descendant issues (Epics, Stories, Subtasks, etc.) regardless of depth
   • Single JQL query gets everything - no manual recursion needed
   • Only fetch key field here - will fetch full data (including changelog) per-issue in Phase 2
   • Note: jira_search does NOT support expand parameter - use jira_get_issue with expand="changelog" for each issue

3. Fetch full data for each issue (including root + all descendants):

   for each issue_key:
     mcp__atlassian__jira_get_issue(
       issue_key=<issue-key>,
       fields="summary,description,issuetype,status,comment",
       expand="changelog"
     )
   

   • This fetches description, comments, and changelog (which includes remote links)
   • Excludes issue links (relates to, blocks, etc.) - only parent-child relationships

🔗 Phase 2: GitHub PR Extraction

Extracts PR URLs from two sources:

Source 1: Jira Remote Links via Changelog (primary)

• Extract remote links from issue changelog (using MCP with authenticated access):

  # Fetch issue with changelog expansion (store in variable)
  issue_json=$(mcp__atlassian__jira_get_issue \
    issue_key="${issue_key}" \
    expand="changelog")
  
  # Extract RemoteIssueLink entries from changelog
  pr_urls=$(echo "$issue_json" | jq -r '
    .changelog.histories[]?.items[]? |
    select(.field == "RemoteIssueLink") |
    .toString // .to_string |
    match("https://github\\.com/[^/]+/[^/]+/(pull|pulls)/[0-9]+") |
    .string
  ' | sort -u)
  

• Important:
  • Remote links appear in changelog as RemoteIssueLink field changes
  • Changelog contains link creation events with GitHub PR URLs in toString or to_string field
  • Store results in variables, not temporary files
  • Uses MCP authentication (no separate curl needed)
• Filters for GitHub PR URLs matching /pull/ or /pulls/ pattern

Source 2: Text Content (backup)

• Searches both fields.description and fields.comment.comments[] (already fetched in Phase 1)
• Description: Extract from fields.description (plain text or Jira wiki format)
• Comments: Iterate through fields.comment.comments[] array and search each comment.body
• Uses regex: https?://github\.com/([\w-]+)/([\w-]+)/pulls?/(\d+)
• Example extraction (using variables):

  # From description (stored in variable from MCP response)
  description_prs=$(echo "$description" | \
    grep -oE 'https?://github\.com/[^/]+/[^/]+/pulls?/[0-9]+')
  
  # From comments (parse JSON in memory)
  comment_prs=$(echo "$issue_json" | \
    jq -r '.fields.comment.comments[]?.body // empty' | \
    grep -oE 'https?://github\.com/[^/]+/[^/]+/pulls?/[0-9]+')
  
  # Combine all PRs
  all_prs=$(echo -e "${description_prs}\n${comment_prs}" | sort -u)
  

Deduplication:

• Merges URLs found in multiple sources/issues
• Tracks sources array: ["comment", "description", "remote_link"] (alphabetically sorted)
  • "comment": Found in issue comments
  • "description": Found in issue description
  • "remote_link": Found via Jira Remote Links API
• Tracks found_in_issues array: ["OCPSTRAT-1612", "CNTRLPLANE-1201"] (alphabetically sorted)
• Important: If same PR URL found in multiple sources or issues, merge into single entry with combined arrays

📊 Phase 3: Data Structuring and Output

PR Metadata: Fetch via gh pr view {url} --json state,title,isDraft. CRITICAL: When building the output JSON, you MUST use the exact values returned by gh pr view - do NOT manually type or guess PR states/titles.

Output: Build JSON in memory using jq -n, output to console. Only save to .work/extract-prs/{issue-key}/output.json if user explicitly requests.

Important: Use bash variables for all data - no temporary files to avoid user confirmation prompts.

Error Handling

• MCP server not available: Display error message directing user to configure MCP server (see Prerequisites)
• Issue not found: Log warning and continue with remaining issues
• Permission denied:
  • If MCP returns 403 for private issues, verify JIRA_API_TOKEN and JIRA_USERNAME are configured correctly
  • MCP authentication handles all Jira access (including changelog and remote links)
• Changelog expansion fails: If expand="changelog" returns error, continue with text-based extraction only (graceful degradation)
• No PRs found: Return empty pull_requests array (valid result)
• Too many descendants: If hierarchy has >100 issues, increase limit parameter in jira_search
• GitHub rate limit: If gh pr view fails due to rate limiting, display error with reset time
• PR metadata fetch fails: If gh pr view returns error (PR deleted/private), exclude that PR from output

Performance Considerations

API calls: 1 jira_search + N jira_get_issue (with changelog) + M gh pr view

• Example: 11 issues = 12 MCP calls + M PR fetches
• Changelog expansion includes remote links (no extra calls needed)
• Can parallelize: issue fetching and PR metadata fetching

File I/O: Save PR metadata to .work/extract-prs/{issue-key}/pr-*-metadata.json, build final JSON by reading files

Converted and distributed by TomeVault — claim your Tome and manage your conversions.