Agent skill
managing-lifecycle
Create, update, close, and bulk process GitHub Issues with state management and metadata updates. Use for CRUD operations, changing issue states, or batch processing.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/managing-lifecycle-terrylica-claude-code-skills-g
SKILL.md
Issue Lifecycle Operations
Capability: Complete CRUD operations for GitHub Issues and PRs
When to use: Creating, reading, updating, deleting, commenting on issues/PRs
Create Operations
Create Issue
# Basic creation
gh issue create --title "Bug: Login fails" --body "Steps to reproduce..."
# With labels and assignee
gh issue create \
--title "Feature: Add dark mode" \
--body "User requested dark mode support" \
--label feature,ui \
--assignee username
# From file
gh issue create --title "API Documentation" --body-file doc.md
# Interactive mode
gh issue create
Create with Template
# Knowledge base entry
gh issue create \
--repo terrylica/claude-code-skills-github-issues \
--title "Claude Code: Using Plan Mode" \
--label claude-code,tips,how-to \
--body-file tip.md
Read Operations
View Issue
# Web view
gh issue view 123 --web
# Terminal view
gh issue view 123
# JSON output (21 fields available)
gh issue view 123 --json title,body,state,labels,assignees,createdAt
List Issues
# List open issues
gh issue list
# Filter by assignee
gh issue list --assignee @me
# Filter by label
gh issue list --label bug --state open
# Limit results
gh issue list --limit 50
Update Operations
Modify Issue
# Update title
gh issue edit 123 --title "New title"
# Update body
gh issue edit 123 --body "Updated description"
# Add labels
gh issue edit 123 --add-label priority:high,bug
# Remove labels
gh issue edit 123 --remove-label wontfix
# Change assignee
gh issue edit 123 --add-assignee username
State Management
# Close issue
gh issue close 123
# Close with comment
gh issue close 123 --comment "Fixed in commit abc123"
# Reopen issue
gh issue reopen 123
# Mark as resolved
gh issue close 123 --reason completed
# Mark as won't fix
gh issue close 123 --reason "not planned"
Comment Operations
# Add comment
gh issue comment 123 --body "Thanks for reporting this!"
# Comment from file
gh issue comment 123 --body-file response.md
# Edit comment (requires comment ID)
gh api repos/owner/repo/issues/comments/COMMENT_ID \
--method PATCH \
--field body="Updated comment"
Delete Operations
# Delete issue (careful - permanent!)
gh issue delete 123
# Delete with confirmation skip
gh issue delete 123 --yes
# Note: Prefer closing over deleting for audit trail
Batch Operations
Close Multiple Issues
# Close all issues with specific label
gh issue list --label wontfix --json number --jq '.[].number' | \
xargs -I {} gh issue close {} --reason "not planned"
# Close old issues
gh search issues "is:open created:<2024-01-01" --json number --jq '.[].number' | \
xargs -I {} gh issue close {}
Bulk Label Updates
# Add label to multiple issues
for issue in 101 102 103; do
gh issue edit $issue --add-label priority:high
done
Common Workflows
Knowledge Base Entry Workflow
# 1. Create issue with content
gh issue create --title "Tip: Git worktrees" --body-file tip.md
# 2. Add labels
gh issue edit 1 --add-label git,tips,how-to
# 3. Verify created
gh issue view 1
Issue Triage Workflow
# 1. List new issues
gh issue list --label needs-triage
# 2. Review and categorize
gh issue edit 123 --add-label bug --remove-label needs-triage
# 3. Assign if needed
gh issue edit 123 --add-assignee dev-team
JSON Output Fields (21 available)
Core: number, title, body, state, url
Metadata: labels, assignees, milestone, projectCards
Timestamps: createdAt, updatedAt, closedAt
Engagement: comments, reactions
Users: author, participants
Full list: gh issue view --help
Best Practices
- Prefer closing over deleting - Maintains audit trail
- Use labels for organization - Better than comments
- Atomic updates - One change per command for clarity
- JSON for automation - Script with
--jsonand--jq - Batch carefully - Test on single issue first
Empirical Testing: 200+ test cases covering all CRUD operations
Full Operational Guide: AI_AGENT_OPERATIONAL_GUIDE.md
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