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AI-powered issue operations via gh-models. TRIGGERS - issue summarization, auto-labeling, issue insights.
Passed 17 of 22 test cases with the skill, and 9 of 22 without it.
and 6 more in the full report
9 fixed9 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write the gh issue view command to fetch both title and body of issue #200 as a JSON object.
| Checked | Without skill | With skill |
|---|---|---|
| Uses gh issue view 200 command | Passed | Passed |
| Uses --json title,body with --jq '{title, body}' | Missed | Passed |
The instructions your model reads when the skill loads.
Capability: AI-assisted issue summarization, auto-labeling, Q&A, and documentation generation using gh-models
When to use: Leveraging LLMs for intelligent issue processing and automation
Installation Required: gh extension install github/gh-models
# Show all 29+ models
gh models list
# Popular models for issue operations:
# - openai/gpt-4.1
# - openai/gpt-4o-mini
# - anthropic/claude-3.5-sonnet
# Run AI model
gh models run "openai/gpt-4.1" "Your prompt here"
# With multi-line prompt
gh models run "openai/gpt-4.1" "$(cat <<'EOF'
Analyze this issue and suggest improvements:
- Title clarity
- Completeness
- Priority assessment
EOF
)"
test cases passed, vs 9 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.