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Get Started Free →List GitHub Actions workflows with per_page pagination support.
.claude/skills/github-github-workflows-query/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -85% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 98% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -62% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -38% | 0% |
List GitHub Actions workflows with efficient pagination using the --per-page flag.
Use this script to list workflows from any repository with controlled page sizes.
bash./query-workflows.sh --owner github --repo gh-aw # Returns 10 workflows (default per_page=10)
bash# Get the first workflow only ./query-workflows.sh --owner github --repo gh-aw --per-page 1 # Get 50 workflows starting from page 2 ./query-workflows.sh --owner github --repo gh-aw --per-page 50 --page 2
| Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | --owner | Yes | - | Repository owner (username or organization) | | --repo | Yes | - | Repository name | | --per-page | No | 10 | Results per page (1–100) | | --page | No | 1 | Page number |
Returns JSON with the following fields:
json{ "total_count": 42, "per_page": 10, "page": 1, "workflows": [ { "id": 12345, "node_id": "W_...", "name": "CI", "path": ".github/workflows/ci.yml", "state": "active", "created_at": "2024-01-01T00:00:00Z", "updated_at": "2024-01-01T00:00:00Z", "url": "https://api.github.com/repos/owner/repo/actions/workflows/12345", "html_url": "https://github.com/owner/repo/actions/workflows/ci.yml", "badge_url": "https://github.com/owner/repo/actions/workflows/ci.yml/badge.svg" } ] }
Calls the GitHub REST API: GET /repos/{owner}/{repo}/actions/workflows?per_page={n}&page={n}
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-05 | fail→pass | 4,641 | 2,283 | -51% | 1 | 1 | 0% | 923 | 832 | -10% | 0 | 0 | — |
case-01 | fail→fail | 14,273 | 8,267 | -42% | 1 | 1 | 0% | 2,891 | 1,127 | -61% | 0 | 0 | — |
case-02 | fail→pass | 22,631 | 2,015 | -91% | 1 | 1 | 0% | 5,102 | 785 | -85% | 0 | 0 | — |
case-03 | fail→fail | 21,107 | 7,777 | -63% | 1 | 1 | 0% | 4,583 | 842 | -82% | 0 | 0 | — |
case-04 | fail→pass | 2,699 | 2,191 | -19% | 1 | 1 | 0% | 468 | 928 | +98% | 0 | 0 | — |
case-06 | fail→pass | 13,868 | 2,812 | -80% | 1 | 1 | 0% | 2,452 | 937 | -62% | 0 | 0 | — |
case-07 | fail→pass | 7,656 | 1,728 | -77% | 1 | 1 | 0% | 1,294 | 797 | -38% | 0 | 0 | — |
case-08 | pass→pass | 4,182 | 1,836 | -56% | 1 | 1 | 0% | 661 | 822 | +24% | 0 | 0 | — |
case-09 | pass→pass | 2,944 | 2,079 | -29% | 1 | 1 | 0% | 443 | 810 | +83% | 0 | 0 | — |
case-10 | pass→pass | 3,290 | 3,168 | -4% | 1 | 1 | 0% | 624 | 1,067 | +71% | 0 | 0 | — |
case-11 | pass→pass | 4,535 | 2,783 | -39% | 1 | 1 | 0% | 787 | 1,003 | +27% | 0 | 0 | — |
case-12 | pass→pass | 2,433 | 2,220 | -9% | 1 | 1 | 0% | 350 | 840 | +140% | 0 | 0 | — |
case-13 | fail→pass | 5,895 | 1,708 | -71% | 1 | 1 | 0% | 880 | 742 | -16% | 0 | 0 | — |
case-14 | pass→pass | 2,972 | 2,068 | -30% | 1 | 1 | 0% | 391 | 785 | +101% | 0 | 0 | — |
case-15 | pass→pass | 8,437 | 1,668 | -80% | 1 | 1 | 0% | 1,260 | 734 | -42% | 0 | 0 | — |
case-16 | pass→pass | 4,236 | 1,987 | -53% | 1 | 1 | 0% | 632 | 721 | +14% | 0 | 0 | — |
case-17 | fail→pass | 7,375 | 1,670 | -77% | 1 | 1 | 0% | 1,294 | 796 | -38% | 0 | 0 | — |
case-18 | fail→pass | 6,983 | 1,871 | -73% | 1 | 1 | 0% | 1,475 | 819 | -44% | 0 | 0 | — |
case-19 | pass→pass | 5,855 | 2,860 | -51% | 1 | 1 | 0% | 625 | 874 | +40% | 0 | 0 | — |
case-20 | pass→pass | 4,907 | 4,565 | -7% | 1 | 1 | 0% | 912 | 1,380 | +51% | 0 | 0 | — |
case-21 | pass→pass | 6,574 | 5,689 | -13% | 1 | 1 | 0% | 1,199 | 1,415 | +18% | 0 | 0 | — |
case-22 | pass→pass | 7,397 | 4,432 | -40% | 1 | 1 | 0% | 1,147 | 1,363 | +19% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 20 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +36 percentage points is the difference between those two pass rates over the 20 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.