AD github-repo
GitHub repository configuration and verification. Topics — actions (GitHub Actions workflow generation + Dependabot grouping by dependency type), setup (integrations: CodeRabbit, Copilot, issue/PR templates, CODEOWNERS, branch protection), verify (repo prerequisites checklist for github-flow: remote, default branch, PR template, branch protection, GitHub Actions, CONTRIBUTING, LICENSE). Use when: "github actions", "workflow generation", "CI workflow", "dependabot", "dependabot groups", "coderabbit", "copilot setup", "GitHub Actions", "repo setup", "CODEOWNERS", "PR template", "issue template", "branch protection", "repo verify".
GitHub repository configuration and verification.
As a process D 46/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "depends-on"
Process rating: all ten parameters 46/100
- 0Steps. Prose only: no discrete steps
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 423 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 14 example trigger phrases
- +3Description length 636: enough signal without eating the budget
- +4Structure: 7 headings
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.