AB github-ops
Operates GitHub through gh CLI and the REST/GraphQL APIs with explicit target, authorization, impact preview, and independent readback. Use for pull requests, issues, Actions, repositories, collaborators, teams, organization member privileges, base permissions, 2FA enforcement, repository settings, API automation, parallel or superseded PR convergence, and public or enterprise GitHub. Also use when a GitHub write returned success but the requested state did not change, or when deciding whether a setting is writable through CLI, REST, GraphQL, or only the GitHub UI.
Operates GitHub through gh CLI and the REST/GraphQL APIs with explicit target, authorization, impact preview, and independent readback.
As a process B 67/100 · Nearly there — weak spots: result and completion, inputs and preconditions
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: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 67/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 20 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2738 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 571: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (9 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.