AC GitHub Actions
Design, debug, and harden GitHub Actions workflows with reusable pipelines, safe permissions, and faster CI and release automation.
As a process C 63/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
ProcedureGitHubInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
How to improve
For the model run — optional
- 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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "changelog"
Process rating: all ten parameters 63/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 19 mutating operations with no state check
- 40Consistency. Frontmatter name (GitHub Actions) differs from the folder (github-actions)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 47 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Failures and branches. 2 branches, has a failure section
- 100Execution cost. Instruction body is 2107 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 16 top-level sections: this looks like several domains in one skill
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 131: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.
External checks
ClawHub: clean
The skills are coherent development and maintainer workflows, with sensitive actions disclosed and mostly gated by user direction.
LLM: benign (high) · VirusTotal: · 29 May 2026