SKILLEMALL.ai

AC golang-continuous-integration

CI/CD pipeline configuration using GitHub Actions for Golang projects — testing, linting, SAST, security scanning, code coverage, Dependabot, Renovate, GoReleaser, code review automation, and release pipelines. Use when setting up or improving Go project CI, configuring GitHub Actions workflows, adding linters or security scanners, automating dependency updates, or adding quality gates.

ClawHub Agent Skills author: Samuel Berthe v1.4.0 MIT-0 20 files body ≈ 3 215 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGitHubSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 19. 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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 27 mutating operations with no state check
    • 60Failures and branches. 2 branches
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 23 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3215 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 top-level sections: this looks like several domains in one skill
    • medium 18 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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
    • +2Single-language instructions
    • +3Description length 389: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 23 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: suspicious
    This is a legitimate Go CI/CD skill, but its AI review workflow ships with broad automatic PR-commenting and log-reading authority that should be reviewed before installation.
    LLM: suspicious (high) · 20 Aug 2026