SKILLEMALL.ai

BC github-ops

GitHub repository operations, automation, and management. Issue triage, PR management, CI/CD operations, release management, and security monitoring using the gh CLI. Use when the user wants to manage GitHub issues, PRs, CI status, releases, contributors, stale items, or any GitHub operational task beyond simple git commands.

The skillemall take

Wraps gh CLI for repository management: issue triage, PR handling, CI/CD, releases, security monitoring. Promises GitHub automation through the standard tool.

Two files, 1452 tokens of description. No critical errors, but two medium-severity issues found. Safety 98, quality 88, process 54—the instructions are solid, but workflow logic has gaps. Wide platform support: Claude, Cursor, DeepSeek, and eight more.

Install if you automate repetitive GitHub tasks via command line. Otherwise it collects dust. The low process score hints at surprises in production.

affaan-m/everything-claude-code Agent Skills author: affaan-m MIT 2 files body ≈ 1 452 tokens Open the sourcegithub.com↗ analyzed 24 h ago

GitHub repository operations, automation, and management.

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureGitHubInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
88
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

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 · 2

    ✓ No critical or high findings

    Medium and low: 2

    ✓ Guard found no suspicious behaviour. 2 matches are attack strings quoted in this security skill's own documentation.

    Files scanned: 2. 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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 46 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1452 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
    • low The response is described with custom markup (3 tags): a typed call is more reliable

    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 327: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 46 items
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.