BF repo-standardizer
Polish any GitHub repository's surface — labels (emoji rating tiers, P0–P3 priority, impact severity), issue forms, PR template, CI workflows, CODEOWNERS, rulesets, docs. Repo meta & config only — no code logic touched. Use when creating a new repo or polishing an existing one.
Polish any GitHub repository's surface — labels (emoji rating tiers, P0–P3 priority, impact severity), issue forms, PR template, CI workflows, CODEOWNERS…
As a process F 46/100 · Will not run — References files that are not bundled: README.zh.md, README.md
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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: 22. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6319 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: README.zh.md - warning
missing-refreference to a missing file: README.md
Process rating: all ten parameters 46/100
- 0Tools and files. 2 referenced file(s) missing: README.zh.md, README.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 6319 tokens
- 100Steps. 76 steps
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 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 (5 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
- -241 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 278: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 76 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.