BC python-pep8-style
Apply PEP 8 Python code style standards when writing, reviewing, or refactoring Python code. Use this skill when the user asks to enforce Python coding style, review Python code formatting, write production-grade Python, fix style issues, organize imports, apply naming conventions, or follow Python best practices. Derived from PEP 8 — the official Style Guide for Python Code.
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 12440 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 57/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 7 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (python-pep8-style) differs from the folder (python-code-guide-skill)
- 40Execution cost. Instruction body is 12440 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Failures and branches. 11 branches
- 100Steps. 74 steps
- 100When it triggers. States when to use and when not to
- 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)
- +4Structure: 0 headings, hard to scan
- +3Output format is not stated: the model decides each time
- -5Long text without headings
- +2Single-language instructions
- +3Description length 378: enough signal without eating the budget
- +3Step-by-step instructions: 74 items
- +4Has examples (0 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.