AC qa-gate
质量检测门——为AI Agent、代码、文案提供标准化质量检测流程。8项检查+龙虾辩论逻辑，确保交付物无bug无遗漏。龙虾兵团专属QC门。" Run this skill on documents, skills, PRDs, blog posts, or code artifacts to validate factual accuracy, tone consistency, completeness, structural integrity, operational soundness, and sensitive data handling. Use when you need to "QA gate this", "validate before publish", run a "final check", perform "quality validation", proofread this, fact-check this, or otherwise validate, QA, or quality-gate an artifact before review, release, or publication.
As a process C 61/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
How to improve
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 3, column 86: …程。8项检查+龙虾辩论逻辑，确保交付物无bug无遗漏。龙虾兵团专属QC门。" Run this skill on documents, skills, PR… ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 61/100
- 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. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (qa-gate) differs from the folder (lobster-qa-gate)
- 60Result and completion. Output format stated, no completion criterion
- 70Failures and branches. 4 branches
- 100Tools and files. No external tools needed
- 100Steps. 34 steps
- 100Execution cost. Instruction body is 1095 tokens
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
- +4Description does not say when NOT to use the skill (false activations)
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 522: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 34 items
- +3Output format is stated explicitly
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.