BD sonarqube-review
Use when fixing SonarQube code quality issues automatically across any language or framework — issue analysis, fix generation, unit tests, and coverage. Supports Community, Enterprise, and custom SonarQube deployments via environment variables. Do NOT use for general code review without SonarQube (use code-review-and-quality), for whole-repo quality interventions without SonarQube (use quality-test-implementation), or for non-SonarQube static analysis tools. Part of the afonsoft/skills collection.
Supports Community, Enterprise, and custom SonarQube deployments via environment variables.
As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, running it twice
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: 26. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6189 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 49/100
- 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
- 30Running it twice. 18 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Steps. 151 steps, 8 vague phrases
- 70Execution cost. Instruction body is 6189 tokens
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 20 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- -244 emoji in the instructions: noise for the model
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 502: enough signal without eating the budget
- +4Structure: 69 headings
- +3Step-by-step instructions: 151 items
- +4Has examples (19 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.