AB alibabacloud-polardb-mysql-sql-lint
Pre-release SQL assessment and optimization for PolarDB MySQL. Combines 28+ static lint rules with Alibaba Cloud DAS dynamic diagnosis. Detects full table scans, missing indexes, dangerous UPDATE/DELETE without WHERE, schema design issues, naming violations, and provides index recommendations with cost estimation. Triggers when users ask to review SQL statements, assess SQL quality, optimize queries before deployment, validate DDL changes, check for SQL injection risks, analyze execution plans, or get DAS-based optimization suggestions for PolarDB MySQL instances.
Pre-release SQL assessment and optimization for PolarDB MySQL.
As a process B 65/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
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 · 1
✓ No critical or high findings
Medium and low: 1
✓ Guard found no suspicious behaviour. 1 matches are attack strings quoted in this security skill's own documentation.
Files scanned: 1. 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 65/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 23 steps, 2 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2562 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 572: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (3 of 9)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.