BD Log Smell Auditor
Application logging quality auditor. Scans source files for logging anti-patterns — debug/print statements left in production paths, log level mismatches (errors logged as info, warnings swallowed), PII exposure risk (email, token, password appearing in log strings), missing structured context fields (no request_id/trace_id in web handler log calls), and noisy debug flooding in tight loops. Supports JavaScript/TypeScript (console.log, winston, pino), Python (logging, structlog, print), Go (log, zap, logrus), Java (SLF4J, Log4j), and Ruby (Rails logger). Reports by severity with file and line citations. Generates a one-command fix for the most common issues. Zero external API — pure static file analysis. Triggers on "logging audit", "bad logs", "debug left in code", "PII in logs", "log level wrong", "missing trace id", "/log-audit".
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (Log Smell Auditor) differs from the folder (phy-log-smell-auditor)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 9 steps
- 100Execution cost. Instruction body is 3520 tokens
- 100Progress reporting. Reports progress
- high The skill tells the model to perform an irreversible action with no human approval
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)
- +3Description length 843: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +4Structure: 14 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (19 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.