AC log-analyzer
Analyze application logs to produce actionable error digests with pattern detection, severity classification, trend analysis, and remediation recommendations. Supports auto-detection of common log formats including syslog, JSON structured logs, Apache/Nginx access and error logs, Python tracebacks, Node.js errors, Docker logs, and generic timestamped formats. Use when asked to analyze logs, debug errors from log files, find recurring issues in logs, create error reports from log data, investigate production incidents from logs, summarize log output, identify error patterns, check application health from logs, or parse server logs. Triggers on "analyze logs", "check logs", "log errors", "error digest", "parse logs", "log report", "what's failing", "production errors", "log summary", "incident analysis", "error patterns".
As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
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: 6. 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 63/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (log-analyzer) differs from the folder (logfile-analyzer)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 27 steps
- 100Execution cost. Instruction body is 862 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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 831: 120–800 characters recommended
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 11 headings
- +3Step-by-step instructions: 27 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.