analyzing-logs
Analyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage. Use when troubleshooting performance issues or debugging errors. Trigger with phrases like "analyze logs", "find slow requests", or "detect error patterns".
57
50%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/performance/log-analysis-tool/skills/analyzing-logs/SKILL.mdQuality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly articulates specific capabilities (log analysis, slow request detection, error pattern identification, resource usage monitoring), provides explicit 'Use when' guidance, and includes natural trigger phrases. It follows third-person voice and is concise without unnecessary padding. It closely matches the rubric's examples of good descriptions.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: analyzing logs for performance insights, issue detection, slow requests, error patterns, and resource usage. | 3 / 3 |
Completeness | Clearly answers both what (analyze application logs for performance insights and issue detection including slow requests, error patterns, resource usage) and when (troubleshooting performance issues, debugging errors) with explicit trigger phrases. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'analyze logs', 'find slow requests', 'detect error patterns', 'troubleshooting performance issues', 'debugging errors'. Good coverage of natural terms. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to application log analysis for performance and error detection. The specific mention of 'logs', 'slow requests', 'error patterns', and 'resource usage' creates a distinct niche unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill content is almost entirely descriptive and abstract, explaining what log analysis is and what the skill 'will do' without providing any concrete, executable guidance. It lacks code examples, specific commands (grep patterns, awk scripts, log parsing snippets), and actionable workflows. The content is heavily padded with generic information Claude already knows, wasting token budget on explanations rather than instructions.
Suggestions
Replace abstract descriptions with concrete, executable code examples — e.g., specific grep/awk commands for extracting slow requests (grep patterns for response times > threshold), Python scripts for parsing structured logs, and regex patterns for common error grouping.
Remove or drastically condense sections like 'Overview', 'How It Works', 'When to Use This Skill', 'Best Practices', and 'Integration' — these explain concepts Claude already knows and consume tokens without adding actionable value.
Add explicit validation checkpoints to the workflow, such as verifying log format before parsing, checking extracted record counts, and validating output report completeness before presenting results.
Include concrete example input (sample log lines) and expected output (structured analysis report format) so Claude knows exactly what format to produce.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive explanation of concepts Claude already knows. Sections like 'Overview', 'How It Works', 'When to Use This Skill', 'Best Practices', and 'Integration' are padded with generic descriptions that add no actionable value. The content explains what log analysis is rather than providing concrete instructions. | 1 / 3 |
Actionability | No concrete code, commands, or executable examples anywhere. The 'Instructions' section is entirely abstract ('Apply pattern matching', 'Generate analysis report'). Examples describe what the skill 'will do' in vague terms rather than showing actual grep/awk commands, regex patterns, or code snippets for parsing logs. | 1 / 3 |
Workflow Clarity | The workflow steps are vague and lack specificity — 'Extract relevant data', 'Apply pattern matching', 'Generate analysis report' provide no concrete guidance on how to accomplish these steps. No validation checkpoints, no feedback loops, and no specific tools or commands are referenced in the workflow. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with many sections that could be condensed or removed entirely. The 'Resources' section lists generic topics without actual links. No references to external files for detailed content. The document is bloated with sections like 'Integration', 'Best Practices', and 'How It Works' that don't add actionable value. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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