analyzing-logs
tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-logsAnalyze 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".
60%
Overall
Validation
Implementation
Activation
Validation
81%| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md line count is 100 (<= 500) | Pass |
frontmatter_valid | YAML frontmatter is valid | Pass |
name_field | 'name' field is valid: 'analyzing-logs' | Pass |
description_field | 'description' field is valid (287 chars) | Pass |
description_voice | 'description' uses third person voice | Pass |
description_trigger_hint | Description includes an explicit trigger hint | Pass |
compatibility_field | 'compatibility' field not present (optional) | Pass |
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
metadata_field | 'metadata' field not present (optional) | Pass |
license_field | 'license' field is present: MIT | Pass |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_present | SKILL.md body is present | Pass |
body_examples | Examples detected (code fence or 'Example' wording) | Pass |
body_output_format | Output/return/format terms detected | Pass |
body_steps | Step-by-step structure detected (ordered list) | Pass |
Total | 13 / 16 Passed |
Implementation
20%This skill content is highly verbose and abstract, explaining concepts Claude already understands while failing to provide the concrete, executable guidance needed for actual log analysis. It describes what log analysis is and what the skill 'will do' rather than providing specific commands, regex patterns, or code examples that Claude could actually use. The workflow exists but lacks validation checkpoints critical for debugging operations.
Suggestions
- Replace abstract descriptions with concrete, executable examples: provide actual grep/awk commands, regex patterns for common log formats, and Python code snippets for parsing logs
- Remove sections explaining what log analysis is (Overview, How It Works, When to Use) - Claude knows this; focus only on project-specific log formats and tool locations
- Add validation checkpoints to the workflow, such as 'verify log format matches expected pattern before proceeding' and 'confirm extracted timestamps are within expected range'
- Include specific log format examples from the project (e.g., actual log line samples) and corresponding parsing commands
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive explanation of concepts Claude already knows. Sections like 'Overview', 'How It Works', and 'When to Use This Skill' explain what log analysis is rather than providing actionable instructions. The content could be reduced by 70%+ while preserving all useful information. | 1 / 3 |
Actionability | No concrete code, commands, or executable examples. The 'Examples' section describes what the skill 'will do' abstractly rather than showing actual grep/awk commands, regex patterns, or code snippets. Instructions like 'Extract relevant data' and 'Apply pattern matching' are vague descriptions, not actionable guidance. | 1 / 3 |
Workflow Clarity | Steps are listed in the Instructions section with a logical sequence, but there are no validation checkpoints, no feedback loops for error recovery, and no concrete verification steps. The Error Handling section lists things to check but doesn't integrate them into the workflow. | 2 / 3 |
Progressive Disclosure | Content is organized into sections but is monolithic - everything is in one file with no references to external detailed documentation. The Resources section mentions guides but provides no actual links. Content that could be split (best practices, integration details) is inline. | 2 / 3 |
Total | 6 / 12 Passed |
Activation
100%This is a well-crafted skill description that excels across all dimensions. It provides specific capabilities (slow requests, error patterns, resource usage), includes natural trigger phrases users would actually say, and explicitly states both what the skill does and when to use it. The description is concise yet comprehensive.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Analyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage.' These are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what (analyze logs for performance insights, slow requests, error patterns, resource usage) AND when ('Use when troubleshooting performance issues or debugging errors. Trigger with phrases like...'). | 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 common variations. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused on application log analysis with specific triggers around performance and error detection. Distinct from general debugging or monitoring skills due to explicit log-focused terminology. | 3 / 3 |
Total | 12 / 12 Passed |
Reviewed
Table of Contents
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