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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".

Install with Tessl CLI

npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-logs
What are skills?

60

Does it follow best practices?

Validation for skill structure

SKILL.md
Review
Evals

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 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.

DimensionReasoningScore

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

Implementation

20%

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 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

DimensionReasoningScore

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

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.

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

metadata_version

'metadata' field is not a dictionary

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

13

/

16

Passed

Reviewed

Table of Contents

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