log-error-digest

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or get distribution stats.

Quality

89%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable tool skill with executable examples and a real supporting script. The main improvement area is adding light validation guidance for interpreting parse failures and verifying output.

Suggestions

Add a short note on how to interpret 'parse failures' in the overview output and when to re-run with a different --format.

Document expected exit codes or error behavior of analyze_logs.py so Claude knows when a run failed vs. produced an empty report.

Trim the illustrative terminal-output block to the most representative lines to further reduce token cost.

Dimension	Reasoning	Score
Conciseness	The body is efficient with well-organized tables and copy-paste commands, assuming Claude's competence; the terminal-output sample is somewhat long but illustrative rather than padded with known concepts.	4 / 5
Actionability	Provides a concrete executable invocation, a full parameter table, and four copy-paste-ready examples covering the common cases (auto-detect, format selection, level filter/export, time range).	5 / 5
Workflow Clarity	The single-action workflow (run the script with options) is unambiguous and read-only, but there is no explicit validation/checkpoint guidance (e.g., how to verify parse failures or interpret the report).	4 / 5
Progressive Disclosure	Clean section structure (Features, Formats, Usage, Output) with a single one-level-deep bundle reference (scripts/analyze_logs.py) that exists as a real file; content is appropriately placed with easy navigation.	5 / 5
	Total	18 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states capabilities and provides an explicit, natural-language trigger clause. The only minor gap is some missing synonyms in the trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'produce error clustering, frequency statistics, and time distribution reports' and 'identify peak error periods' — with comprehensive coverage and no vague filler.	5 / 5
Completeness	Explicitly answers both what it does (analyze logs, produce clustering/stats/distribution reports) and when to use it via a concrete 'Use when a user uploads a .log file and asks to...' trigger clause.	5 / 5
Trigger Term Quality	Includes natural user phrases ('analyze errors', 'find patterns', 'debug issues', 'get distribution stats') and the '.log file' extension, but is missing a few synonyms like 'logs' or 'log files' in the trigger clause.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (log error analysis with named formats JSON/syslog/Nginx) with distinct triggers and minimal overlap risk with unrelated skills.	5 / 5
	Total	19 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: zebbern/claude-code-guide
Path: skills/log-error-digest/SKILL.md
Commit: 3b43482

Reviewed: 1 day ago

Table of Contents

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