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log-analyzer

Use this skill when the user wants to analyze log files — find errors and their frequency, detect anomalies, build incident timelines, or summarize what happened during an outage.

Quality

90%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

82%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 solid, actionability-first skill body: complete executable code covering the full log-analysis pipeline with a helpful function index. The main improvement areas are removing the hardcoded dated model version, adding an explicit end-to-end usage sequence with a format-detection checkpoint, and splitting the bulk code into bundle files.

Suggestions

Replace the hardcoded time-sensitive model "claude-opus-4-6" with a current model id or configuration-driven selection, or move version guidance to a deprecated/old-patterns section.

Add a short explicit workflow (parse → check for UNKNOWN levels/format detection → extract → analyze → report) with a validation checkpoint so the sequence and error handling are prescriptive, not just implied by function order.

Move the full parser/AI code into a scripts/ or references/ file and keep SKILL.md as a lean overview with clearly signaled one-level-deep links, improving progressive disclosure.

DimensionReasoningScore

Conciseness

The body is lean and code-forward — minimal prose, brief docstrings, no explanation of concepts Claude already knows — matching the level-4 anchor of efficient with minor trimmable instances. It is not a 5 because of the time-sensitive hardcoded version "claude-opus-4-6" (version-specific detail not placed in an old-patterns/deprecated section) and the Overview paragraph slightly duplicating the frontmatter description.

4 / 5

Actionability

All guidance is complete, executable Python (no pseudocode) covering the common cases — parse_log_file, extract_errors, error_frequency, analyze_logs_with_ai, build_incident_timeline, generate_log_report — plus a Quick Reference table mapping tasks to functions, matching the level-5 copy-paste-ready anchor. The Summary Report block omits imports but reads as a continuation of the single module, so this does not fall to level 4's 'minor gaps'.

5 / 5

Workflow Clarity

Sections sequence the work clearly (parse → extract/count → AI analysis/timeline → report) and the Quick Reference table maps each task to its function, matching the level-4 anchor of a clear sequence with minor validation gaps. It is not a 5 because there is no explicit end-to-end run example or validation checkpoint (e.g., verifying the log format was detected vs. falling to UNKNOWN), and not a 3 because the sequence and task mapping are explicit rather than implicit.

4 / 5

Progressive Disclosure

A single well-organized SKILL.md (no references/, scripts/, or assets/ exist in the bundle) with clear section headers and a navigation table, matching the level-4 anchor of good structure with most content appropriately placed. It is not a 5 because at ~150 lines the full parser/AI code is inlined where a scripts/ or references/ split would keep SKILL.md an overview, though the skill is well over the under-50-line simple-skill exception.

4 / 5

Total

17

/

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 description: concrete multi-action capability statement fused with an explicit, natural trigger clause. The only gap is modest keyword coverage — no .log extension or synonyms like "troubleshoot"/"debug" — which keeps trigger term quality at 4 rather than 5.

DimensionReasoningScore

Specificity

The description lists four concrete, specific actions — "find errors and their frequency, detect anomalies, build incident timelines, or summarize what happened during an outage" — giving comprehensive coverage of the log-analysis domain, matching the level-5 anchor's multi-action comprehensiveness. It is well above level 4 (which allows minor coverage gaps) and there is no vagueness that would place it lower.

5 / 5

Completeness

It explicitly answers "when" with the trigger clause "Use this skill when the user wants to analyze log files" and answers "what" through the concrete embedded actions (find errors/frequency, detect anomalies, build timelines, summarize outages), matching the level-5 anchor of both what and when with concrete triggers. The phrasing is imperative "Use this skill when..." with no first/second-person pronouns, so no voice penalty applies.

5 / 5

Trigger Term Quality

Natural phrases users would say are present: "analyze log files", "find errors", "anomalies", "incident timelines", "outage" — good coverage matching the level-4 anchor. It falls short of level 5 because file extensions (.log) and common synonyms/variations (e.g., "troubleshoot", "debug", "grep the logs") are missing.

4 / 5

Distinctiveness Conflict Risk

The log-analysis niche is clearly defined with distinct triggers ("log files", "incident timelines", "outage") that would not naturally fire for unrelated skills, matching the level-5 anchor of a clear niche with minimal conflict risk. It is distinctly more scoped than the level-4 example's multi-format overlap.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

ProwlrBot/prowlr-marketplace

Path

external/community/log-analyzer/SKILL.md

Reviewed

Table of Contents

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