analyzing-web-server-logs-for-intrusion

Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.

Quality

73%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/analyzing-web-server-logs-for-intrusion/SKILL.md

Quality

Content

72%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 concise, actionable skill body with a clear command and concrete examples, undermined by two structural gaps: a batch workflow with no validation checkpoint, and an orphaned reference file that duplicates inline content rather than being linked from the overview.

Suggestions

Add an explicit validation/verification step to the workflow, e.g. after parsing confirm 'parsed N entries, 0 unparseable' and sanity-check the report before finishing.

Link references/api-reference.md from the body (e.g. a '## API reference' section) and move the duplicated attack-signature and scanner-UA tables out of SKILL.md into that file to avoid redundancy.

Either show executable detection-rule code inline or explicitly defer to scripts/agent.py for the full pattern set, so the guidance is fully executable rather than a pattern list.

Dimension	Reasoning	Score
Conciseness	The body is lean and efficient — bullet-list 'When to Use' and 'Prerequisites', a tight numbered instruction set, one command, two short examples — with no over-explanation of concepts Claude already knows; every token earns its place.	5 / 5
Actionability	Provides a copy-paste-ready bash command whose CLI flags (--log-file, --geoip-db, --output) match the real agent.py, plus concrete detection patterns and real example log lines; held at 4 because the detection rules are pattern lists rather than full executable code.	4 / 5
Workflow Clarity	A clear five-step sequence is present, but this is a batch log-processing operation with no validation or verification checkpoint (e.g. confirm parsing succeeded, sanity-check the generated report); per the rubric cap, a batch operation without validation cannot score above 3.	3 / 5
Progressive Disclosure	Sections are well-organized and scripts/agent.py is correctly referenced, but the bundled references/api-reference.md is never linked or signaled from the body and duplicates content already inlined (attack-signature and scanner-UA tables), leaving references present but not clearly signaled.	3 / 5
	Total	15 / 20 Passed

Description

75%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 specific, third-person, well-scoped description that clearly conveys capabilities and occupies a distinct niche. Its main weakness is the absence of an explicit 'Use when…' trigger clause, which caps completeness at 3 despite otherwise strong content.

Suggestions

Append an explicit trigger clause, e.g. 'Use when analyzing Apache or Nginx access logs for SQL injection, LFI, traversal, scanner, or brute-force activity.'

Add a few synonym/extension variants users might say (e.g. 'web logs', 'access logs', '.log files', 'intrusion detection') to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns' plus 'regex-based pattern matching', 'GeoIP enrichment', 'statistical anomaly detection' — comprehensive coverage matching the level-5 anchor.	5 / 5
Completeness	The 'what' is explicit and detailed, but there is no 'Use when…' clause or equivalent explicit trigger guidance; per the rubric guideline a missing trigger clause caps completeness at 3.	3 / 5
Trigger Term Quality	Good natural keyword coverage ('Apache and Nginx access logs', 'SQL injection', 'brute-force', 'OWASP attack signatures'), but lacks the 'Use when…' trigger phrasing and synonym/extension variants that would lift it to 5.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (web server log intrusion analysis) with distinct triggers (Apache/Nginx logs, specific attack classes) and minimal conflict risk with other skills.	5 / 5
	Total	17 / 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: mukul975/Anthropic-Cybersecurity-Skills
Path: skills/analyzing-web-server-logs-for-intrusion/SKILL.md
Commit: 54a7988

Reviewed: 5 minutes ago

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