analyzing-security-logs-with-splunk
Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.
85
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
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 strong skill description that clearly articulates specific capabilities (log correlation, timeline reconstruction, anomaly detection), covers relevant data types, and provides explicit trigger conditions. It uses proper third-person voice throughout and includes natural keywords that security professionals would use. The description is well-structured with a clear what/when separation.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'investigate security incidents through log correlation, timeline reconstruction, and anomaly detection' and specifies data types: 'Windows event logs, firewall logs, proxy logs, and authentication data analysis.' | 3 / 3 |
Completeness | Clearly answers both 'what' (investigate security incidents through log correlation, timeline reconstruction, anomaly detection across multiple log types) and 'when' ('Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation'). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Splunk', 'SPL', 'SIEM', 'log analysis', 'security event correlation', 'incident investigation', 'Windows event logs', 'firewall logs', 'proxy logs', 'authentication data'. These are terms a security analyst would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: Splunk Enterprise Security and SPL-based investigation. The combination of specific tool (Splunk), language (SPL), and domain (security incident investigation) makes it very unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, highly actionable skill with excellent SPL query examples covering the full incident investigation lifecycle. Its main weaknesses are verbosity from definitional content Claude doesn't need (glossary, tool descriptions) and the lack of explicit validation checkpoints in the workflow. The document would benefit from trimming explanatory content and adding verification steps between investigation phases.
Suggestions
Remove or drastically reduce the Key Concepts glossary and Tools & Systems sections—Claude already knows these definitions and they consume significant token budget.
Add explicit validation checkpoints between workflow steps, such as 'Verify search scope returned results from all expected sourcetypes before proceeding' and 'Cross-validate timeline entries across at least two independent log sources.'
Split the Common Scenarios, Output Format template, and reference material into separate linked files (e.g., SCENARIOS.md, REPORT_TEMPLATE.md) to keep the main skill focused on the core workflow and queries.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly comprehensive but includes some unnecessary elements like the Key Concepts glossary (Claude knows what SPL, CIM, sourcetype, and timechart are) and the Tools & Systems section which largely describes well-known tools. The core SPL queries and workflow are well-targeted, but the overall document could be tightened by removing definitional content. | 2 / 3 |
Actionability | Excellent actionability with fully executable SPL queries for each investigation step, covering authentication analysis, process tracing, network analysis, timeline building, and detection rule creation. Queries are copy-paste ready with realistic field names, event codes, and filter conditions. | 3 / 3 |
Workflow Clarity | The six steps provide a clear logical sequence for incident investigation, but there are no explicit validation checkpoints or feedback loops. For a security investigation workflow where incorrect queries could miss critical evidence or produce false conclusions, there should be verification steps (e.g., validate search scope covers all relevant data, confirm timeline completeness, cross-validate findings across sources). | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and headers, but it's a monolithic document with no references to external files for detailed content. The Key Concepts table, Tools & Systems section, Common Scenarios, and Output Format template could be split into separate reference files to keep the main skill lean. For a skill of this length (~180+ lines), better progressive disclosure would help. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
c15f73d
- Reviewed
Table of Contents
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