analyzing-certificate-transparency-for-phishing
Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.
69
62%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/analyzing-certificate-transparency-for-phishing/SKILL.mdQuality
Discovery
82%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 description with excellent specificity, naming concrete tools and actions in a well-defined security niche. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The domain-specific terminology serves as effective natural trigger terms for security professionals.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about certificate monitoring, CT log analysis, detecting phishing domains via certificates, or mentions crt.sh or Certstream.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Monitor Certificate Transparency logs', 'detect phishing domains', 'lookalike certificates', 'unauthorized certificate issuance'. Also names specific tools: 'crt.sh' and 'Certstream'. | 3 / 3 |
Completeness | Clearly answers 'what does this do' (monitor CT logs, detect phishing domains, lookalike certs, unauthorized issuance) but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Certificate Transparency', 'crt.sh', 'Certstream', 'phishing domains', 'lookalike certificates', 'unauthorized certificate issuance'. These are terms a security professional would naturally use when needing this capability. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche focused on Certificate Transparency monitoring with specific tools (crt.sh, Certstream) and specific threat types. Very unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides highly actionable, executable Python code for CT log monitoring, which is its primary strength. However, it suffers from significant verbosity—explaining concepts Claude already knows, including generic 'When to Use' bullets, and inlining massive code blocks that should be in separate files. The workflow lacks integrated validation checkpoints and error recovery guidance between steps.
Suggestions
Remove the 'Key Concepts' section entirely or reduce to 2-3 bullet points of non-obvious information; Claude already understands CT logs, certificate issuance, and crt.sh.
Extract the large class implementations into separate referenced files (e.g., ct_monitor.py, certstream_monitor.py) and keep only concise usage examples inline in SKILL.md.
Add explicit validation checkpoints between steps: e.g., 'Verify crt.sh returns data before proceeding' and 'If rate-limited, wait 10s and retry' with concrete error-handling code.
Remove the generic 'When to Use' section—it adds no actionable information and wastes tokens on obvious use cases.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is excessively verbose. The 'Key Concepts' section explains CT logs, phishing detection via CT, and crt.sh in detail—all concepts Claude already knows. The 'When to Use' section is generic filler. The 'Prerequisites' section explains what crt.sh and Certstream are despite already being obvious from context. The code blocks are very long with extensive boilerplate that could be significantly condensed. | 1 / 3 |
Actionability | The skill provides fully executable Python code with complete class implementations, concrete API calls, specific library usage, and copy-paste ready examples. Each step includes working code with proper imports, error handling, and example invocations. | 3 / 3 |
Workflow Clarity | The four steps are clearly sequenced and logically ordered (historical query → real-time monitoring → subdomain enumeration → reporting). However, there are no explicit validation checkpoints between steps—the 'Validation Criteria' section is a post-hoc checklist rather than integrated feedback loops. There's no guidance on what to do if crt.sh returns errors, rate limits, or empty results. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with ~200+ lines of inline code. The four large code blocks with full class implementations should be split into separate reference files. There's no quick-start section—the reader must wade through concepts and prerequisites before reaching any actionable content. References are listed but no content is appropriately delegated to separate files. | 1 / 3 |
Total | 7 / 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
888bbe4
- Reviewed
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