logging-api-requests
Monitor and log API requests with correlation IDs, performance metrics, and security audit trails. Use when auditing API requests and responses. Trigger with phrases like "log API requests", "add API logging", or "track API calls".
72
67%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/api-development/api-request-logger/skills/logging-api-requests/SKILL.mdQuality
Discovery
92%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 well-structured skill description that clearly states concrete capabilities and includes explicit trigger guidance with natural user phrases. The 'what' and 'when' are both clearly addressed. The main weakness is potential overlap with broader logging, monitoring, or security audit skills, though the API-specific focus helps mitigate this.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: monitor and log API requests, correlation IDs, performance metrics, and security audit trails. These are concrete, well-defined capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (monitor and log API requests with correlation IDs, performance metrics, security audit trails) and 'when' (explicit 'Use when auditing API requests and responses' plus trigger phrases). | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would say: 'log API requests', 'add API logging', 'track API calls', plus terms like 'auditing', 'API requests', 'correlation IDs', and 'performance metrics' that users might naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Fairly specific to API logging/auditing, but could overlap with general logging skills, observability skills, or security audit skills. The focus on API requests helps narrow it, but 'performance metrics' and 'security audit trails' could conflict with monitoring or security-focused skills. | 2 / 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 is well-organized with good progressive disclosure and a logical structure, but critically lacks actionable, executable code—the core implementation is entirely deferred to a reference file. The instructions describe what to build at a high level without providing concrete middleware code, configuration snippets, or PII redaction patterns that Claude could directly use or adapt. The error handling table is a useful addition but doesn't compensate for the absence of executable guidance in the main body.
Suggestions
Add at least one complete, executable middleware code example (e.g., a minimal Express/Fastify request logging middleware with correlation ID) directly in the Instructions section rather than deferring everything to implementation.md.
Include a concrete PII redaction code snippet showing configurable field-path patterns, since this is a critical and non-obvious part of the skill.
Add explicit validation checkpoints between steps, such as 'Verify log output matches expected JSON structure by running: curl localhost:3000/test | jq' after step 2.
Trim the Overview and Prerequisites sections—remove parenthetical expansions like '(Elasticsearch, Logstash, Kibana)' and general descriptions of what structured logging enables, as Claude already knows these concepts.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably structured but includes some unnecessary verbosity, such as the detailed overview paragraph explaining what JSON logging is for and listing aggregation systems Claude already knows about. The prerequisites section also over-explains concepts like what ELK Stack stands for. | 2 / 3 |
Actionability | Despite listing 9 steps, the skill provides zero executable code—no middleware implementation, no configuration snippets, no concrete examples of PII redaction patterns. The instructions read as high-level descriptions of what to build rather than concrete, copy-paste-ready guidance. The actual implementation is deferred to a reference file. | 1 / 3 |
Workflow Clarity | Steps are sequenced logically (examine existing setup → implement middleware → add features → test), and step 9 includes testing as validation. However, there are no explicit validation checkpoints between steps, no feedback loops for verifying PII redaction works before proceeding, and no intermediate verification that the logging middleware is functioning correctly. | 2 / 3 |
Progressive Disclosure | The skill appropriately structures content with a clear overview, then references implementation details, error patterns, and examples in separate files via well-signaled one-level-deep references (implementation.md, errors.md, examples.md). The main file serves as a navigable overview. | 3 / 3 |
Total | 8 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
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