rate-limiting-apis
Implement sophisticated rate limiting with sliding windows, token buckets, and quotas. Use when protecting APIs from excessive requests. Trigger with phrases like "add rate limiting", "limit API requests", or "implement rate limits".
78
75%
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-rate-limiter/skills/rate-limiting-apis/SKILL.mdQuality
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 communicates what the skill does (implement rate limiting using specific algorithms), when to use it (protecting APIs from excessive requests), and includes natural trigger phrases. It is concise, specific, and distinctive with minimal risk of conflicting with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions/techniques: 'sliding windows, token buckets, and quotas' are distinct, well-defined rate limiting strategies. The description clearly names the domain (rate limiting) and specific implementation approaches. | 3 / 3 |
Completeness | Clearly answers both 'what' (implement rate limiting with sliding windows, token buckets, and quotas) and 'when' (protecting APIs from excessive requests, with explicit trigger phrases). Has an explicit 'Use when' clause and a 'Trigger with' clause. | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would actually say: 'add rate limiting', 'limit API requests', 'implement rate limits'. Also includes terms like 'API', 'rate limiting', 'requests' which are natural keywords. Good coverage of common variations. | 3 / 3 |
Distinctiveness Conflict Risk | Rate limiting is a clear, specific niche that is unlikely to conflict with other skills. The mention of specific algorithms (sliding windows, token buckets) and the focus on API protection make this highly distinctive. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a well-structured overview of rate limiting implementation with good coverage of algorithms, tiers, headers, and error handling. Its main weaknesses are the lack of executable code examples (everything is described in prose rather than shown) and missing validation checkpoints in the workflow. The references to external files suggest good progressive disclosure intent, but without bundle files to back them up, the skill falls short of being fully actionable.
Suggestions
Add concrete, executable code examples for at least one algorithm (e.g., a complete sliding window implementation with Redis) instead of prose descriptions.
Insert explicit validation checkpoints in the workflow, such as 'Verify Redis connectivity before proceeding' and 'Test rate limiter with a single endpoint before applying globally'.
Provide the referenced bundle files (implementation.md, errors.md, examples.md) or inline the most critical code snippets to ensure the skill is self-sufficient.
Trim the prerequisites section to only essential items and remove explanatory phrases like 'required for multi-instance deployments' that Claude can infer.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is moderately verbose with some unnecessary elaboration (e.g., explaining what each tier means, describing what token bucket does). The prerequisites section includes items like 'Documentation system for publishing rate limit policies' that are tangential. However, it's not egregiously padded and most content is relevant. | 2 / 3 |
Actionability | The instructions provide a clear sequence of what to do but lack executable code examples. Steps describe actions at a conceptual level ('implement rate limiting middleware that extracts the client identifier') without providing concrete, copy-paste-ready code. The examples section describes scenarios in prose rather than showing actual implementation code. | 2 / 3 |
Workflow Clarity | The 9-step workflow is clearly sequenced and logically ordered from analysis through implementation to testing. However, there are no explicit validation checkpoints or feedback loops between steps—step 9 mentions tests but there's no 'validate before proceeding' pattern. For a skill involving distributed state and Redis operations, missing intermediate validation caps this at 2. | 2 / 3 |
Progressive Disclosure | The skill references external files (implementation.md, errors.md, examples.md) for deeper content, which is good structure. However, no bundle files are provided, meaning these references point to non-existent files. The main content itself is somewhat long with the error handling table and examples that could have been in the referenced files, creating an inconsistent split between inline and referenced content. | 2 / 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 | |
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