api-response-optimization
Optimizes API performance through payload reduction, caching strategies, and compression techniques. Use when improving API response times, reducing bandwidth usage, or implementing efficient caching.
82
78%
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-response-optimization/skills/api-response-optimization/SKILL.mdQuality
Discovery
77%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 solid description that clearly communicates both what the skill does and when to use it, with specific concrete actions listed. Its main weaknesses are moderate trigger term coverage (missing natural user phrasings like 'slow API' or 'latency') and some potential overlap with general backend optimization or caching-focused skills.
Suggestions
Add more natural user trigger terms like 'slow API', 'latency', 'API speed', 'large payloads', or 'gzip' to improve discoverability when users describe problems in everyday language.
Strengthen distinctiveness by specifying the types of APIs (REST, GraphQL) or clarifying boundaries with related skills (e.g., 'Does not cover API design or authentication').
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'payload reduction', 'caching strategies', and 'compression techniques'. These are distinct, actionable optimization approaches rather than vague language. | 3 / 3 |
Completeness | Clearly answers both 'what' (optimizes API performance through payload reduction, caching strategies, compression techniques) and 'when' (improving API response times, reducing bandwidth usage, implementing efficient caching) with an explicit 'Use when' clause. | 3 / 3 |
Trigger Term Quality | Includes relevant terms like 'API performance', 'response times', 'bandwidth', and 'caching', but misses common user variations like 'slow API', 'latency', 'API optimization', 'gzip', 'minify payload', or 'rate limiting'. The terms are somewhat technical rather than how users naturally phrase requests. | 2 / 3 |
Distinctiveness Conflict Risk | While 'API performance optimization' is a reasonably specific niche, terms like 'caching strategies' could overlap with general backend/infrastructure skills, and 'compression techniques' could conflict with file compression or data processing skills. The API focus helps but doesn't fully eliminate overlap risk. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
79%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, concise skill with excellent actionable code examples covering three key API optimization techniques. Its main weakness is the lack of an explicit optimization workflow with measurement/validation steps—there's no guidance on how to verify that optimizations actually hit the stated performance targets. The content is well-structured but could benefit from a clear before/after measurement process.
Suggestions
Add a measurement/validation workflow: e.g., 'Before optimizing, benchmark with `curl -w` or APM tools. After each change, re-measure and compare against Performance Targets table.'
Include a brief feedback loop for the optimization process: measure → apply optimization → re-measure → iterate if targets not met.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. No unnecessary explanations of what APIs, caching, or compression are. Every section delivers actionable content without preamble. | 3 / 3 |
Actionability | All three main techniques include fully executable JavaScript code examples that are copy-paste ready. The checklist and performance targets table provide concrete, specific guidance. | 3 / 3 |
Workflow Clarity | The checklist provides a reasonable sequence of optimization steps, but there's no explicit workflow for applying these optimizations in order, no validation/verification steps (e.g., how to measure before/after), and no feedback loop for confirming improvements against the performance targets. | 2 / 3 |
Progressive Disclosure | The content is well-organized with clear section headers, but it's somewhat monolithic—the checklist, best practices, and performance targets could be separated or the skill could reference deeper guides for topics like N+1 query prevention or APM tool setup. For a skill of this size (~60 lines), the structure is adequate but not exemplary. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- secondsky/claude-skills
- Commit
88da5ff
- Reviewed
Table of Contents
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