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.
Best use case
api-response-optimization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Optimizes API performance through payload reduction, caching strategies, and compression techniques. Use when improving API response times, reducing bandwidth usage, or implementing efficient caching.
Teams using api-response-optimization should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/api-response-optimization/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How api-response-optimization Compares
| Feature / Agent | api-response-optimization | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Optimizes API performance through payload reduction, caching strategies, and compression techniques. Use when improving API response times, reducing bandwidth usage, or implementing efficient caching.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# API Response Optimization
Reduce payload sizes, implement caching, and enable compression for faster APIs.
## Sparse Fieldsets
```javascript
// Allow clients to select fields: GET /users?fields=id,name,email
app.get('/users', async (req, res) => {
const fields = req.query.fields?.split(',') || null;
const users = await User.find({}, fields?.join(' '));
res.json(users);
});
```
## HTTP Caching Headers
```javascript
app.get('/products/:id', async (req, res) => {
const product = await Product.findById(req.params.id);
const etag = crypto.createHash('md5').update(JSON.stringify(product)).digest('hex');
if (req.headers['if-none-match'] === etag) {
return res.status(304).end();
}
res.set({
'Cache-Control': 'public, max-age=3600',
'ETag': etag
});
res.json(product);
});
```
## Response Compression
```javascript
const compression = require('compression');
app.use(compression({
filter: (req, res) => {
if (req.headers['x-no-compression']) return false;
return compression.filter(req, res);
},
level: 6 // Balance between speed and compression
}));
```
## Performance Targets
| Metric | Target |
|--------|--------|
| Response time | <100ms (from 500ms) |
| Payload size | <50KB (from 500KB) |
| Server CPU | <30% (from 80%) |
## Optimization Checklist
- [ ] Remove sensitive/unnecessary fields from responses
- [ ] Implement sparse fieldsets
- [ ] Add ETag/Last-Modified headers
- [ ] Enable gzip/brotli compression
- [ ] Use pagination for collections
- [ ] Eager load to prevent N+1 queries
- [ ] Monitor with APM tools
## Best Practices
- Cache immutable resources aggressively
- Use short TTL for frequently changing data
- Invalidate cache on writes
- Compress responses >1KB
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