clade-performance-tuning
Optimize Anthropic API latency — streaming, prompt caching, model selection, Use when working with performance-tuning patterns. connection reuse, and parallel requests. Trigger with "anthropic slow", "claude latency", "speed up anthropic", "anthropic performance", "claude response time".
Best use case
clade-performance-tuning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Optimize Anthropic API latency — streaming, prompt caching, model selection, Use when working with performance-tuning patterns. connection reuse, and parallel requests. Trigger with "anthropic slow", "claude latency", "speed up anthropic", "anthropic performance", "claude response time".
Teams using clade-performance-tuning 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/clade-performance-tuning/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How clade-performance-tuning Compares
| Feature / Agent | clade-performance-tuning | 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?
Optimize Anthropic API latency — streaming, prompt caching, model selection, Use when working with performance-tuning patterns. connection reuse, and parallel requests. Trigger with "anthropic slow", "claude latency", "speed up anthropic", "anthropic performance", "claude response time".
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.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
ChatGPT vs Claude for Agent Skills
Compare ChatGPT and Claude for AI agent skills across coding, writing, research, and reusable workflow execution.
SKILL.md Source
# Anthropic Performance Tuning
## Overview
Claude latency has two components: **time to first token (TTFT)** and **tokens per second (TPS)**. Different strategies target each.
## Latency Benchmarks (approximate)
| Model | TTFT (p50) | TTFT (p95) | Output TPS |
|-------|-----------|-----------|------------|
| Claude Haiku 4.5 | 200ms | 600ms | ~150 |
| Claude Sonnet 4 | 400ms | 1.2s | ~90 |
| Claude Opus 4 | 800ms | 2.5s | ~40 |
## Optimization Strategies
## Instructions
### Step 1: Always Stream
```typescript
// Streaming delivers the first token ASAP — user sees response instantly
// instead of waiting for the full response to generate
const stream = client.messages.stream({
model: 'claude-sonnet-4-20250514',
max_tokens: 1024,
messages,
});
// First token arrives in ~400ms (Sonnet)
// Full response may take 5-10s, but user sees progress immediately
for await (const event of stream) {
if (event.type === 'content_block_delta') {
yield event.delta.text;
}
}
```
### Step 2: Prompt Caching — Faster TTFT
```typescript
// Cached prompts skip re-processing — dramatically lower TTFT for large system prompts
const message = await client.messages.create({
model: 'claude-sonnet-4-20250514',
max_tokens: 1024,
system: [{
type: 'text',
text: largeSystemPrompt, // 10K+ tokens
cache_control: { type: 'ephemeral' },
}],
messages,
}, {
headers: { 'claude-beta': 'prompt-caching-2024-07-31' },
});
// TTFT drops from ~2s to ~500ms on cache hit with large prompts
```
### Step 3: Use Haiku for Speed-Critical Paths
```typescript
// Haiku is 2-4x faster than Sonnet with 80% quality for many tasks
// Use for: classification, extraction, simple Q&A, routing decisions
const route = await client.messages.create({
model: 'claude-haiku-4-5-20251001', // 200ms TTFT
max_tokens: 10,
system: 'Classify the intent. Reply with exactly one word: search, create, update, delete.',
messages: [{ role: 'user', content: userInput }],
});
// Then use Sonnet/Opus for the actual task
```
### Step 4: Reuse Client Instance
```typescript
// BAD — creates new connection pool per request
app.get('/api/chat', async (req, res) => {
const client = new Anthropic(); // DON'T
// ...
});
// GOOD — single client shared across requests
const client = new Anthropic(); // Module-level singleton
app.get('/api/chat', async (req, res) => {
const message = await client.messages.create({ ... });
// ...
});
```
### Step 5: Parallel Requests
```typescript
// When you need multiple independent Claude calls, fire them in parallel
const [summary, sentiment, entities] = await Promise.all([
client.messages.create({ model: 'claude-haiku-4-5-20251001', max_tokens: 200,
messages: [{ role: 'user', content: `Summarize: ${text}` }] }),
client.messages.create({ model: 'claude-haiku-4-5-20251001', max_tokens: 20,
messages: [{ role: 'user', content: `Sentiment (positive/negative/neutral): ${text}` }] }),
client.messages.create({ model: 'claude-haiku-4-5-20251001', max_tokens: 200,
messages: [{ role: 'user', content: `Extract named entities from: ${text}` }] }),
]);
```
### Step 6: Minimize Output Tokens
```typescript
// Fewer output tokens = faster response
system: 'Be extremely concise. Use bullet points, not paragraphs.',
// Set tight max_tokens
max_tokens: 256, // Don't use 4096 for short answers
```
## Output
- Streaming enabled for all user-facing responses (first token in ~400ms with Sonnet)
- Prompt caching reducing TTFT for large system prompts
- Model routing to Haiku for speed-critical classification/routing tasks
- Client instance reused across requests (no per-request connection overhead)
- Parallel requests firing independent Claude calls concurrently
## Error Handling
| Issue | Cause | Fix |
|-------|-------|-----|
| TTFT > 3s | Large uncached prompt | Enable prompt caching |
| Slow output | Using Opus for simple tasks | Downgrade to Haiku/Sonnet |
| Timeouts | Long generation + default timeout | `new Anthropic({ timeout: 120_000 })` |
| 529 overloaded | API capacity | SDK auto-retries; add fallback model |
## Examples
See Latency Benchmarks table and six numbered strategy sections above, each with complete TypeScript code examples.
## Resources
- [Streaming Docs](https://docs.anthropic.com/en/api/messages-streaming)
- [Prompt Caching](https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching)
- [Models Comparison](https://docs.anthropic.com/en/docs/about-claude/models)
## Next Steps
See `clade-deploy-integration` for production deployment patterns.
## Prerequisites
- Completed `clade-install-auth`
- User-facing application where latency matters
- Understanding of streaming and async patternsRelated Skills
running-performance-tests
Execute load testing, stress testing, and performance benchmarking. Use when performing specialized testing. Trigger with phrases like "run load tests", "test performance", or "benchmark the system".
workhuman-performance-tuning
Workhuman performance tuning for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman performance tuning".
workhuman-cost-tuning
Workhuman cost tuning for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman cost tuning".
wispr-performance-tuning
Wispr Flow performance tuning for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr performance tuning".
wispr-cost-tuning
Wispr Flow cost tuning for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr cost tuning".
windsurf-performance-tuning
Optimize Windsurf IDE performance: indexing speed, Cascade responsiveness, and memory usage. Use when Windsurf is slow, indexing takes too long, Cascade times out, or the IDE uses too much memory. Trigger with phrases like "windsurf slow", "windsurf performance", "optimize windsurf", "windsurf memory", "cascade slow", "indexing slow".
windsurf-cost-tuning
Optimize Windsurf licensing costs through seat management, tier selection, and credit monitoring. Use when analyzing Windsurf billing, reducing per-seat costs, or implementing usage monitoring and budget controls. Trigger with phrases like "windsurf cost", "windsurf billing", "reduce windsurf costs", "windsurf pricing", "windsurf budget".
webflow-performance-tuning
Optimize Webflow API performance with response caching, bulk endpoint batching, CDN-cached live item reads, pagination optimization, and connection pooling. Use when experiencing slow API responses or optimizing request throughput. Trigger with phrases like "webflow performance", "optimize webflow", "webflow latency", "webflow caching", "webflow slow", "webflow batch".
webflow-cost-tuning
Optimize Webflow costs through plan selection, CDN read optimization, bulk endpoint usage, and API usage monitoring with budget alerts. Use when analyzing Webflow billing, reducing API costs, or implementing usage monitoring for Webflow integrations. Trigger with phrases like "webflow cost", "webflow billing", "reduce webflow costs", "webflow pricing", "webflow budget".
vercel-performance-tuning
Optimize Vercel deployment performance with caching, bundle optimization, and cold start reduction. Use when experiencing slow page loads, optimizing Core Web Vitals, or reducing serverless function cold start times. Trigger with phrases like "vercel performance", "optimize vercel", "vercel latency", "vercel caching", "vercel slow", "vercel cold start".
vercel-cost-tuning
Optimize Vercel costs through plan selection, function efficiency, and usage monitoring. Use when analyzing Vercel billing, reducing function execution costs, or implementing spend management and budget alerts. Trigger with phrases like "vercel cost", "vercel billing", "reduce vercel costs", "vercel pricing", "vercel expensive", "vercel budget".
veeva-performance-tuning
Veeva Vault performance tuning for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva performance tuning".