Api Response Optimization logo

Api Response Optimization

Community
secondsky
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.

Overview

Publishersecondsky
Repositoryclaude-skills
Skill nameapi-response-optimization
Stars
219
Forks
31
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by secondsky on GitHub. Read the source before you install it.

Installation

Install the Api Response Optimization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/secondsky/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/plugins/api-response-optimization/skills/api-response-optimization .claude/skills/api-response-optimization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Response Optimization in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Api Response Optimization on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Api Response Optimization is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

MetricTarget
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
  • Profile before optimizing

Frequently asked questions

What does the Api Response Optimization AI 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.

Why use Api Response Optimization on TypingMind?

Because you install it once and use it with any model. Api Response Optimization is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Api Response Optimization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/secondsky/claude-skills/tree/main/plugins/api-response-optimization/skills/api-response-optimization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Api Response Optimization?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Api Response Optimization?

As many as you like. As long as a model supports skills, you can use Api Response Optimization with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Api Response Optimization AI skill free?

Yes. It is published on GitHub by secondsky under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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