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APIClaw Skills

The data infrastructure built for agents.
Currently powering Amazon commerce with 200M+ products, 1B+ reviews, and real-time signals.

Website • Get API Key • Discord • Quick Start • API Reference

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What is APIClaw?

APIClaw is the data infrastructure built for agents. Not a scraping API. Not a human dashboard. A purpose-built data layer that gives your AI agents direct access to Amazon commerce signals — 200M+ indexed products, 2+ years of history, and 1B+ reviews pre-processed into structured insights. Clean JSON, real-time, agent-ready.

This repo contains two agent skills that let any AI assistant use APIClaw instantly:

Skill	Description	Best For
📦 apiclaw/	Data layer overview, 6 API endpoints, quick integration	Getting started, agent tool-calling
🎯 amazon-analysis/	14 selection strategies, market validation, competitor intelligence, risk assessment	Deep product research, autonomous sourcing agents

Quick Start

1. Install the Skills

npx skills add SerendipityOneInc/APIClaw-Skills

You'll be prompted to select which skills to install:

• APIClaw — Commerce Data for AI Agents (general overview, 6 endpoints)
• Amazon Product Research & Seller Analytics (deep analysis, 14 strategies)

Or clone manually:

git clone https://github.com/SerendipityOneInc/APIClaw-Skills.git

2. Set Your API Key

export APICLAW_API_KEY='hms_live_xxx'   # Get yours free at apiclaw.io/en/api-keys

🎁 Free tier: 1,000 credits on signup. 1 credit = 1 API call. No credit card required.

3. Try It

Ask your AI agent:

"Analyze the competitive landscape for wireless earbuds under $50 on Amazon US"

Or use the CLI directly:

python amazon-analysis/scripts/apiclaw.py products --keyword "wireless earbuds" --mode competitive_landscape

Example: Product Search

curl -X POST 'https://api.apiclaw.io/openapi/v2/products/search' \
  -H 'Authorization: Bearer hms_live_xxx' \
  -H 'Content-Type: application/json' \
  -d '{
    "keyword": "wireless earbuds",
    "mode": "beginner",
    "priceMax": 50,
    "pageSize": 3
  }'

Example response (simplified):

{
  "products": [
    {
      "asin": "B0D5CRV4KL",
      "title": "Wireless Earbuds Bluetooth 5.3 ...",
      "price": 29.99,
      "rating": 4.5,
      "ratingCount": 12847,
      "bsrRank": 15,
      "atLeastMonthlySales": 8500,
      "brand": "SoundCore",
      "profitMargin": 0.42
    }
  ]
}

Note: This is a simplified example. Actual responses include additional fields. See API reference for full field list.

API Endpoints

Endpoint	Description	Example Use Case
🔍 products/search	Product search with 14 preset modes, 20+ filters	"Find running shoes under $80 with 4+ stars"
📊 markets/search	Market-level metrics — concentration, brand share, pricing	"How competitive is the yoga mat market?"
🏷️ products/competitor-lookup	Competitor discovery by keyword, brand, or ASIN	"Who are the top sellers in this niche?"
⚡ realtime/product	Real-time product details — reviews, features, variants	"Get current details for ASIN B0D5CRV4KL"
💬 reviews/analyze	AI-powered review insights — sentiment, pain points	"What do customers love/hate about this product?"
📁 categories	Amazon category tree navigation	"Show subcategories under Electronics"

Base URL: https://api.apiclaw.io/openapi/v2
Auth: Authorization: Bearer $APICLAW_API_KEY
Method: All endpoints use POST with JSON body

14 Product Search Modes

The products/search endpoint supports 14 preset modes for different research strategies:

Mode	Strategy	Target
beginner	Low competition, easy entry	New sellers
fast-movers	High sales velocity	Quick revenue
emerging	Rising trends, low saturation	Early movers
long-tail	Niche keywords, steady demand	Sustainable income
underserved	High demand, few sellers	Market gaps
new-release	Recently launched products	Trending items
fbm-friendly	Suitable for merchant fulfillment	Low-investment start
low-price	Budget-friendly products	Volume strategy
single-variant	Simple listings, no variants	Easy management
high-demand-low-barrier	High sales, low review barrier	Scalable entry
broad-catalog	Wide product range analysis	Category overview
selective-catalog	Curated high-quality picks	Premium selection
speculative	High-risk, high-reward opportunities	Aggressive strategy
top-bsr	Best Seller Rank leaders	Market leaders

Use Cases

• 🔎 Product Research — Find profitable niches with low competition
• 📈 Competitor Monitoring — Track pricing, reviews, and BSR changes
• ✍️ Listing Optimization — AI-powered review analysis to improve your listings
• 🚀 Market Entry Analysis — Evaluate market size, competition, and profit potential
• 📊 Trend Detection — Spot rising products and emerging categories

Project Structure

├── apiclaw/                        # General skill (lightweight)
│   ├── SKILL.md                      # Capabilities overview, quick start
│   └── references/
│       └── openapi-reference.md      # API field reference
│
├── amazon-analysis/                # Amazon deep skill
│   ├── SKILL.md                      # Intent routing, workflows, evaluation criteria
│   ├── references/
│   │   ├── reference.md              # Full API reference
│   │   ├── scenarios-composite.md    # Comprehensive recommendations
│   │   ├── scenarios-eval.md         # Product evaluation, risk, reviews
│   │   ├── scenarios-pricing.md      # Pricing strategy, profit estimation
│   │   ├── scenarios-ops.md          # Market monitoring, alerts
│   │   ├── scenarios-expand.md       # Expansion, trends
│   │   └── scenarios-listing.md      # Listing writing, optimization
│   └── scripts/
│       └── apiclaw.py                # CLI — 8 subcommands, 14 preset modes

Requirements

• Python 3.8+ (stdlib only, zero pip dependencies)
• APIClaw API Key (get one free)

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Community

• 💬 Discord — Chat, get help, share what you're building
• 🐛 Issues — Bug reports and feature requests
• 📖 API Docs — Full API documentation

License

MIT © SerendipityOne Inc.

• 📖 API Docs — Full API documentation

License

MIT © SerendipityOne Inc.