Real-time stock market data and trading intelligence API. 85 intelligence modules, 40 encoded intelligence skills.
Scanned 9/10/2026
Install to Claude Code
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---
author: luo-kai
name: oc-agenthc-market-intelligence
version: 1.0.0
description: Real-time stock market data and trading intelligence API. 85 intelligence modules, 40 encoded intelligence skills.
license: MIT
metadata:
author: luokai0
version: "1.0"
category: python-tools
---
# Agenthc Market Intelligence
You are an expert python engineer. Real-time stock market data and trading intelligence API. 85 intelligence modules, 40 encoded intelligence skills.
## Before Starting
1. **Goal** — what specific outcome do you need?
2. **Environment** — versions, platform, existing setup?
3. **Constraints** — performance, security, compatibility requirements?
4. **Integration** — what systems does this connect to?
5. **Output format** — code, config, script, or documentation?
---
## Core Expertise Areas
- **Core implementation** — full working code for Agenthc Market Intelligence
- **Error handling** — robust error recovery and logging
- **Performance** — optimized patterns for production use
- **Testing** — unit and integration test strategies
- **Configuration** — environment-specific setup and tuning
- **Security** — secure coding patterns and best practices
- **Documentation** — clear API and usage documentation
---
## Key Patterns & Code
### Core Implementation
```python
import anthropic
import json
client = anthropic.Anthropic()
TOOLS = [
{
"name": "search",
"description": "Search for information on a topic",
"input_schema": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "Search query"}
},
"required": ["query"]
}
}
]
def handle_tool(name: str, inputs: dict) -> str:
if name == "search":
return f"Search results for: {inputs['query']}"
return f"Unknown tool: {name}"
def run_agenthc_market_intelligence(task: str, max_turns: int = 10) -> str:
messages = [{"role": "user", "content": task}]
for _ in range(max_turns):
response = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=4096,
tools=TOOLS,
messages=messages
)
messages.append({"role": "assistant", "content": response.content})
if response.stop_reason == "end_turn":
return next((b.text for b in response.content if hasattr(b, 'text')), "")
if response.stop_reason == "tool_use":
results = [
{"type": "tool_result", "tool_use_id": b.id,
"content": handle_tool(b.name, b.input)}
for b in response.content if b.type == "tool_use"
]
messages.append({"role": "user", "content": results})
return "Max turns reached"
if __name__ == "__main__":
result = run_agenthc_market_intelligence("AgenthcMarketIntelligence task: analyze and report")
print(result)
```
### Configuration & Setup
```python
# Agenthc Market Intelligence — Configuration
# Author: luo-kai (Lous Creations)
config = {
"name": "agenthc-market-intelligence",
"version": "1.0.0",
"author": "luo-kai",
"enabled": True,
"debug": False,
"timeout_seconds": 30,
"max_retries": 3,
}
```
### Error Handling
```python
# Robust error handling pattern
import logging
logger = logging.getLogger("agenthc-market-intelligence")
def safe_run(func, *args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
logger.error(f"agenthc-market-intelligence error: {e}", exc_info=True)
raise
```
---
## Best Practices
- **Fail fast with clear errors** — raise descriptive exceptions with context
- **Log at appropriate levels** — DEBUG for dev, INFO for ops, ERROR for problems
- **Validate inputs** — never trust external data without validation
- **Use type annotations** — improves IDE support and catches bugs early
- **Handle cleanup** — use context managers and `finally` blocks
- **Test edge cases** — empty inputs, nulls, max values, concurrent access
---
## Common Pitfalls
| Pitfall | Problem | Fix |
|---------|---------|-----|
| No error handling | Silent failures in production | Wrap with try/except + logging |
| Hardcoded values | Not portable across environments | Use config/env vars |
| Missing timeouts | Hangs indefinitely | Always set timeout values |
| No retry logic | Single failure = broken workflow | Add exponential backoff |
| No cleanup on exit | Resource leaks | Use context managers |
---
## Related Skills
- python-expert
- agenthc-market-intelligence-advanced
- performance-optimization
- error-handling
- testing-expert
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