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Oc Patiently Ai

ASecurity

Patiently AI simplifies medical documents for patients.

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  • Added September 10, 2026
testingpythonrustgotestingapisecurityperformancedocumentation

Works with

  • api

Security analysis

A100/100

Scanned September 10, 2026

npx -y skills add luokai0/ai-agent-skills-by-luo-kai --skill oc-patiently-ai --agent claude-code

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SKILL.md
---
author: luo-kai
name: oc-patiently-ai
version: 1.0.0
description: Patiently AI simplifies medical documents for patients.
license: MIT
metadata:
  author: luokai0
  version: "1.0"
  category: python-tools
---

# Patiently Ai

You are an expert python engineer. Patiently AI simplifies medical documents for patients.

## 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 Patiently Ai
- **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
#!/usr/bin/env python3
"""
PatientlyAi — by luo-kai (Lous Creations)
Patiently AI simplifies medical documents for patients.
"""
from __future__ import annotations
import logging, sys
from pathlib import Path
from typing import Any

logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
logger = logging.getLogger("patiently-ai")

class PatientlyAi:
    """Main implementation of PatientlyAi."""

    def __init__(self, config: dict[str, Any] | None = None):
        self.config = config or {}
        self._ready = False

    def setup(self) -> None:
        logger.info("Setting up PatientlyAi...")
        self._ready = True

    def run(self, input_data: Any) -> dict[str, Any]:
        if not self._ready:
            self.setup()
        logger.info("Processing...")
        result = self._process(input_data)
        return {"success": True, "result": result, "author": "luo-kai"}

    def _process(self, data: Any) -> Any:
        return data  # Override with real logic

def main() -> int:
    tool = PatientlyAi()
    try:
        tool.setup()
        result = tool.run(sys.argv[1:])
        print(f"Done: {result['result']}")
        return 0
    except Exception as e:
        logger.error(f"Error: {e}")
        return 1

if __name__ == "__main__":
    sys.exit(main())
```

### Configuration & Setup
```python
# Patiently Ai — Configuration
# Author: luo-kai (Lous Creations)

config = {
    "name": "patiently-ai",
    "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("patiently-ai")

def safe_run(func, *args, **kwargs):
    try:
        return func(*args, **kwargs)
    except Exception as e:
        logger.error(f"patiently-ai 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
- patiently-ai-advanced
- performance-optimization
- error-handling
- testing-expert

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