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Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (backed by Jupiter).
---
author: luo-kai
name: oc-market-snapshot-9a970ff4dc87
version: 1.0.0
description: Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (backed by Jupiter).
license: MIT
metadata:
author: luokai0
version: "1.0"
category: python-tools
---
# Market Snapshot
You are an expert python engineer. Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (backed by Jupiter).
## 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 Market Snapshot
- **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
"""
MarketSnapshot — by luo-kai (Lous Creations)
Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (b
"""
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("market-snapshot")
class MarketSnapshot:
"""Main implementation of MarketSnapshot."""
def __init__(self, config: dict[str, Any] | None = None):
self.config = config or {}
self._ready = False
def setup(self) -> None:
logger.info("Setting up MarketSnapshot...")
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 = MarketSnapshot()
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
# Market Snapshot — Configuration
# Author: luo-kai (Lous Creations)
config = {
"name": "market-snapshot",
"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("market-snapshot")
def safe_run(func, *args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
logger.error(f"market-snapshot 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
- market-snapshot-advanced
- performance-optimization
- error-handling
- testing-expert
---
author: luo-kai
name: oc-market-snapshot-9a970ff4dc87
version: 1.0.0
description: Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (backed by Jupiter).
license: MIT
metadata:
author: luokai0
version: "1.0"
category: python-tools
---
# Market Snapshot
You are an expert python engineer. Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (backed by Jupiter).
## 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 Market Snapshot
- **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
"""
MarketSnapshot — by luo-kai (Lous Creations)
Fetch a token market snapshot (price/liquidity/volume) and return stable JSON (b
"""
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("market-snapshot")
class MarketSnapshot:
"""Main implementation of MarketSnapshot."""
def __init__(self, config: dict[str, Any] | None = None):
self.config = config or {}
self._ready = False
def setup(self) -> None:
logger.info("Setting up MarketSnapshot...")
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 = MarketSnapshot()
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
# Market Snapshot — Configuration
# Author: luo-kai (Lous Creations)
config = {
"name": "market-snapshot",
"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("market-snapshot")
def safe_run(func, *args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
logger.error(f"market-snapshot 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
- market-snapshot-advanced
- performance-optimization
- error-handling
- testing-expert
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.