--- author: luo-kai name: oc-near-email-reporter version: 1.0.0 description: Send NEAR reports and alerts via email with SMTP configuration, scheduling, and automatic reporting. license: MIT metadata: author: luokai0 version: "1.0" category: python-tools --- # Near Email Reporter You are an expert python engineer. Send NEAR reports and alerts via email with SMTP configuration, scheduling, and automatic reporting. ## 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 Near Email Reporter - **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 """ NearEmailReporter — by luo-kai (Lous Creations) Send NEAR reports and alerts via email with SMTP configuration, scheduling, and """ 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("near-email-reporter") class NearEmailReporter: """Main implementation of NearEmailReporter.""" def __init__(self, config: dict[str, Any] | None = None): self.config = config or {} self._ready = False def setup(self) -> None: logger.info("Setting up NearEmailReporter...") 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 = NearEmailReporter() 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 # Near Email Reporter — Configuration # Author: luo-kai (Lous Creations) config = { "name": "near-email-reporter", "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("near-email-reporter") def safe_run(func, *args, **kwargs): try: return func(*args, **kwargs) except Exception as e: logger.error(f"near-email-reporter 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 - near-email-reporter-advanced - performance-optimization - error-handling - testing-expert --- Source attribution: luokai0 Original project: https://github.com/luokai0/ai-agent-skills-by-luo-kai/blob/main/ai-agent-skills/18-ai-agents-and-automation%20%28by%20Luo%20Kai%29/16-other-agents/oc-near-email-reporter/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: luokai0 Original project: https://github.com/luokai0/ai-agent-skills-by-luo-kai/blob/main/ai-agent-skills/18-ai-agents-and-automation%20%28by%20Luo%20Kai%29/16-other-agents/oc-near-email-reporter/SKILL.md Attribution basis: Source repository record Fields of work: Marketing Roles: Email Marketer, Growth Marketer, Marketing Analyst Specialties: API Tools: Email (SMTP/IMAP) Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 374ad71cf076b7a9110a264371d45488a9e4e65b001f5dff7ecd20cc1bf5fcd7