error-handling
Implement robust backend error handling with custom classes, middleware, structured logging, and recovery patterns.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
154 skills found
Implement robust backend error handling with custom classes, middleware, structured logging, and recovery patterns.
A unified interface for integrating and managing LLM chat providers like OpenAI, Anthropic, Google, Azure, and Bedrock within LangChain applications.
Transcribe audio files (wav, mp3, ogg) to text using the Qwen ASR model. Fast, local-friendly, and requires no API keys.
Execute implementation plans in small, verifiable batches with pause-for-feedback checkpoints to prevent drift and ensure code quality.
Classical machine learning with scikit-learn. Use for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building robust ML pipelines in Python.
Create, register, and manage custom agent tools and MCP servers to extend AI agent capabilities with external APIs and custom logic.
Creates isolated git worktrees for parallel development, automatically handling directory selection, .gitignore safety checks, dependency installation, and baseline test verification.
Automate the migration of Netflix Conductor workflows to Temporal Python, including server orchestration, worker management, and workflow troubleshooting.
Automates production deployment workflows with version management, health checks, release tagging, and post-deployment monitoring.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Gate 2 development cycle skill that validates observability implementation, including structured logging, OpenTelemetry tracing, and instrumentation coverage, without modifying code.
Advanced multi-language debugging support with stack trace analysis, runtime error triage, and automated diagnostic tools for containerized and distributed systems.