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Found 11 Skills
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
Use when debugging Foundation Models issues — context exceeded, guardrail violations, slow generation, availability problems, unsupported language, or unexpected output. Systematic diagnostics with production crisis defense.
Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Also handles MCP setup and configuration.
AI Debugging Collaboration Solution. Convert console.log into HTTP requests to collect logs. After the user completes operations, AI can automatically view and analyze the logs without the need for screenshots or copying console content. Supports Claude Code, OpenCode, Cursor.
Analyzes a single MLflow trace to answer a user query about it. Use when the user provides a trace ID and asks to debug, investigate, find issues, root-cause errors, understand behavior, or analyze quality. Triggers on "analyze this trace", "what went wrong with this trace", "debug trace", "investigate trace", "why did this trace fail", "root cause this trace".
Enable and interpret TensorRT-LLM AutoDeploy FX graph text dumps via AD_DUMP_GRAPHS_DIR. Use when you need before/after graphs per transform, to locate subgraphs, or to confirm a rewrite ran. Paths and behavior are grounded in tensorrt_llm/_torch/auto_deploy (GraphWriter, BaseTransform). Complements ad-add-fusion-transformation.
AI-powered enterprise debugging orchestrator with Context7 integration, intelligent error pattern recognition, automated root cause analysis, predictive fix suggestions, and multi-process debugging coordination across 25+ languages and distributed systems
Centralized, extensible devtools panel for TanStack libraries with a plugin architecture.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Create effective debugging prompts—include error messages, stack traces, expected vs actual behavior, logs, and attempted solutions