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Found 209 Skills
Analyze application logs to detect errors, patterns, anomalies, and generate insights. Use when troubleshooting issues or analyzing system behavior.
Diagnose and fix bugs with root-cause analysis and verification. Use when you have a concrete issue report, failing behavior, runtime error, or test regression that should be resolved safely. For ambiguous, high-risk, or broad-scope issues, stop and route to write-plan first.
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
Break the Loop - Deep Bug Analysis
Hypothesis → Prediction → Test → Revise with explicit falsification. Use for debugging, feature experimentation, performance investigation, and A/B testing design.
Follow this sub-process when fixing bugs — turn the verbal description of "problem found" into a closed loop from verification to repair, leaving three documents: problem report, root cause analysis, and repair record. This process adds a buffer between "seeing the problem" and "starting to modify code" to avoid common pitfalls: the problem description in your mind disappears after the fix, you only fix the surface without analyzing the root cause, the scope of repair expands and cannot be traced, and you don't know if the fix is correct without verification after modification. This skill only acts as a router, deciding which of report / analyze / fix to proceed with based on existing artifacts. For simple problems that can be identified at a glance, a fast track will be taken, skipping the two middle steps and only retaining the fix-note.
Apply systematic problem-solving methodologies to complex challenges. Use when the user says "guide me through structured problem solving" or "I want to crack this challenge with guided problem solving techniques"
Find and fix issues from Sentry using MCP. Use when asked to fix Sentry errors, debug production issues, investigate exceptions, or resolve bugs reported in Sentry. Methodically analyzes stack traces, breadcrumbs, traces, and context to identify root causes.
Diagnose why a product metric changed (dropped, spiked, or plateaued) by orchestrating breakdowns, actors, paths, lifecycle, retention, and annotations queries. Use when the user reports an anomaly, asks "why did X change?", or needs root-cause analysis for a trend, funnel, retention, stickiness, or lifecycle metric.
Write the canonical engineering record of a fixed bug — root cause, mechanism, fix, validation, and how it slipped through. Engineer-audience, code identifiers welcome. Use after a debug session lands a fix, before closing the ticket. Trigger on /post-mortem, when the user says "write the post-mortem / postmortem / RCA / root cause analysis", "document this fix", "write up the root cause", "close out this bug with a writeup", or hands you a fixed-and-validated bug and asks for the writeup.
End-to-end pipeline from unlabeled ml_app traces to a bootstrapped evaluator suite. Runs trace classification → root cause analysis → eval bootstrap in sequence with user checkpoints. Use when user says "run the eval pipeline", "go from traces to evals", "bootstrap evals end to end", "classify then RCA then bootstrap", "build an eval set from scratch", or wants a guided walkthrough from production data to evaluator code.
Extract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use after running VLM evaluation when you have a predictions JSON and need to identify failure cases for DEFT root cause analysis on a binary-classification VLM workflow.