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Found 27 Skills
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
A disciplined diagnostic loop for tricky bugs and performance regressions. Reproduce → Minimize → Hypothesize → Instrument → Fix → Regression-test. Use this when the user says "diagnose this" / "debug this", reports a bug, states that something is broken/throwing errors/failing, or describes a performance regression.
Use when working with error diagnostics smart debug
This skill should be used when the user asks to "investigate an issue", "debug a problem", "find out why something is slow", "check error rates", "analyze user behavior", "understand a production incident", "query telemetry data", "look at logs", "check traces", "examine spans", "analyze RUM data", "check frontend performance", "investigate backend latency", "find transaction data", "check payment metrics", "analyze user journeys", or wants to answer questions using observability data from logs, metrics, traces, RUM, or APM - this is the gateway skill for deciding where to look first.
Search Sourcegraph-indexed codebases for patterns, examples, and system understanding. Triggers on implementation questions, debugging, or "how does X work" queries.
This skill should be used when encountering bugs, errors, failing tests, or unexpected behavior. Provides systematic debugging with evidence-based root cause investigation using a four-stage framework.
Systematic root-cause debugging: reproduce, investigate, hypothesize, fix with verification. Use when asked to "debug this", "fix this bug", "why is this failing", "troubleshoot", or mentions errors, stack traces, broken tests, flaky tests, regressions, or unexpected behavior.
Systematic evidence-based debugging using runtime logs. Generates hypotheses, instruments code with NDJSON logs, guides reproduction, analyzes log evidence, and iterates until root cause is proven with cited log lines. Use when the user reports a bug, unexpected behavior, or asks to debug an issue.
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".
Systematically diagnose and resolve bugs through conversational investigation and root cause analysis
Intelligent Core Web Vitals analysis with automated workflows and decision trees. Measures LCP, CLS, INP with guided debugging that automatically determines follow-up analysis based on results. Includes workflows for LCP deep dive (5 phases), CLS investigation (loading vs interaction), INP debugging (latency breakdown + attribution), and cross-skill integration with loading, interaction, and media skills. Use when the user asks about Core Web Vitals, LCP optimization, layout shifts, or interaction responsiveness. Compatible with Chrome DevTools MCP.