Loading...
Loading...
Found 1,678 Skills
Debug Kubernetes pods, nodes, and workloads using kubectl debug. Covers ephemeral containers, pod copying, node debugging, debug profiles, and interactive troubleshooting sessions. Use when user mentions kubectl debug, debugging pods, ephemeral containers, node debugging, or interactive troubleshooting in Kubernetes clusters.
Rust debugging skill for systems programming. Use when debugging Rust binaries with GDB or LLDB, enabling Rust pretty-printers, interpreting panics and backtraces, debugging async/await with tokio-console, stepping through no_std code, or using dbg! and tracing macros effectively. Activates on queries about rust-gdb, rust-lldb, RUST_BACKTRACE, Rust panics, debugging async Rust, tokio-console, or pretty-printers.
Systematic debugging methodology — binary search isolation, hypothesis-driven debugging, reproducing issues, and root cause analysis. Use when debugging errors, unexpected behavior, or test failures.
Debug and troubleshoot common issues with the Orderly SDK including errors, WebSocket issues, authentication problems, and trading failures.
Diagnoses .NET Framework CLR activation issues using CLR activation logs (CLRLoad logs) produced by mscoree.dll. Use when: the shim picks the wrong runtime, fails to load any runtime, shows unexpected .NET 3.5 Feature-on-Demand (FOD) dialogs, unexpectedly does NOT show FOD dialogs, loads both v2 and v4 into the same process causing failures, or any time someone is wondering "what is happening with .NET Framework activation?"
Use when debugging a Nemo Gym run or reward profiling job. Covers rollout collection failures, empty or partial JSONL outputs, stale materialized inputs, verifier/schema errors, Ray or Slurm issues, vLLM readiness, judge failures, tool/sandbox failures, cache problems, and throughput bottlenecks.
Evidence-driven investigation for network, streaming, and protocol-layer bugs. Use when debugging connection resets (ECONNRESET, HTTP/2 RST_STREAM, INTERNAL_ERROR), SSE or long-polling stalls, fixed-time connection drops, CDN/proxy/CGNAT idle timeouts, or any incident where symptoms do not match the obvious cause. Applies falsification-first methodology — layered isolation experiments to pin down the responsible network layer, env-gated runtime instrumentation for non-invasive observation, and counter-review agent teams to challenge single-cause assumptions. Strongly trigger on "socket closed unexpectedly", "stream interrupted", "ECONNRESET", "HTTP/2 INTERNAL_ERROR", "fails after N seconds", "works sometimes but not always", "upstream silent for X seconds", or any scenario where the investigator might jump to conclusions before evidence. Generalizes to any multi-layer system investigation where assumption-first thinking is the failure mode.
4-phase root cause debugging: understand bugs before fixing.
Use when RLM requirement involves debugging a bug, test failure, or unexpected behavior. Insert Phase 1.5 between Phase 1 and Phase 2 to perform systematic root cause analysis before attempting any fixes.
Salesforce debug log analysis and troubleshooting with 100-point scoring. TRIGGER when: user analyzes debug logs, hits governor limits, reads stack traces, or touches .log files from Salesforce orgs. DO NOT TRIGGER when: running Apex tests (use running-apex-tests), generating or fixing Apex code (use generating-apex), or Agentforce session tracing (use observing-agentforce).
Debugs why session recordings aren't appearing in the local dev environment. Use when a developer reports that local replay ingestion isn't working, recordings aren't showing up despite /s calls, or the replay pipeline seems broken after hogli start. Covers the full local pipeline: SDK capture, Caddy proxy, capture-replay (Rust), Kafka, ingestion-sessionreplay (Node), recording-api (Node), SeaweedFS, and common failure modes like orphaned processes, stuck phrocs workers, and trigger misconfiguration.
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix