1.7천건 · 관련도순
Retrieve an EagleEye traceId, an identifier linking a request across logs, using Arthas without changing application code. Observe request-handling methods, capture parameters when needed, and inspect method calls and timings to investigate problems.
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Investigate slow or failing requests in Google Cloud using Cloud Trace. Filter traces by duration or error status, inspect spans representing individual operations, and retrieve related Cloud Logging entries to investigate bottlenecks and exceptions.
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Profile app launches and individual user flows in iOS Simulator with ETTrace. Collect traces with readable function names, identify CPU-heavy call stacks, and compare performance changes when recording conditions are consistent.
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Use this skill when building or maintaining a Requirements Traceability Matrix (RTM) on a Salesforce project: one row per requirement, columns for source, user-story id(s), test-case id(s), defect id(s), sprint, release, and status. Covers forward traceability (req → story → code → test) and backward traceability (test → req). Trigger keywords: RTM, requirements traceability matrix, audit trail for salesforce delivery, traceability for steerco, deferred requirement tracking, regulatory traceability. NOT for eliciting the requirements in the first place — use admin/requirements-gathering-for-sf. NOT for user-story authoring — use admin/user-story-writing-for-salesforce. NOT for UAT test design — use admin/uat-test-case-design. NOT for Apex test design — use apex/test-class-standards. NOT for backlog prioritization — use admin/moscow-prioritization-for-sf-backlog. More triggers: traceability.md, build-layer traceability, REQ-XXX and FG-XXX id mapping, artefact-to-requirement orphan report, coverage-gap report, check_rtm.py --manifest-dir, owning run-time agent column, design decision ref column, metadata API name in a traceability row.
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Inspect existing LLM application records in Arize to investigate errors, slow operations, or behavior changes. Export traces, which group related operations, or individual operations and conversation sessions as JSON using the ax command-line tool.
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Use this skill when the user runs doca_dpa_hl_tracer to capture/decode DPA-side traces at the programming-events layer (kernel entry/exit, sync points, comm primitive calls, RDMA WR submission, completion drain) — picking TRACE vs CRIT, tuning the JSON config (file-size limits + file_size_limit_policy, thread priorities/cores), decoding against the matching DPA-side ELF, or diagnosing empty/noisy captures. Trigger even when the user does not explicitly mention "DOCA DPA tracer" or "high-level tracer" — typical implicit phrasings include "DPA kernel returns wrong result but host completions look clean", "kernel-entry to first-comm latency is huge", "RDMA WR to drain gap on the DPA", "trace file truncated mid-run", "TRACE doubled my DPA latency", or "tracer wrote a file but parser shows zero events". Refuse and route elsewhere for writing DPA kernels, DPA-Comms/DPA-Verbs programming, raw per-cycle DPA profiling, host-side doca-dpa debugging, or production DPA telemetry — those belong to other skills.
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Collect, normalize, and structure execution traces from instrumented programs (strace, ltrace) into JSON format for downstream analysis. Use when working with system call traces, library call traces, or execution logs that need to be analyzed for debugging, test case reproduction, or verification. Supports parsing strace/ltrace output, filtering noise, extracting debug information, and preparing traces for bug analysis or reproduction workflows.
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Operate NVIDIA Nsight Graphics from the command line to capture application frames and GPU activity. Summarize performance traces, analyze existing capture files through ngfx-replay, and check installed versions and compatibility before starting an investigation.
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SQL discipline for querying Pulp Perfetto traces (.pftrace) with trace_processor — idempotent CREATE OR REPLACE PERFETTO views, GLOB not LIKE, dur = -1 incomplete-slice handling, EXTRACT_ARG for span args, joining on stable utid/upid, SPAN_JOIN PARTITIONED, and the draft→validate→execute loop. Ships Pulp's CPU/UI trace stdlib plus closed GPU startup, health, and probe views. TRIGGER when writing or debugging SQL over a .pftrace, when `pulp trace query` returns wrong/empty rows, or when the trace-analysis skill needs a query primitive.
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Create a requirements traceability matrix linking requirements to design, test, and delivery. Use when the user says "traceability matrix", "RTM", "requirements traceability", "link requirements to tests", "trace requirements", "coverage matrix", "are all requirements tested", "requirements coverage", "forward traceability", "backward traceability" - even if they don't explicitly say "traceability matrix".
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Diagnose running Java applications with Arthas. Follow guides for high CPU usage, retrieving EagleEye request tracking IDs, and inspecting Spring configuration and managed objects, then summarize evidence and next steps.
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Launch an SGLang server, run a quick accuracy check, and capture an execution trace for performance inspection. Return the trace location and generated files, ready to open in Perfetto or Chrome tracing.
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Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs.
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Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs. NOT for OTel metrics/logs pipelines, vendor backend setup (Datadog/Honeycomb/Jaeger/Tempo), or browser RUM tracing.
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Recommend, create, preview, and attach Coval trace-based metrics from OpenTelemetry spans. Use when a user has Coval traces and wants custom trace metrics, trace-aware LLM judge metrics with include_traces, latency, token usage, provider failures, tool behavior, vertical-specific workflow signals, or production monitoring based on trace attributes.
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Configure OpenTelemetry to send AI application traces, records of execution steps, to Confident AI. Reuse existing exporters, choose the regional endpoint, and add AI-specific attributes without requiring the deepeval Python package.
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Set up monitoring for deployed agents to inspect execution paths, latency, and model interactions. It explains Cloud Trace, prompt and response logging, BigQuery analytics, and external monitoring integrations, with checks for missing data and unwanted content capture.
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Choose diagnostic tools and collect performance traces for production .NET problems such as high CPU usage, memory growth, or slow requests. Get environment-specific collection commands and guidance on which tools to use for later analysis.
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VictoriaTraces provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery via the Jaeger-compatible HTTP API. This skill should be used when the user mentions "VictoriaTraces", "obz trace -p vt", or needs to search distributed traces from a VT backend.
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Use when analyzing harness trace logs to surface recurring failure patterns and suggest harness improvements. Scatter-gather pattern across last N runs with mandatory HITL gate before any change is applied. Triggers on /mk:trace-analyze, "analyze traces", "find patterns in harness runs", or after a model upgrade flagged dead-weight-audit-needed.
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Use this skill when the risk register and the statement of applicability were written separately and may not agree, and the team asks "do our risks link to our controls", "traceability between risk treatment and the SoA", "why is this control applicable", "the auditor could not trace a risk to a control", "check our risk treatment plan against the SoA" or "orphan controls". Checks in both directions that every treated risk points to controls and actions, and every applicable control traces back to a risk or obligation, then writes a traceability matrix and a list of orphans and contradictions with proposed fixes.
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Inspect, rebuild, or verify the append-only SDD Composy semantic trace (events.jsonl) and its derived projection (trace.json). Use for 'o que aconteceu nessa task', 'histórico do fluxo', 'verificar o trace', 'rebuild the trace projection'. Do NOT use for a status overview (sdd-status), evidence manifests (sdd-evidence), or to edit trace history.
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Capture Unreal Engine traces, export timing and counter data to CSV, and summarize expensive operations. Manage ongoing recordings, browse stored traces, and open Unreal Insights for visual inspection on Windows.
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Inspect local AI coding session logs with agenttrace to identify cost spikes, delays, failed tools, and retry loops. Produce readable reports, compare attempts, and configure automated checks for unusual or unhealthy runs.
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