'raci' 검색 결과

Set up Langfuse to record LLM application activity, costs, and response times. Manage prompt versions, organize evaluation datasets, and compare results to investigate failures and guide improvements using recorded evidence.

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• Investigating failures in LLM applications
• Comparing prompt versions and evaluation scores
• Monitoring LLM costs and response times

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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• Send existing AI application traces to Confident AI
• Configure tracing for a non-Python AI application
• Choose the US or EU endpoint for an API key

Manage the KubeSphere ServiceMesh extension built on Istio, Kiali, and Jaeger. Install or remove it, check deployment status, and investigate problems with staged releases, proxy injection, service topology, traffic metrics, and tracing across application components.

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• Installing, upgrading, or removing ServiceMesh
• Investigating staged release routing problems
• Checking missing Istio proxy containers

Use LangSmith to record LLM application inputs, outputs, and timing, investigate failures, evaluate answers against test datasets, and monitor production usage. It also guides automated quality checks and analysis of token usage and costs.

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• Investigating failures in LLM applications
• Evaluating answers against test datasets
• Monitoring production latency and costs

Turn existing or proposed business processes into reusable standard operating procedures. Organize steps, roles, conditions, and known exceptions while marking missing details, producing clear handover documents without inventing approvals or responsibilities.

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• Turning workflow notes into a standard operating procedure
• Preparing process documentation for a handover
• Clarifying assignment, execution, and review responsibilities

Investigate organizations, domains, media locations, and cryptocurrency flows using open-source intelligence, or OSINT. The skill helps select relevant research tools, connect findings across sources, and preserve evidence with timestamps, screenshots, file hashes, and reproducible logs.

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• Mapping an organization's publicly exposed infrastructure
• Connecting public company records and social profiles
• Investigating image locations and video evidence

Update application code so a developer’s mirrord session identifier travels across service calls, queues, and storage events. Reuse existing tracing tools where possible, then report which request flows carry the identifier and where it still disappears.

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• Route downstream requests to the same developer session
• Preserve session identifiers across queue consumers
• Carry session context through upload events

Add OpenTelemetry tracing to frontend and backend flows. Connect execution records across services and background jobs, record phase durations and entity IDs, and mark failures so developers can investigate slow or broken operations.

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• Tracing a user action across multiple services
• Investigating slow queues and background jobs
• Connecting missing or disconnected traces

Trace system behavior across code, APIs, authentication, data, and networks through an interactive workflow. Store steps, branches, and findings in SQLite, then export diagrams and documentation for security audits, debugging, architecture reviews, or incident analysis.

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• Documenting authentication flows for security audits
• Tracing branches while debugging system behavior
• Reviewing how system components interact

Instrument C/C++ with -finstrument-functions for execution tracing and Perfetto visualisation

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Applies systematic tracing and isolation techniques to pinpoint exactly where a bug originates in code. Use when a bug is hard to locate, code is not working as expected, an error or crash appears with unclear cause, a regression was introduced between recent commits, or you need to narrow down which component, function, or line is faulty. Covers binary search debugging, git bisect for regressions, strategic logging with [TRACE] patterns, data and control flow tracing, component isolation, minimal reproduction cases, conditional breakpoints, and watch expressions across TypeScript, SQL, and bash.

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Thin Bevy genre router for Racing. Keywords: Bevy, Racing, genre, ECS, router.

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Expert at making systems observable and debuggable. Covers structured logging, metrics collection, distributed tracing, error tracking, and alerting. Knows how to find the needle in the haystack when production breaks at 3 AM. Use when "observability, logging, metrics, tracing, monitoring, error tracking, Sentry, Datadog, OpenTelemetry, debugging production, observability, logging, metrics, tracing, monitoring, sentry, prometheus, opentelemetry" mentioned.

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Site reliability specialist for Prometheus metrics, distributed tracing, alerting strategies, and SLO designUse when "observability, monitoring, prometheus, grafana, alerting, slo, sli, metrics, tracing, logging, on-call, incident, observability, prometheus, grafana, tracing, jaeger, alerting, slo, sli, metrics, logging, sre, ml-memory" mentioned.

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Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when "langfuse, llm observability, llm tracing, prompt management, llm evaluation, monitor llm, debug llm, langfuse, observability, tracing, llm-monitoring, evaluation, prompt-management, debugging, analytics" mentioned.

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Analyzing contact tracing data — network reconstruction, transmission chains, and evaluating tracing performance.

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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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Instrument a shipped product's AI agents with tracing and observability so you can see what they did, why outputs happened, and what each run cost. Plain-language primer plus free-tier-first backend selection (Langfuse, Phoenix, LangSmith, Braintrust) and OpenTelemetry/OpenInference instrumentation. Load when the user asks to add observability, add tracing, instrument my agents, see what my agent is doing in production, set up Langfuse or Phoenix or LangSmith, debug why my agent gave a bad answer, or track LLM cost per request. Also fires when agent-system-architecture or setup-evaluation requires an observability plan for an agent-chain product. NOT for tracing the coding agent itself — that is run-trace. Precondition for runtime-learning-loop.

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INVOKE THIS SKILL when adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md.

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운영 데이터베이스의 구조 변경과 기존 데이터 이전을 계획합니다. 열과 인덱스 추가, 단계적 전환, 복구 절차를 정리하고 중단 시간과 잠금을 고려한 변경을 돕습니다.

• 운영 테이블에 열이나 인덱스 추가
• 대량 데이터의 분할 갱신
• 앱을 중단하지 않고 열 교체

실제 파일과 행 번호를 확인해 CodeTour 형식의 단계별 코드 안내를 만듭니다. 새 담당자의 학습, 설계 이해, PR 검토, 장애 경로와 보안 경계 확인에 활용합니다.

• 새 유지보수 담당자를 위한 코드 안내
• 설계와 기능의 실행 경로 이해
• PR 변경 사항을 순서대로 검토

Debug Node.js from the terminal by pausing execution, inspecting variables, and tracing function calls. Use interactive commands or scripts to investigate failing tests, collect runtime state, and capture CPU profiles or memory snapshots.

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• Inspecting intermediate state in failing Node.js tests
• Tracing function calls and unexpected variable values
• Investigating stalled asynchronous processing

코드, 변경 이력, 재현 절차로 오류와 예상 밖 동작의 원인을 조사합니다. 가설 검증 후 최소한으로 수정하고 회귀 테스트와 증거를 담은 보고서까지 남깁니다.

• 오류와 스택 추적의 원인 조사
• 최근 변경으로 생긴 버그 추적
• 수정 검증과 회귀 테스트 기록

claude-mem에 쌓인 프로젝트 이력을 주별 이야기 형식의 보고서로 정리합니다. 앞선 주의 과제와 판단을 이어 받아 장기적인 작업 흐름을 추적합니다.

• 개발 경위를 주별로 돌아볼 때
• 문제 발생부터 해결까지 추적할 때
• 긴 이력을 색인이 있는 장으로 정리할 때