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概要と使いどころ
Arize is an AI observability platform, and Phoenix is its open-source tracing and evaluation tool for LLM applications. Use this skill when the user wants to trace OpenAI or LangChain calls, run a local Phoenix server, score RAG answers for faithfulness, debug slow or wrong LLM responses, or send OpenTelemetry traces to Arize for production monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Guide collection and analysis of performance traces. Use when a mid-level developer needs to diagnose slowness.
日本語の概要は準備中です。原文の説明を表示しています。
Turn a PRD into a multi-phase implementation plan using tracer-bullet vertical slices, saved as a local Markdown file in ./plans/. Use when user wants to break down a PRD, create an implementation plan, plan phases from a PRD, or mentions "tracer bullets".
日本語の概要は準備中です。原文の説明を表示しています。
Reinforces an AI agent by turning Monte Carlo's reinforcement loop diagnosis into code fixes. Reads the daily reinforcement loop report for an agent's workflows, ranks the diagnosed issues, proposes what to fix, and — with the user's approval at each step — opens a pull request. Activates on "fix my agent", "improve my agent's health", "reinforce my agent", "what should I fix in my agent". Not for investigating a specific agent alert or trace (monte-carlo-troubleshoot-agent-traces), creating agent monitors (monte-carlo-monitoring-advisor), or instrumenting a new agent (monte-carlo-instrument-agent).
日本語の概要は準備中です。原文の説明を表示しています。
Troubleshoots Monte Carlo AI agent alerts and traces — eval score drops, latency/token spikes, trajectory and validation breaches. Not for data incidents (monte-carlo-analyze-root-cause) or monitor creation (monte-carlo-monitoring-advisor).
日本語の概要は準備中です。原文の説明を表示しています。
Traces decisions and requirements through GSD artifacts. Use when user asks "why did we...", "what happened to...", or mentions decision history.
日本語の概要は準備中です。原文の説明を表示しています。
Intercept and debug Claude Code API requests using mitmproxy. Inspect system prompts, tool definitions, token usage, and streaming responses. Triggers: cc-trace, mitmproxy, API interception, Claude Code debugging, traffic inspection.
日本語の概要は準備中です。原文の説明を表示しています。
Query and manage Datadog monitoring data — logs, metrics, monitors, dashboards, events, SLOs, traces, and incidents. Use this whenever the user wants to search logs, look at a metric, check which monitors are alerting, investigate a trace, pull SLO status, mute an alert, or ask "what's happening in Datadog" — even if they don't say "API". Also use it for any URL under *.datadoghq.com. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for enterprise mail abuse, OAuth consent, inbox or forwarding rules, transport rules, shared mailbox access, phishing chains, and token-to-mailbox side effects. Use when the user asks to trace mailbox rules, OAuth consent grants, forwarding or delegate abuse, shared mailbox access, message-trace evidence, or explain how mail artifacts turn into persistence, exfiltration, or privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Trace Odoo execution flow from an entry point through controllers, button actions, cron jobs, model methods, overrides, computes, onchanges, constraints, database operations, security checks, and side effects. Use before implementation, during debugging, impact analysis, performance review, or code review when behavior depends on Odoo call chains.
日本語の概要は準備中です。原文の説明を表示しています。
Compose, orchestrate, and trace production multi-agent workflows with Microsoft Agent Framework.
日本語の概要は準備中です。原文の説明を表示しています。
Insert a trace-aware guardrail layer between agents and their tools so unsafe message patterns or tool-call sequences are blocked by explicit rules.
日本語の概要は準備中です。原文の説明を表示しています。
在 AST JSON 上做信号路径追踪：source → sink 提取跨模块层次的传播路径，判定是否跨时钟域。供 CDC violation 根因分析与 critical path 辅助。触发场景：(1) bb-check-cdc 报 violation 需取证；(2) 综合 critical path 分析；(3) 显式 /bb-trace-signal-path。
日本語の概要は準備中です。原文の説明を表示しています。
Trace execution time of Python method invocations in a live process with call stack visualization. Use this to see a hierarchical call tree showing which sub-calls are slow and where time is spent within a function.
日本語の概要は準備中です。原文の説明を表示しています。
Render module-scoped human-readable traceability for a single module — REQs, DESs, TESTs, code locations with anchor links, plus the module-dependency graph as a markdown edge-list.
日本語の概要は準備中です。原文の説明を表示しています。
Export the REQ↔DES↔TEST traceability matrix for a feature in csv or markdown format. Phase D ships csv + markdown; Phase E (Assured) extends with standard-specific formats.
日本語の概要は準備中です。原文の説明を表示しています。
Exposes Claude's reasoning chain as an auditable, decomposable artifact. Quick mode (default) gives assumption inventory + weakest-link in 2 stages. Full mode (--full) adds decision branching, confidence decomposition, and falsification conditions. Triggers on "왜 그렇게 생각해", "reasoning", "근거", "show your work", "어떻게 그 결론이", "trace", "판단 근거", "why do you think that".
日本語の概要は準備中です。原文の説明を表示しています。
AgentCore の Observability ナレッジ。OpenTelemetry 必須4点セット（OTEL_EXPORTER設定・StrandsTelemetry・traceable デコレータ・Langfuse連携）、EMF メトリクス、Jaeger/コンソールエクスポーターでのトレース確認、トレースが出ない・繋がらない場合のデバッグ手順等
Create or refine custom icon assets as native or traced SVGs and transparent PNG/WebP files. Use when the user asks for a bespoke icon or cohesive icon set, wants an image traced into a clean vector, or needs a detailed or 3D icon with transparency.
日本語の概要は準備中です。原文の説明を表示しています。
Perform a Computer Systems Validation (CSV) assessment following GAMP 5 methodology. Covers user requirements, risk assessment, IQ/OQ/PQ planning, traceability matrix creation, and validation summary reporting. Use when a new computerized system is being introduced in a GxP environment, when an existing validated system is undergoing significant change, when periodic revalidation is required, or when a regulatory inspection demands a validation gap analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Implement pharmaceutical serialisation and track-and-trace systems compliant with EU FMD, US DSCSA, and other global regulations. Covers unique identifier generation, aggregation hierarchy, EPCIS data exchange, and verification endpoint integration. Use when implementing serialisation for a new product launch, integrating with the EMVS/NMVS, designing DSCSA-compliant transaction exchange, building an EPCIS event repository, or extending serialisation to additional markets (China, Brazil, Russia).
日本語の概要は準備中です。原文の説明を表示しています。
Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive primary skill for agents working with Weights & Biases. Covers both the W&B SDK (training runs, metrics, artifacts, sweeps) and the Weave SDK (GenAI traces, evaluations, scorers). Includes helper libraries, gotcha tables, and data analysis patterns. Use this skill whenever the user asks about W&B runs, Weave traces, evaluations, training metrics, loss curves, model comparisons, or any Weights & Biases data — even if they don't say "W&B" explicitly.
日本語の概要は準備中です。原文の説明を表示しています。
Use when writing eBPF programs with libbpf, bpftrace, or Rust with aya-ebpf and aya-log, attaching kprobes, tracepoints, or XDP hooks, declaring maps, sharing data with a Tokio loader, triaging verifier or Aya load errors, or porting with CO-RE. Not for full kernel bypass: use dpdk.
日本語の概要は準備中です。原文の説明を表示しています。