382 件 ・ 関連度順
概要と使いどころ
Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO definition.
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。
Map knowledge components and skill hierarchies for a cognitive tutoring system or adaptive learning platform. Use when designing intelligent tutoring software or skill-based mastery systems.
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。
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
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。
Idiomatic Go HTTP middleware patterns with context propagation, structured logging via slog, centralized error handling, and panic recovery. Use when writing middleware, adding request tracing, or implementing cross-cutting concerns.
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。
Provides monitoring and observability best practices covering the three pillars (logs, metrics, traces), OpenTelemetry instrumentation, Prometheus/Grafana dashboards, SLO-based alerting, and APM strategies. Use when setting up monitoring, observability, prometheus, grafana, opentelemetry, alerting, tracing, logging, metrics, dashboards, SLOs, or APM.
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。
Causal reasoning in historical analysis. Covers distinguishing immediate from underlying causes, tracing chains of causation across time scales, identifying unintended consequences, and applying counterfactual reasoning to assess causal significance. Use when analyzing why historical events occurred, evaluating the relative weight of causes, or assessing whether outcomes were inevitable or contingent.
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。
Reliability engineering for cloud systems — SLIs, SLOs, error budgets, SRE practices, runbooks, incident response, on-call rotation, blameless postmortems, chaos engineering, and the NASA Systems Engineering methodology (MCR/SRR/PDR/CDR/ORR phase gates, TAID verification, requirements tracing) adapted to cloud operations. Use when establishing SLOs for a new service, running an incident, writing a runbook, preparing a launch readiness review, or bringing NASA SE discipline to cloud deployments.
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。
Testing and debugging for Zephyr RTOS. Covers the Ztest framework for unit and integration tests, the Twister test runner for automated HIL/SIM validation, and advanced tracing/debugging techniques (SystemView, Thread Analyzer, Stack analysis). Trigger when writing unit tests, setting up CI/CD pipelines, or analyzing system performance and latency.
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。
Audit skill lifecycle by tracing call chains, detecting circular dependencies, finding instruction contradictions, identifying duplicated datasets, analyzing bidirectional coherence, discovering scriptable sequences, and learning patterns. Use when checking skill coherence, validating skill workflow, finding semantic gaps in plugin structure, or auditing plugin before marketplace submission. Generates audit reports to .plugin-creator/audits/ with findings by dimension.
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 bugs, CI failures, and unexpected behavior from reproduced evidence to a causal mechanism and governing contract. Distinguish product, architecture, test-oracle, and harness defects; investigate intermittent failures with controlled experiments and report unresolved evidence 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。
Dasel v3 selectors for Spring bean factory XML — use when querying any Spring ApplicationContext XML for bean discovery, dependency wiring, JMS destination mapping, property injection extraction, or cross-bean reference tracing. Load this skill before writing dasel selectors against Spring bean XML files (applicationContext.xml, *_beans.xml, spring-*.xml).
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。
Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.
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。
Produces a structured, end-to-end linear walkthrough of an unfamiliar codebase by orchestrating parallel subagents across four phases — discovery, tracing, validation, and synthesis. Use when onboarding to a new repository, understanding execution paths from entry points, generating navigable codebase documentation, or needing fact-checked coverage of architecture, deployment, testing, and operations.
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。
Turns dictated captures in a deliverable's inbox/ into a proposed planning-wiki diff, classifying and tracing each statement; decisions need the author's assent. Use to intake notes or process the inbox.
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。
Build production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production deployment.
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 IPA runtime analysis, Frida hooks, Objective-C or Swift method tracing, Keychain inspection, SSL pinning bypass, URL scheme handling, and iOS request-signing recovery. Use when the user asks to hook an IPA, trace Objective-C or Swift runtime behavior, inspect Keychain or plist state, bypass pinning, analyze deeplinks or universal links, or replay accepted iOS requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$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。
Use Odigos to add OpenTelemetry tracing to Kubernetes or VM workloads without code changes, then route the traces to the observability backend an operator already uses.
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。
解析 SystemVerilog RTL 为 AST JSON，供 CDC 检查 / signal path tracing / module dep 分析。统一 4 个后端 (babel-lsp / pyverilog / verible / slang)，auto 模式自动降级。触发场景：(1) bba-guru-synthesis CDC 前；(2) bb-trace-signal-path / bb-find-module-deps 之前；(3) 显式 /bb-parse-ast。
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。
Respan for LLM observability. Use to set up tracing or the gateway, manage prompts (create/version/deploy), run evals, experiments, and datasets, or work with traces and logs. Trigger for any Respan platform task or when instrumenting an app to send telemetry to Respan.
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。
Investigate stuck runs and execution failures by tracing Symphony and Codex logs with issue/session identifiers; use when runs stall, retry repeatedly, or fail unexpectedly.
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。
Investigate stuck runs and execution failures by tracing Symphony agent-provider logs with issue/session identifiers; use when runs stall, retry repeatedly, or fail unexpectedly.
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 working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).
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。
Apply MCAF human-review-planning guidance for a large AI-generated code drop by reading the target area, tracing the natural user and system flows, identifying the riskiest boundaries, and prioritizing the files a human should inspect first. Use when the codebase is too large to review line-by-line and you need a practical review sequence plus a prioritized file 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。