1.2万 件 ・ 関連度順
概要と使いどころ
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
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 Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big data workloads. Invoke to write DataFrame transformations, optimize Spark SQL queries, implement RDD pipelines, tune shuffle operations, configure executor memory, process .parquet files, handle data partitioning, or build structured streaming analytics.
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。
Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing. Implements Prometheus/Grafana stacks, conducts load testing, performs application profiling, and plans infrastructure capacity. Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottlenecks, or forecasting capacity needs.
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。
Implements concurrent Go patterns using goroutines and channels, designs and builds microservices with gRPC or REST, optimizes Go application performance with pprof, and enforces idiomatic Go with generics, interfaces, and robust error handling. Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration, CLI tools, benchmarks, or table-driven testing.
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。
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
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。
CRM-lite for managing GEO agency prospects and clients. Track leads through the full sales pipeline: Lead → Qualified → Proposal Sent → Won → Lost. Store audit history, notes, deal values, and generate pipeline summaries. Use when user says "prospect", "lead", "client", "pipeline", "crm", "nuovo prospect", "aggiungi cliente", or when managing the business side of GEO services.
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。
Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs. new-session composer, terminal strip vs. agent terminal, all twelve native harnesses). Covers the web UI, native harness terminals, and the CLI.
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。
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.
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。
Validate Claude Ads contracts, scoring inputs, run bundles, capabilities, source freshness, safety, installation, uninstall, or release readiness. Use for ads validate, ads status, ads next, stale claims with missing tool access, maturity checks, ownership-manifest uninstall, preserving unrelated ads-* skills, checksum verification, preflight, QA, or release audits. Missing access must demote stale evidence for the run and block dependent release-current claims before recovery guidance.
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。
Review open NPRM comment periods, log decisions, track deadlines. Use when an NPRM has a comment window open and you need to surface deadlines, decide whether to file, or record a filing / not-filing / waived decision (--decide CMT-ID).
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 a deposition outline for a witness — pull their documents from the eDiscovery platform, organize topics around the case theory, and surface impeachment material. Use when the user says "depo prep for [witness]", "build a depo outline", or "prepare for [name]'s deposition".
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。
Track case deadlines — add, cross-case rollup report, update, complete, close. Warns at configurable thresholds (default 14/7/3/1 days); overdue items stay flagged until resolved. The operational record for a clinic workload. Use when a student or supervisor needs to add a deadline, ask what's due this week, get a deadline report, or update a case deadline.
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。
Translates a contract review into a summary the business stakeholder will actually read. Not a legal memo — a two-minute answer to "can I sign this and what do I need to know." Use when user says "summarize for the business", "write this up for [stakeholder]", "explain this to procurement", "non-legal summary", or when a review is done and needs to go to someone outside legal.
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。
Run every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.
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。
Route retrieval of Chinese medical guidelines, consensus statements, regulatory documents, drug information, safety notices, standards, and public-health materials through authoritative originals and verified fallback copies. Use when a canonical medical source is blocked, slow, unavailable, moved, paywalled, or difficult to parse, or when designing and auditing domestic medical-source fallback rules. Do not treat secondary summaries or reposts as independent clinical evidence.
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。
하네스 진화 스킬. 사용 중인 하네스의 실행 결과에 대한 피드백을 수집·일반화하여 에이전트/스킬/오케스트레이터에 반영하고, 초기 구성 대비 델타를 포착해 변경 이력을 갱신한다. '하네스 회고', '하네스 진화', '하네스 피드백 반영', '하네스 개선', '결과가 아쉬웠어 하네스 고쳐줘', '이 피드백 하네스에 반영해줘', '하네스 레슨 정리' 등 기존 하네스의 실행 경험을 바탕으로 한 개선 요청 시 반드시 이 스킬을 사용. 하네스 신규 구축·구조 재설계·에이전트 추가는 harness 스킬이 담당.
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。
中文文档排版参考——中英文空格、全半角标点、术语保留、链接格式、中文文案排版指北约定。仅在用户显式 /chinese-documentation 时调用，不要根据上下文自动触发。
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。
国内 Git 平台配置参考——Gitee、Coding.net、极狐 GitLab、CNB 的 SSH/HTTPS/凭据/CI 接入差异与镜像同步配置。仅在用户显式 /chinese-git-workflow 时调用，不要根据上下文自动触发。
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。
中文 commit 与 changelog 配置参考——Conventional Commits 中文适配、commitlint/husky/commitizen 中文模板、conventional-changelog 中文配置。仅在用户显式 /chinese-commit-conventions 时调用，不要根据上下文自动触发。
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。
中文 review 沟通参考——话术模板、分级标注（必须修复/建议修改/仅供参考）、国内团队常见反模式应对。仅在用户显式 /chinese-code-review 时调用，不要根据上下文自动触发。
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。
Create polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and stateDiagram input; inspect repository evidence when the diagram must reflect real code. Use when the user asks to visualize system architecture, infrastructure, cloud/security/network topology, technical workflows, API call sequences, request lifecycles, data pipelines, ETL/ELT, data lineage, state machines, or to convert/beautify Mermaid.
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。
Verify harness changes end-to-end without docker — drive the real pinned CLI against a header-capturing stub server with the exact env resolve_auth_env() produces.
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。
Sets up and runs libFuzzer, the coverage-guided fuzzer built into LLVM, on C/C++ code that compiles with Clang. Covers harness structure, -fsanitize=fuzzer builds, corpus and dictionary management, sanitizer integration, and campaign triage. Use when writing or debugging an LLVMFuzzerTestOneInput harness, starting fuzzing on a C/C++ library, choosing between libFuzzer and AFL++, or working out why a libFuzzer run finds nothing.
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。
Smart contract development advisor based on Trail of Bits' best practices. Analyzes codebase to generate documentation/specifications, review architecture, check upgradeability patterns, assess implementation quality, identify pitfalls, review dependencies, and evaluate testing. Use when asking whether a smart contract project follows development best practices, reviewing on-chain/off-chain split, upgradeability, or delegatecall proxy patterns against guidelines, or seeking recommendations on contract design, inheritance, events, documentation, dependencies, or test strategy.
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。