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概要と使いどころ
Use when operating Volcengine TLS (日志服务) through volclog in agent or CI sessions and you need a contract-first workflow for runtime selector resolution, discover/describe/exec routing, App resource or Topic resolution, envelope reading, large-result delivery, and error recovery without guessing commands, fields, or shortcut flows. 当用户提到火山引擎日志服务 TLS、volclog、日志检索/分析/导入/导出、 日志项目或日志主题等操作时调用。
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。
Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.
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。
Guidance for Tauri v2 security model, baseline hardening, and runtime authority controls.
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。
Deno runtime guidance — TypeScript-first development, permissions, standard library, and deploying Deno apps.
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。
Secure containerized workloads — image hardening, registry scanning, runtime protection, and supply-chain integrity.
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。
Deploy ML models to production with Baseten — high-performance inference with autoscaling and custom runtimes.
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。
Bun runtime guidance — fast installs, built-in bundler and test runner, Bun.serve APIs, and migration from Node.
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。
Orchestrate agents at runtime — task routing, scheduling, parallel execution, result aggregation, and supervision dashboards. Use when running agents as a managed fleet rather than one-off calls.
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。
Inspect and manage the user's Vercel websites, web apps, projects, and deployments. Use to read build and runtime logs, investigate production errors and failed deployments, check deployment status, and deploy projects through Vercel's official MCP server.
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。
Observes runtime behavior of binaries via QEMU emulation, GDB debugging, and Frida hooking — syscall tracing, breakpoints, memory inspection, and function interception. Use when running, tracing, or debugging a binary, verifying hypotheses from static analysis, or watching actual syscalls, network calls, or file access; requires human approval before any execution.
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 this skill when asked to search public content platforms such as Bilibili or YouTube, pick the top relevant results for a topic, and summarize each item with links and brief overviews. Uses Runtime-aware routing — opencli first, fetch second, browser last.
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 one approved master still into a character's whole animated sprite set - one image-to-video clip per action (idle, walk, run, attack, jump, hurt, cast and so on), all from that still, generated through generate2dmedia route_media.py (the xAI API when a key is configured, else the local Grok CLI) - then gate each take, key it with a soft matte, register it to the master, pick loops or retime actions, finish (HD by default, pixel on request) and package fixed-canvas frames, alpha WebM, packed MP4 for iPhone and a PNG fallback with engine metadata and a JS runtime. Also processes a supplied clip. Use for character and creature animation, fluid motion and any video-to-sprite work. Not for FX, icon or prop sheets (generate2dsprite), maps or plate loops (generate2dmap), code-drawn animation (codeart2d, only on request) or calling a video API by itself (generate2dmedia).
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。
Explicit-only last resort. Draws game art from code, with no image model - pixel sprites from a PixelSpec, flat vector props, UI and icons from portable SVG, rigged characters with planted feet, FX with a JS runtime, seam-proven autotiles, playable top-down layouts with collision, stylized parallax and ambient plate motion - palette-exact, with QA and review sheets. Use only when the user explicitly asks for code-drawn art, or when generate2dmedia route_media.py finds no image or video route (no-route, exit 3). Never the default - image generation (generate2dsprite, generate2dmap, video2dsprite) comes first for characters, props, maps and FX. Not for painterly, detailed or likeness art, HD-2D plates or realistic fire, smoke or water. Always disclose the result as code-drawn.
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。
Manage persistent coding sessions across Claude Code, Codex, Antigravity (agy), Grok Build, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 78 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "auto research", "switch model", "hand off a session", "session handoff", "switch engine", "continue on codex", "continue on claude", "move this session to another engine", "multi-agent coding", "coding session", "session inbox", "grok session", "grok build", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness", "clawo runs", "run ledger", "session cost", "coding-agent token usage", "spend cap", "budget limit", "maxBudgetUsd", "durable workflow", "resume a run", "verify a coding run", "acceptance contract", "evidence bundle", "did the agent's tests actually pass", "protected tests", "agent edited the tests", "human gate", "repair loop", "clawo workflow", "clawo verify", "clawo solve", "clawo fanout", "fix and verify", "solve from the terminal".
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。
Plan, implement, audit, and review C#/.NET SwiftlyS2 plugins. Use when working with Commands, Core Events, Game Events, GameHooks Pre/Post, raw native hooks, Modules, Workers, Services, high-frequency runtime loops, NetMessages, Schema access, entity handling, thread safety, performance, or IPlayer lifecycle behavior.
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。
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap Hub via local Proxy mailbox.
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 this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.
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 alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using Multi-Window Multi-Burn-Rate SLO alerts, memory saturation, and cluster health such as CrashLoopBackOff and Node NotReady conditions. Don't use for non-GKE compute runtimes such as standalone Compute Engine VMs or standalone Cloud Run services without GKE.
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 and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.
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 best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI 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。
Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack.
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。
Guidance on non-obvious runtime behaviors of Salesforce standard objects — polymorphic lookups, lead conversion field loss, PersonAccount dual-nature, CaseComment trigger isolation, and Activity date fields. Also covers which trigger actually fires for a person account, the either/or Event duration contract, the Closed status category behind Task.CompletedDateTime, the 3-record merge cap and its single delete + single update trigger events, and the CaseComment post-insert write lock. Trigger keywords: person account trigger not firing, Contact trigger person account, Event required field EndDateTime, DurationInMinutes, CompletedDateTime null, merge MasterRecordId, CaseComment cannot be edited, IsNotificationSelected null, lead conversion triggers disabled. NOT for the Activity object model — use admin/activity-and-task-patterns. NOT for writing TYPEOF queries — use apex/apex-polymorphic-soql.
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 setting up, customizing, or troubleshooting the Salesforce Path component on Opportunity, Lead, Case, or custom objects. Triggers: 'add guidance to stages', 'key fields on path', 'celebrate closed won', 'path not showing', 'configure path steps', 'confetti on stage change'. NOT for creating the stage picklist — use admin/opportunity-management. NOT for in-app prompts — use admin/in-app-guidance-and-walkthroughs. Metadata: PathAssistant, PathAssistantStep, PathAssistantSettings, pathAssistantEnabled, canOverrideAutoPathCollapseWithUserPref, runtime_sales_pathassistant:pathAssistant, picklistValueName, recordTypeName, BusinessProcess.
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 this skill when designing the checkout experience for a Salesforce B2B or D2C Commerce storefront — covering runtime model selection (LWR Managed Checkout vs Aura Flow Builder), cart and line-item requirements, payment option scoping, shipping rule definition, and guest vs. registered buyer experience design. Trigger keywords: checkout flow design, checkout UX requirements, LWR vs Aura checkout, guest checkout design, payment options design, shipping rules, checkout experience planning. NOT for configuring the checkout in Setup once designed — use admin/commerce-checkout-configuration. NOT for choosing B2B vs D2C Commerce — use admin/b2b-vs-b2c-requirements.
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。