2.2万 件 ・ 関連度順
概要と使いどころ
Evaluate a codebase for agent-friendliness based on autonomous agent best practices. Use when asked to "evaluate for agents", "check agent readiness", "audit for autonomous execution", "assess agent-friendliness", or when reviewing infrastructure for unattended agent operation. Also use when asked about making a codebase more suitable for AI agents or autonomous workflows.
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 benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test 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。
Use when designing an autonomous agent, planning agent architecture, building a scheduled automation, or creating a Claude Code agent workflow. Triggers: 'design an agent', 'build an automation', 'agent architecture', 'automate this workflow', 'create a scheduled agent', 'shell script 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。
This skill should be used when creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
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 agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Galyarder 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。
Design effective AI agent systems with clear architecture, capability planning, and tool integration. Use when building agent systems, designing agent workflows, planning tool ecosystems, defining agent roles and boundaries, or architecting multi-agent systems. Covers agent patterns, agentic loops, capability design, and system composition.
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。
Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).
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 designing an autonomous agent, planning agent architecture, building a scheduled automation, or creating a Claude Code agent workflow. Triggers: 'design an agent', 'build an automation', 'agent architecture', 'automate this workflow', 'create a scheduled agent', 'shell script 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。
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
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。
Generative Engine Optimization plus agent readiness. Use this skill whenever the user asks about GEO, AEO, LLMO, optimizing content for AI search engines (ChatGPT, Perplexity, Google AI Overviews, Claude, Gemini, Copilot), getting cited by LLMs, brand mentions in AI responses, llms.txt, robots.txt for AI crawlers, Schema.org JSON-LD, FAST framework, agent readiness, MCP server discovery, Web Bot Auth, OAuth for agents, API Catalog, agentic commerce (x402, ACP, UCP), Markdown content negotiation, or auditing a site or page for AI visibility. Also trigger when the user says "AI SEO", asks how to "rank in ChatGPT", "show up in Perplexity", "appear in AI Overviews", or wants a site to "speak to AI agents". Trigger even when the request is implicit, such as "review this article so AI search picks it up" or "make our docs agent-friendly".
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。
Test AI agent systems for tool abuse, unauthorized actions, privilege escalation through tool chaining, and safety bypass via agentic workflows. Use this skill when assessing autonomous AI agents that use tool-calling (function calling, plugins, actions) to interact with external systems. Covers multi-step attack chains, implicit trust exploitation, and capability boundary testing for AI agents.
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 a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.
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 cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.
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。
Apex test patterns for @InvocableMethod agent actions: per-reason-code branch coverage, bulk safety, callout mocking, deterministic assertions. NOT for testing whether the agent routes to the right topic or answers well — use agentforce/agent-testing-and-evaluation. NOT for designing the error envelope the tests assert on — use agentforce/agent-action-error-handling.
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 defining or refining the tone, voice, and behavioral personality of an Agentforce agent: system instruction encoding, brand voice alignment, adaptive response formats, multi-persona strategies. NOT for writing the actual conversational copy — utterances, fallback messages, escalation phrasing — use admin/agent-conversation-design. NOT for topic scope design — use agentforce/agent-topic-design.
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 designing or reasoning about an Agentforce Grid worksheet — the spreadsheet-like Agentforce workspace where rows are jobs and columns are sequential Data / AI / Action steps that process left to right — to run bulk record updates, generate insights, or test multi-turn AI conversations over CRM or Data Cloud (Data 360) data without Apex or Flow. Trigger keywords: Agentforce Grid, workbook, worksheet, grid column, data column, AI column, action column, bulk AI update, Flex Credits per row, metered compute. NOT for building the agent, its topics, or its actions themselves (use agentforce/* action and topic skills), NOT for single-record prompt design (use the prompt-builder skills), NOT for deployable metadata/Apex (Grid is a no-code Studio tool, not a metadata type), and NOT for AI governance/ethics policy (use admin/ai-ethics-and-governance-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。
Use when an ISV or consulting partner is creating, pricing, publishing, or maintaining an AgentExchange listing through the Partner Console — covers the listing plan, the 5-step Listing Builder workflow (Fill in the Basics, Set Pricing, Add Details, Link Your Solution, Grow Your Business), commercialization models (revenue share vs. annual fee vs. freemium), AgentExchange Checkout setup (Stripe connection, pricing plans, fees, geographic eligibility), Private Offers, Security Review gating, and post-publish listing updates. NOT for building the agent or managed package itself (use agentforce/agentforce-agent-creation and devops/second-generation-managed-packages), NOT for LMA/Trialforce licensing internals (use devops/isv-license-management-and-trialforce), and NOT for the customer-side install experience.
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 overriding the default UI of an Agentforce agent action's Apex input or output with your own Lightning web components via a LightningTypeBundle (schema.json + editor.json/renderer.json, lightning__AgentforceInput / lightning__AgentforceOutput targets, the @apexClassType binding). NOT for standard agent actions with primitive inputs/outputs (only Apex-class input/output can be overridden), NOT for Flow screen custom property editors (use flow/flow-custom-property-editors), and NOT for general LWC-in-Lightning-page work (use lwc/* skills).
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。
Author the Salesforce Configuration Workbook — the structured, reviewable handoff document an admin uses to execute a feature across Objects/Fields, Page Layouts, Profiles/PSGs, Sharing, Validation, Automation, List Views, Reports, Integrations, and Data. Triggers: 'salesforce configuration workbook', 'admin handoff document', 'implementation workbook'. NOT for object design itself (use admin/custom-field-creation, admin/lookup-and-relationship-design, agents/object-designer/AGENT.md), NOT for permission set design (use admin/permission-set-architecture, agents/permission-set-architect/AGENT.md), NOT for Flow construction (use skills/flow/* and agents/flow-builder/AGENT.md), and NOT for the deployment manifest (use skills/devops/metadata-api-retrieve-deploy). More triggers: workbook row schema, recommended_agent, recommended_skills, row_id, source_req_id, RTM linkage block, not-in-scope-this-release, descope ledger, version-lock the workbook, check_workbook.py.
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。
Router for the 53 SfSkills `agentforce` skill packages. Agentforce and Einstein: agents, topics, actions, prompt templates, grounding, guardrails, evaluation and production readiness. Use when the request mentions Agentforce, agent topic, agent action, prompt builder, Einstein, Trust Layer, grounding, RAG, guardrails, agent evaluation, prompt injection. Finds and opens the exact skill package to read; it does not contain the guidance itself.
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 or auditing the conversational copy layer of a Salesforce bot or Agentforce agent: utterance authoring strategy, fallback message copy, escalation-criteria phrasing, and persona-consistent dialog scripting across channels. NOT for designing the bot dialog structure, intent model, or handoff architecture — use architect/einstein-bot-architecture. NOT for encoding agent tone in Agentforce system instructions — use agentforce/agentforce-persona-design.
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。
Agent-to-Agent 轻量通信协议。仿 Google A2A 设计，但适配 Clawdbot/OpenClaw 生态。用于：(1) Agent 能力发现 (2) 跨 agent 任务协作 (3) 结构化的 agent 间消息交换。触发词：a2a、agent协议、agent通信、agent card、能力发现。
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。
Agent 专用邮箱统一管理：让 Claude Code、Codex 等平台的 Agent 用一套命令收发邮件、整理收件箱、分发任务。支持网易 ClawEmail（claw.163.com）和腾讯 Agent Mail（QQ 邮箱，agent.qq.com）两家后端，通过 MAIL_PROVIDER 切换。当用户提到收发邮件、看收件箱、搜索邮件、回复转发邮件、下载附件、整理邮件、给其他 Agent 派邮件任务、配置 Agent 邮箱、腾讯 QQ 邮箱 Agent、网易 ClawEmail 时使用此 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。
Launch Marcus multi-agent experiments with independent Claude agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent Claude CLI agents that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this 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。