2.3만건 · 관련도순
Set up Google's agents-cli and find the right workflow for building AI agents. Connects requirements planning, project creation, implementation, evaluation, deployment, publishing, and monitoring through specialized skills for the Gemini Enterprise Agent Platform.
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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types, including the Agent Script language for the new Agentforce Builder (hybrid-reasoning -> logic vs | prompt instructions, @actions/@subagent/@variables references, subagents). Use when creating agents in source control, writing or debugging Agent Script, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'write or debug Agent Script', 'how do I deploy an Agentforce agent using source control', 'convert an agent topic to a subagent', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship', 'Agent Script logic vs prompt instructions'. NOT for Apex-based agent actions — use agentforce/custom-agent-actions-apex. NOT for clicking the agent together in the Builder UI — use agentforce/agentforce-agent-creation.
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Build servers and clients for A2A, an open protocol that lets AI agents communicate across frameworks. Publish agent capabilities, exchange tasks and results, stream progress, and add notifications for workflows involving multiple agents.
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Register a deployed agent with Gemini, choose the appropriate registration method, and troubleshoot setup problems. Also covers managing agents and registering MCP servers, which expose tools to agents, in Google Cloud Agent Registry.
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Look up an AI agent’s owner and profile using its blockchain identity, find ERC-8004 registry addresses, and generate an AgentCard JSON file describing services, supported trust models, and x402 support for registration.
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Use when creating, configuring, auditing, or troubleshooting an Agentforce agent end-to-end: agent definition, agent user setup, channel assignment, system instructions, activation, and lifecycle management. Triggers: 'create agentforce agent', 'agent not appearing to users', 'how to activate agent', 'agent channel setup', 'agent lifecycle', 'deploy agent to production'. NOT for designing what the agent can DO — an agent that looks up an order, checks a case, or creates a record is action design, use agentforce/agent-actions. NOT for topic boundary design — use agentforce/agent-topic-design.
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Use when testing, evaluating, or building regression suites for Agentforce agents: conversation testing in Agent Builder, topic (now subagent) coverage and utterance testing, Testing API and AiEvaluationDefinition metadata, Agentforce DX CLI test runs (sf agent generate test-spec, sf agent test create/run/resume/results/list), evaluation metrics (containment rate, escalation rate, CSAT, topic activation accuracy), and post-deploy analytics via Enhanced Event Logs. Triggers: 'how do I test my Agentforce agent', 'agent routes to wrong subagent', 'write utterance tests', 'regression test after topic change', 'measure agent quality', 'agent containment rate', 'run agent tests from the CLI'. NOT for agent creation, topic design, or action contract design — use agentforce/agentforce-agent-creation, agentforce/agent-topic-design, or agentforce/agent-actions respectively.
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Plan and carry out agent deployments on Google Cloud using agents-cli. The guide covers deployment targets, permissions, secrets, automated build and deployment pipelines, verification, and recovery procedures for agents built with supported frameworks.
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Orchestrator for agent harness work — the setup that makes AI agents follow project rules and improve when they fail. FIRES PROACTIVELY when agents misbehave, repeat mistakes, ignore instructions, skip skills, or when AGENTS.md exists but docs/harness/manifest.json is missing. Also triggers on: harness engineering, agent scaffold, agent keeps failing, agent not following instructions, make agents reliable, agents going off rails, agent forgot context, improve agent setup, self-improving agents, agents keep making mistakes, why is my agent bad, agent quality, agent setup broken, agents ignore skills, same mistake again, fix agent behavior, tune agent instructions, set up agent infrastructure, after project setup agents still bad. Routes bootstrap vs evolution. Not multi-agent topology — agent-builder.
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Claude Code 플러그인에 여러 단계의 작업을 독립적으로 수행하는 전용 에이전트를 추가합니다. 호출 조건, 역할, 도구와 출력 형식을 정하고 검증까지 안내합니다.
Create and install Observal Agents, edit their definitions, and manage publication and version releases. The skill also supports forking approved Agents, archiving and restoring them, transferring ownership, and managing co-authors.
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Deploy and operate AI agents with AWS Bedrock AgentCore. Choose services for hosting agents, connecting external APIs, managing credentials and conversation state, monitoring activity, and assessing agent quality through automated evaluations.
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Design autonomous agents for Claude Code plugins, including when they should run, what tools they may use, and how they should respond. Provides configuration templates, prompt guidance, and validation steps for creating agent files.
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Create and manage custom Agent resources on Gemini Enterprise Agent Platform before running conversations. Prepare REST requests to configure instructions, attach files and skills, connect tools, track creation progress, and retrieve, update, or delete agents.
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Investigate 403 and 500 errors in Google Cloud Gemini Enterprise Agent Platform. Examine logs, registered destinations, agent identities, and authorization policies to produce a diagnostic report with evidence, recommended fixes, and verification steps.
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Single entry point for every Agentlas command: /agentlas network, /agentlas build, /agentlas storm, /agentlas graph, /agentlas one, /agentlas upload, /agentlas cloud, /agentlas hub, /agentlas local, /agentlas browser, /agentlas call, /agentlas search, /agentlas connect, /agentlas login, /agentlas orch, /agentlas update.
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Create and update prompt-based agents in Azure AI Foundry from a local JSON manifest, a file listing agent definitions. The skill prepares synchronization scripts, pushes instructions to the service, and verifies registered agents.
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Connect agentmemory to coding agents such as Claude Code and Codex while preserving existing server settings. It guides configuration, host restarts, and checks that memory tools are available and can save and retrieve information.
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Find API patterns and examples for coding agents with ADK, the Agent Development Kit. Covers tools, state, callbacks, multi-agent coordination, and graph workflows, with Python and Go references plus guidance on studying existing implementations.
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Microsoft Entra Agent ID (preview) for creating OAuth2-capable AI agent identities via Microsoft Graph beta API. Covers Agent Identity Blueprints, BlueprintPrincipals, Agent Identities, required permissions, sponsors, and Workload Identity Federation. Includes Microsoft Entra SDK for AgentID (containerized sidecar) for polyglot agent authentication (Docker/Kubernetes), 3P agent integration, autonomous and interactive agent patterns. Triggers: "agent identity", "agent id", "Agent Identity Blueprint", "BlueprintPrincipal", "entra agent", "agent identity provisioning", "Graph agent identity", "entra sidecar", "agent id sidecar", "auth sidecar", "3P agent", "third-party agent identity", "polyglot agent auth".
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Drive the AgentWiki knowledge platform via its CLI (`@aiagentwiki/cli`, command `agentwiki`) and MCP server (`https://api.agentwiki.cc/mcp`). Use this skill whenever the user mentions AgentWiki, agentwiki.cc, app.agentwiki.cc, the `agentwiki` CLI, the `@aiagentwiki/cli` npm package, the AgentWiki MCP server, or asks to create/list/search/share/publish documents, manage folders or tags, upload files or images, deploy static sites, traverse a knowledge graph, or query their AgentWiki workspace from the terminal or as an AI agent. Triggers include phrases like "agentwiki login", "aw_… API key", "create a doc on agentwiki", "search my wiki", "publish to agentwiki", "agentwiki MCP", or any task that would otherwise require opening app.agentwiki.cc manually.
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Authoring and managing Agentforce agent definitions using the declarative Agent Script DSL (.agent files) and associated metadata types. Use when creating agents in source control, debugging agent metadata, or understanding the metadata lifecycle of GenAiPlugin/GenAiPlanner/BotVersion types. Triggers: 'how do I deploy an Agentforce agent using source control', 'what metadata types make up an Agentforce agent', 'agent test run command failing in CI pipeline', 'GenAiPlugin vs GenAiPlanner metadata relationship'. NOT for Apex-based agent actions (use custom-agent-actions-apex). NOT for UI-based agent creation (use agentforce-agent-creation).
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Build production-grade AI agents from scratch using patterns inspired by production-grade agentic systems like Claude Code. Covers two audiences — (1) workflow builders who need planner+executor pipelines, human-in-the-loop checkpoints, and multi-agent orchestration, and (2) application embedders who need HTTP/SSE APIs, multi-user session management, and React frontend integration. Use when asked to build an AI agent, create a coding assistant, embed an agent in an app, build an API agent, clone Claude Code, build a CLI agent, design an agent architecture, scaffold an agentic system, or automate a multi-step workflow. Triggers on keywords like agent builder, agent blueprint, coding assistant, CLI agent, agentic tool, claude code clone, agent scaffold, agent architecture, workflow automation, multi-agent, planner executor, SSE streaming, agent API.
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Automate Agenty tasks through Rube MCP, a connection to external tools. The skill discovers available operations and their required inputs, checks the Agenty connection, and executes tasks using the tools it finds.
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