“agents”的搜索结果

Create, improve, or audit CLAUDE.md files that introduce AI agents to a project. Review project structure and development commands, keep shared instructions concise, and move detailed guidance into referenced documents, with drafts reviewed before changes are applied.

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• Draft project instructions for AI agents
• Shorten an existing CLAUDE.md
• Audit instruction quality without editing files

Create, improve, or audit CLAUDE.md files that explain a project's purpose, structure, and development workflow to AI agents. Organize essential instructions, remove redundant content, and link to detailed documents where needed.

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• Creating project instructions for AI agents
• Condensing an overly long CLAUDE.md
• Auditing existing instructions without editing files

Create, improve, or audit CLAUDE.md files that explain a project's purpose, structure, and development workflow to AI agents. Organize essential instructions, remove redundant content, and link to detailed documents where needed.

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• Creating project instructions for AI agents
• Condensing an overly long CLAUDE.md
• Auditing existing instructions without editing files

Organize feature development across multiple agents by dividing work, assigning one owner per file, and agreeing on interfaces before implementation. Provides strategies for shared files, branches, and integration so agents can build separate parts of the same system.

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• Dividing a large feature among multiple agents
• Assigning file ownership to avoid conflicting edits
• Agreeing on APIs before parallel implementation

Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.

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• Create project instructions for VS Code Copilot
• Refresh agent rules after project changes
• Split monorepo instructions by project area

Consult another agent for specialist advice, reviews, or workspace context through QwenPaw commands. Keep follow-up conversations connected using session identifiers, and submit longer tasks in the background while continuing other work and checking results later.

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• Ask a specialist agent for advice
• Request a second opinion or review
• Consult an agent with relevant files or context

Manage multiple AI agents through the AI Maestro command-line tool. Create agents, inspect their status, pause and resume work, rename them, export or import configurations, and manage plugins from one interface.

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• Creating an agent for a specific project
• Checking agent status and assigned tasks
• Hibernating agents and resuming them later

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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• Connecting agentmemory to a coding agent
• Checking supported agents and connection methods
• Investigating an incorrect configuration path

Design AI agents and chatbots in n8n, choosing suitable nodes and connecting models, tools, conversation memory, and structured JSON output. Includes guidance on document retrieval and human approval before tool execution.

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• Building a chatbot with conversation memory
• Connecting external tools to an AI agent
• Returning data in a defined JSON format

Plan and build AI agents on Google Cloud, from gathering requirements to choosing a single-agent or multi-agent design. Produce architecture diagrams, deployment code and instructions, and validation plans tailored to the workload.

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• Plan an AI agent architecture on Google Cloud
• Choose between single-agent and multi-agent designs
• Prepare deployment code and step-by-step instructions

Guides iterative improvement of AI agent prompts, skills, and memory using A-Evolve. It explains how to evaluate agents against benchmark tasks, apply changes, validate results, and track or roll back revisions with Git.

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• Improve an existing agent against benchmark tasks
• Build evaluations for domain-specific tasks
• Refine skills and memory from failure feedback

Build teams of AI agents with CrewAI, assigning roles such as researcher, writer, and analyst. Guidance covers passing results between tasks, running work in sequence or under a manager, adding memory, and creating workflows with conditional branches.

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• Connecting research, writing, and editing agents
• Coordinating specialist agents through a manager
• Branching workflows based on analysis results

Guides building chatbots and tool-using agents with LangChain. Covers conversation history, model provider integration, and RAG, which retrieves relevant documents to inform answers, plus tracing to inspect application behavior.

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• Build a chatbot that remembers conversation history
• Create document question answering with source references
• Build an agent that uses custom tools

Inspect imports and agent patterns in existing Python code to identify its framework and recommend an Omnigent executor, the component that runs the agent. Explain unsupported frameworks and suggest available next steps.

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• Identify the framework used by existing Python agent code
• Choose an executor for Claude SDK or OpenAI Agents SDK code
• Check whether a framework has native support

Manage agents on a host by listing their capabilities, reading source code, and downloading or deploying agents in the smith namespace. Check available language model connections and their roles without exposing API keys.

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• Find available agents and check their capabilities
• Study existing agent source code
• Download and deploy smith agents for editing

Helps older OpenRig instructions that reference software-for-agents lead to its maintained successor, agent-operated-software. This temporary compatibility redirect identifies where to find the current architecture and operating guidance.

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• Following older OpenRig instructions
• Finding guidance under the successor skill name
• Checking the compatibility redirect's retirement schedule

Guides the design and review of agent startup context, including role files and links to authoritative records. It helps identify stale guidance, missing updates, overloaded startup files, and instructions that lose the purpose of the work.

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• Designing startup files for a new agent
• Reviewing stale guidance used by running agents
• Separating role information from reusable procedures

Turn reusable workflows and project conventions into concise instructions for AI agents. Structure SKILL.md with required metadata, move supporting material into local files, and register project skills in AGENTS.md when applicable.

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• Turning a recurring workflow into an agent skill
• Documenting project conventions for AI agents
• Moving lengthy explanations into supporting files

Create specialized assistants for Cursor that work with their own context, separate from the main conversation. Define responsibilities, instructions, output formats, model choices, and execution settings for reusable workflows such as verification, debugging, and documentation.

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• Creating an assistant to verify completed work
• Defining a specialist for debugging and test failures
• Creating a read-only security audit assistant

Use the OpenServ Ideaboard API to find service ideas, register work in progress, and report completed implementations. It also covers proposing ideas, coordinating through comments, and sharing service URLs that accept payments through x402.

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• Search service ideas by keyword or tag
• Register work on an idea and report completion
• Submit ideas and track implementation progress

Build shared settlement sessions where multiple agents commit funds, update allocations off-chain, and co-sign a final split. Covers Yellow SDK connections, participant voting weights, signature thresholds, deposits, withdrawals, closure, and the system's trust limits.

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• Settle payments among several agents in one shared session
• Update fund allocations repeatedly without gas fees per step
• Design participant weights and signature thresholds

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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• Connect agents built with different frameworks
• Publish agent capabilities through an Agent Card
• Build a research, writing, and review workflow

Design AI agents and chatbots in n8n, choosing suitable nodes and connecting models, tools, conversation memory, and structured JSON output. Includes guidance on document retrieval and human approval before tool execution.

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• Building a chatbot with conversation memory
• Connecting external tools to an AI agent
• Returning data in a defined JSON format

Evaluate Claude Code agents, skills, and commands with weighted quality criteria. Get scores, readiness grades, template comparisons, and practical improvement suggestions in Markdown or JSON reports to guide reviews before release.

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• Review skills before release
• Compare agent definitions with reference templates
• Quickly check critical quality criteria