“agents”的搜索结果

Claude Code（.claude）と Codex（.codex / .agents / AGENTS.md）に分裂したエージェント設定を、 実ファイル1つ + symlink と双方向変換で単一化・同期するスキル。 実ファイルをどちら側に置くか（symlink の向き）は共通設定 source で選べる。 プロジェクト単位の導入ウィザード、既に分裂しているリポジトリを危険度の低い順に解決する手順、 片方しか無いリポジトリへもう片方を生成する scaffold、書き換え前のバックアップと復元、常駐の管理を含む。 「エージェント設定を同期して」「.codex と .claude がずれている」「Codex でも同じスキルを使いたい」 「AGENTS.md と CLAUDE.md を一本化したい」「MCP を Codex でも使えるようにして」 「サブエージェントを Codex 側にも作って」「設定の分裂を解消して」「元に戻して」 「agents-sync」「同期デーモン」などと言われたら使う。 Keywords: agents-sync, エージェント設定同期, .claude, .codex, .agents, AGENTS.md, symlink 統合, symlink の向き, 実ファイルを置く側, 双方向同期, scaffold, 分裂解消, MCP 同期, hooks 同期, サブエージェント同期, バックアップ, 復元, fswatch, launchd, 常駐デーモン

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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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• Set up agents-cli and its specialized skills
• Document agent requirements before writing code
• Find the workflow for creating and evaluating an ADK agent

帮助编写和编辑AI代理阅读的技能及指令文档，整理操作步骤、参考信息和完成条件，明确何时阅读相关资料，并减少重复内容。

• 编写或编辑技能文档
• 整理AGENTS.md和CLAUDE.md
• 明确阅读参考资料的条件

Create, update, or audit AGENTS.md instructions using evidence from repository files and CI workflows. Preserve maintainer policies while clarifying commands, validation steps, and directory-specific rules that guide coding agents.

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• Creating AGENTS.md from repository evidence
• Correcting stale commands and duplicated rules
• Organizing root and package-level instructions

Analyze a codebase to create project-specific AGENTS.md instructions and supporting rule files. Detect the package manager and relevant conventions, preview proposed changes, or update existing guidance when the project’s tools change.

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• Create agent instructions tailored to an existing project
• Generate a minimal AGENTS.md file
• Refresh instructions after changing development tools

Build AI agents on Cloudflare Workers with the Agents SDK. Implement persistent state, real-time chat, scheduled tasks, multi-step background workflows, and MCP servers, using current Cloudflare documentation to guide implementation.

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• Build agents that retain and synchronize state
• Create real-time chat with resumable streaming
• Implement scheduled tasks and multi-step workflows

Use when you need to install the embedded robot agents into .github/agents, .claude/agents, .cursor/agents, or .codex/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .github/agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Bootstrap .codex/agents; Copy robot agents. Part of Plinth Toolkit

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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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• Registering multiple agents from JSON definitions
• Synchronizing changes to agent instructions
• Preparing a manifest and synchronization script

Browse available specialist agents by domain, select up to five, and run them independently on the same task in parallel. Receive a combined report showing each agent’s findings, shared conclusions, conflicting recommendations, and suggested next steps.

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• Browsing available specialist agents
• Selecting agents from different domains
• Reviewing a site for security and SEO before launch

Document a project's structure, commands, and specific conventions in a hierarchy of AGENTS.md files. Analyze directory complexity to choose useful locations, update existing guidance, and check that child files avoid repeating their parents.

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• Create project guidance for coding agents
• Refresh existing AGENTS.md documentation
• Document rules specific to complex directories

Documents a codebase with linked AGENTS.md files that explain each directory, important files, dependencies, and working rules. It can also update existing documentation while preserving human-written notes and checking that the document hierarchy remains consistent.

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• Documenting an unfamiliar codebase for AI agents
• Recording directory-specific rules and dependencies
• Updating documentation after structural changes

Create an AGENTS.md file that explains how coding agents should work in a project. Examine its structure and existing configuration, then document setup commands, development workflows, tests, coding conventions, builds, and contribution requirements.

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• Creating project instructions for coding agents
• Documenting setup and test commands
• Organizing instructions across monorepo packages

Build and operate AutoGPT agents that carry out multi-step workflows. Covers a visual editor for connecting processing blocks, scheduled and webhook triggers, deployment, execution monitoring, and benchmarks for evaluating agent performance.

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• Build an AI workflow in a visual editor
• Run agents on a schedule or external event
• Add custom agent abilities with Forge

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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Coordinate a task from a verifiable goal through completion. Handle work directly or split independent tasks across separate agent sessions, track progress, verify results, and arrange pull request merging when included in the goal.

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• Split independent tasks across agents
• Check progress across ongoing tasks
• Resume a previously started project

Create and maintain repository instructions for AI agents in AGENTS.md. Check rules against project evidence, preserve existing requirements during revisions, and record observed mistakes so future agents receive concise, relevant guidance for working in the codebase.

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• Creating or consolidating repository instructions for AI agents
• Updating and auditing rules after project changes
• Recording recurring or costly agent mistakes

Helps build AI agents in .NET with persistent conversation threads. Covers messages, execution status, streaming responses, document search, and custom function calls using Azure.AI.Agents.Persistent, with examples for creating agents and cleaning up resources.

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• Build an AI assistant that retains conversation threads
• Answer questions using uploaded documents
• Connect an agent to custom functions

Create, design, and validate agents for Microsoft 365 Copilot. The skill guides JSON configuration or TypeSpec definitions, a typed alternative, alongside local testing, enterprise requirements, and deployment planning with Microsoft 365 Agents Toolkit.

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• Build a prototype agent for Microsoft 365 Copilot
• Plan enterprise features and multilingual support
• Validate an existing agent's configuration

Reorganize long AGENTS.md, CLAUDE.md, and similar instruction files into a short main file with links to topic-specific documents. Identifies conflicting rules and deletion candidates, then checks links and coverage so instructions remain organized and accessible.

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• Shorten an oversized AGENTS.md
• Split CLAUDE.md into topic-specific files
• Resolve conflicting agent instructions

Reduce the size of AGENTS.md or RESOLVER.md by grouping skills into functional areas. Each area keeps a list of its sub-skills, helping the agent find the appropriate skill through a two-level routing structure.

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• Shortening a large AGENTS.md
• Grouping skill routes by functional area
• Checking routing accuracy after compression

Turn an idea, existing code, or a previous Codex conversation into a runnable OpenAI Agents SDK app. Supports local verification, focused evaluations of agent behavior, and local deployment through the Deployment Manager.

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• Build a runnable agent prototype from an idea
• Adapt existing code into an agent app
• Turn a previous Codex conversation into an app

Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.

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Use when you need to install the embedded robot agents into either .cursor/agents or .claude/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Copy robot agents. Part of cursor-rules-java project

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Claude Code プラグインを Codex CLI 互換形式に変換。SKILL.md → .agents/skills/、agents → .agents/skills/、AGENTS.md 生成。「deploy」「codex」「Codex 変換」「エクスポート」などで自動適用。

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