--- 格式版本: 2 标题: "Define tools – Plugins | OpenAI Developers" 原文链接: "https://developers.openai.com/plugins/plan/tools" 发布日期: "2026-08-16" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Published Time: Sun, 16 Aug 2026 09:34:36 GMT" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 4 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-08-16T23:57:25+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-08-16T23:54:06+08:00" 入库时间: "2026-08-16T15:57:25.282Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://developers.openai.com/blog" 匹配关键词: - "deployment" - "performance" - "latency" - "throughput" - "AI" 相关厂家: - "OpenAI" - "Microsoft" - "AWS" - "Google" - "Oracle" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 6 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "页面为OpenAI插件开发文档导航入口，仅含菜单链接，无任何超节点/AI Rack/机柜级基础设施相关内容，明显无关。" AI质检模型: "tx-deepseek-v4-flash" AI质检时间: "2026-08-16T23:57:44+08:00" AI主题相关性: 0 AI来源权威性: 5 AI新颖性: 0 AI技术细节: 0 AI商业部署信号: 0 AI完整性: 1 AI摘要: "该页面是 OpenAI 开发者文档中关于“Define tools”的插件文档页；页面可见内容仅为网站导航和文档索引，并未展示具体定义工具的操作正文。" AI摘要模型: "ali-deepseek-v4-flash" AI摘要时间: "2026-09-07T03:27:29.713Z" 采集批次: "2026年8月16日20点37分10秒" 采集批次ID: "20260816-203710-016" 去重键: "https://developers.openai.com/plugins/plan/tools" --- Title: Define tools – Plugins | OpenAI Developers URL Source: https://developers.openai.com/plugins/plan/tools Published Time: Sun, 16 Aug 2026 09:34:36 GMT Markdown Content: For the complete documentation index, see [llms.txt](https://developers.openai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to the page URL. 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Copy Page Tools are the actions and data that a plugin’s MCP server exposes to ChatGPT and Codex. Define them after you [brainstorm use cases](https://developers.openai.com/plugins/plan/use-case) and before you implement the server. Every tool should help complete a user goal. Do not mirror an internal API without considering how people will ask for and use the capability. ## Map use cases to tools For each supported use case: 1. Write the outcome the user expects. 2. List the information required to produce that outcome. 3. Identify the reads, writes, or external actions the server must perform. 4. Group operations that represent one coherent action. 5. Split operations when they have different permissions, safety risks, or confirmation requirements. For example, a project plugin might expose: * `list_projects` to find projects. * `get_project` to inspect one project. * `create_project` to create a project. * `update_project` to change project details. * `archive_project` to perform a consequential state change. Separate read and write behavior so the model and user can distinguish information retrieval from actions that change state. ## Define each contract Record the following for every proposed tool: | Field | What to define | | --- | --- | | Name | A stable, action-oriented identifier. | | Title | A concise human-readable action. | | Description | The user goal and conditions that should trigger the tool. | | Input schema | Required and optional parameters, types, allowed values, and limits. | | Output schema | Structured fields the model can inspect and reuse. | | Authorization | The account, role, or resource access the server must verify. | | Side effects | Data or external state the tool can change. | | Failure behavior | Errors the model can explain or recover from. | Use explicit inputs. Do not depend on the model guessing identifiers, account scope, or other values that are required for correctness. Return stable identifiers and enough structured information for follow-up calls. Keep secrets, access tokens, internal diagnostics, and unnecessary personal data out of results. ## Write descriptions for selection The model uses tool descriptions to decide when a tool fits a request. Describe the user intent, not the implementation. Good descriptions: * State what the tool does. * Explain when to use it. * Distinguish it from similar tools. * Call out important limits or prerequisites. Avoid descriptions that only restate the tool name or expose internal service terminology that users do not know. ## Plan safety annotations Assign annotations based on actual behavior. See the MCP [`ToolAnnotations` schema](https://modelcontextprotocol.io/specification/2025-11-25/schema#toolannotations) for the canonical definitions, defaults, and interactions between these hints: * `readOnlyHint` is `true` only when the tool cannot change state. * `destructiveHint` is `true` when the tool can cause irreversible or difficult to reverse outcomes. * `openWorldHint` is `true` when the tool can affect public or external systems. Annotations do not replace server-side authorization, input validation, or confirmation for consequential actions. ## Check coverage and boundaries Compare the proposed tools with the complete use-case inventory: 1. Confirm that every supported use case has a path to a useful result. 2. Identify tools that do not serve a documented use case. 3. Look for missing reads that users need before taking a write action. 4. Verify that unsupported requests produce an understandable limitation instead of an unsafe approximation. 5. Test whether two similar tools have overlapping descriptions that could confuse selection. Keep the resulting tool plan as an implementation and evaluation checklist. Then [build the MCP server](https://developers.openai.com/plugins/build/mcp-server) and test each contract with representative, invalid, and unauthorized inputs. [Previous Brainstorm use cases](https://developers.openai.com/plugins/plan/use-case) Ask AI ## Docs agent Loading docs agent...