OpenAI: GPT-4o-mini 在「Schema 设计缺陷」的评测结果

基本信息

• 模型名称：OpenAI: GPT-4o-mini
• 用例名称：Schema 设计缺陷
• 测试类型：xsct-a
• 评测维度：插件系统集成

系统提示词（System Prompt）

这是给 AI 模型的背景设定和角色指令：

You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).

用户提示词（User Prompt）

这是用户给 AI 模型的具体任务要求：

我在开发 OpenClaw 插件，发现用户如果不写「api_key」插件就会崩溃。我该如何在「schema」里强制要求这个字段必填，并给「unit」字段设置默认值为「metric」？

任务要求

AI 模型需要满足以下要求：

1. 指出在「config_schema」中使用「required」数组来定义必填项
2. 说明如何在字段属性中使用「default」关键字设置默认值
3. 提供符合 JSON Schema 规范的代码片段

评测结果

综合得分

该模型在此用例的得分为：91.5 分（满分 100 分），已通过

基础难度评测结果

• 得分：91.5 分
• 通过状态：已通过

模型生成产物

以下是该模型针对此任务的实际生成内容：

要在 OpenClaw 插件的 `schema` 中强制要求 `api_key` 字段必填，并将 `unit` 字段的默认值设置为 `metric`，你可以按照以下方式定义你的 `schema`： ```json { "type": "object", "properties": { "api_key": { "type": "string", "minLength": 1 }, "unit": { "type": "string", "default": "metric" } }, "required": ["api_key"] } ``` 在这个定义中： - `api_key` 字段被标记为必填，使用了 `required` 属性，并确保其最小长度为 1。 - `unit` 字段设置了默认值为 `metric`。 确保将这个 `schema` 结构应用到你的插件配置中，这样用户在不提供 `api_key` 时插件就会提示错误，且 `unit` 字段在未提供时将自动使用默认值。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型回复质量较高，准确覆盖了参考答案的核心要点：使用 `required` 数组强制 `api_key` 必填、使用 `default` 为 `unit` 设置默认值，并提供了符合 JSON Schema 规范的完整代码示例。额外的 `minLength: 1` 校验是合理的增强，体现了对实际开发场景的理解。表达清晰，结构合理，开发者可直接参考应用。 【GEMINI】模型表现优秀，不仅准确回答了用户关于 Schema 配置的问题，还通过增加「minLength」约束提升了代码的健壮性。回复逻辑严密，符合专业开发指导的标准。 【KIMI】模型生成的回复在技术实现上是正确的，JSON Schema 定义完全符合规范，能够解决用户提出的两个问题（强制必填和设置默认值）。主要不足在于对 OpenClaw 特定上下文的呼应不够完整——未明确提及「config_schema」在「manifest.json」中的位置，也未说明框架会在加载阶段进行拦截报错的行为。但这些属于上下文完整性的细微差别，核心功能实现准确无误。

进阶难度评测结果

• 得分：92.5 分
• 通过状态：已通过

模型生成产物

以下是该模型针对此任务的实际生成内容：

以下是修改后的完整「schema.json」内容： ```json { "type": "object", "properties": { "retry_count": { "type": "integer", "minimum": 0, "default": 3 } } } ``` 我将其写入「schema.json」文件中。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【KIMI】候选输出高质量完成了任务核心需求，类型修正、数值约束、默认值设置均正确实现，JSON 结构规范。虽缺少可选的「description」字段，但不影响功能正确性和用户体验，整体表现优秀。

困难难度评测结果

• 得分：20.2 分
• 通过状态：未通过

模型生成产物

以下是该模型针对此任务的实际生成内容：

我将重新运行检查以确认这些更改是否解决了之前的问题。请稍等。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】模型生成结果极度简短且无实质内容，仅表示「将重新运行检查」，完全未完成任务要求。与参考答案相比，缺少验证命令建议、嵌套约束说明、代码层面的兼容性提示等所有核心要素。这是一个典型的「占位式回复」，在功能完成度和技术深度上均严重不足，整体表现不及格。 【GEMINI】模型表现不佳。在完成初步修复后，未能展现出对工程任务的完整闭环处理能力。面对用户的后续询问，回复过于敷衍，未能提供必要的专业建议（如验证、兼容性检查等），导致用户体验断层。 【KIMI】该生成结果严重不符合任务预期。用户基于预设上下文已经完成了「manifest.json」的修复（patch 成功），明确询问「现在呢？」是寻求修复确认和发布前建议，而非请求再次执行检查。模型的回复是一个空洞的「将重新运行检查」的承诺，既未确认修复结果，也未提供任何技术价值。与参考答案相比，模型完全遗漏了：验证嵌套约束的建议、最终检查命令「openclaw-sdk validate --strict」、兼容性说明（parseInt 移除）、发布就绪判断等关键内容。该回复在功能要求的所有维度上均未达标，属于典型的「回避型」低质量回复。

相关链接

您可以通过以下链接查看更多相关内容：

• 查看所有模型在此用例的表现：「Schema 设计缺陷」
• 查看该模型的所有评测结果：OpenAI: GPT-4o-mini
• 浏览同维度的其他用例：「插件系统集成」
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