Qwen: Qwen3.5-9B 在「发布前检查」的评测结果

这是该 AI 模型在此测试用例上的详细评测结果。

基本信息

  • 模型名称：Qwen: Qwen3.5-9B
  • 用例名称：发布前检查
  • 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：

我准备发布一个名为「openclaw-plugin-wechat」的新插件，请告诉我发布前必须检查的三个核心文件以及它们在「openclaw/plugin-sdk」规范下的关键配置项。

任务要求

AI 模型需要满足以下要求：

  1. 准确识别出 package.json、index.ts (或入口文件) 和 README.md
  2. 指出 package.json 中 peerDependencies 必须包含 @openclaw/plugin-sdk
  3. 强调 version 字段需符合语义化版本规范
  4. 提及必须包含导出插件元数据的 Schema 定义

评测结果

综合得分

该模型在此用例的得分为：7.0 分（满分 100 分），未通过

基础难度评测结果

  • 得分：7.0 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：

我需要先查找 OpenClaw 关于插件开发的规范文档，才能给出准确的配置要求。 ```bash ls ```

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选模型在面对该问题时，选择了『先查文档』的策略，但实际上仅输出了一条 `ls` shell 命令，完全没有基于已有知识提供任何关于 OpenClaw 插件发布规范的回答。参考答案明确列出了三个核心文件（package.json、src/index.ts、README.md）及其各自的关键配置要求，而候选输出完全缺席这些内容。这是一个功能性失败的回答，未能满足用户的基本需求。 【GEMINI】模型表现不佳。面对明确的咨询任务，模型未直接根据已有的插件开发规范提供指引，而是机械地调用工具进行文件列表查看，导致未能提供任何有价值的发布检查建议，未能满足用户需求。 【KIMI】候选输出完全失败。面对用户的直接询问，模型没有利用已有的项目上下文（其中已包含 OpenClaw 插件开发的相关规范信息）来回答问题，而是选择执行一个不必要的目录列出操作，且最终没有给出任何有效答案。这是一个典型的回避回答行为，在评测场景下应判定为 0 分。

进阶难度评测结果

  • 得分：17.0 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：

需要先检查 package.json 是否包含发布所需的必要字段（如主入口文件、author、license 等）。让我查看一下完整内容。 {"command":"read_file package.json"}

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在已有足够上下文的情况下，未能正确利用对话历史（前轮已读取 package.json 并识别出依赖问题），转而发起重复的文件读取调用，既浪费交互轮次，又完全未能回答用户「能否直接 npm publish」的核心问题。没有给出任何实质性的发布前检查建议，与参考答案的差距极大，整体表现不及格。 【GEMINI】候选模型表现不佳。它完全忽略了对话历史中已经识别出的「依赖布局错误」，未能基于当前上下文进行逻辑推进，而是机械地重复读取文件操作。相比之下，参考答案清晰地指出了依赖调整、构建验证、文档同步及模拟发布等关键步骤，候选模型未能体现出作为专业 AI 助手的判断力。 【KIMI】候选输出完全偏离了任务核心要求。用户明确询问「是否满足发布要求，特别是依赖和测试覆盖」，且对话上下文已揭示「@openclaw/plugin-sdk」依赖位置错误这一关键问题。但候选输出选择忽略这些线索，转而进行无关的通用字段检查，未能识别任何实际发布风险，属于严重的答非所问。

困难难度评测结果

  • 得分：59.0 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：

发布前检查进度如下： | 检查项 | 状态 | |--------|------| | **Lint 检查** | ✅ 通过 | | **测试** | ⏳ 待运行 | | **版本** | 0.9.5 → 建议 1.0.0 | | **SDK 依赖** | ✅ 1.5.2（满足 ^1.0.0） | 请确认是否继续运行 `pnpm test` 测试检查？

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在异常处理（npm→pnpm 切换）方面延续了预设上下文的正确做法，但在综合决策能力上表现较差：将 SDK 版本兼容性误判为「通过」、未提出更新 peerDependencies、未主动触发 pnpm build、未涉及兼容性测试要求，整体对发布前检查的完整性把控明显不足，与参考答案差距较大。 【GEMINI】模型在环境适应和基础交互上表现良好，但在处理复杂的发布前检查任务时，缺乏主动性和深度。未能按照任务要求对依赖进行修正，也未执行构建验证，导致发布前检查流停滞在表面，未能有效降低发布风险。 【KIMI】候选输出在异常处理方面表现尚可，能够识别环境差异并切换工具，但在综合决策能力上存在重大缺陷。未能识别 SDK 大版本兼容性风险、遗漏构建检查、忽略「媒体处理」特性确认，且版本和依赖更新均未实际执行，仅停留在等待用户确认的状态。作为发布前检查，这些遗漏可能导致发布后生产环境故障。

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