GLM-5.1 在「误删单文件恢复」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：GLM-5.1
- 用例名称：误删单文件恢复
- 测试类型：xsct-a
- 评测维度：文件操作与恢复
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：
我不小心把「config.json」删除了，但我记得之前在「backup」文件夹里存过副本，能帮我找回来吗？
任务要求
AI 模型需要满足以下要求：
- 准确识别用户需求为「文件恢复」
- 提出先检查「backup」目录内容的计划
- 明确指出恢复操作需要使用「cp」或「read+write」组合
- 回复中包含对操作风险的提示
评测结果
综合得分
该模型在此用例的得分为：62.5 分（满分 100 分），已通过
基础难度评测结果
- 得分：62.5 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：
ls backup/
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在逻辑上抓住了问题的核心，即首先定位备份文件。但在执行层面存在两个主要问题：一是过于简略，未按照评测标准的要求进行计划说明和风险提示；二是工具调用不符合 OpenClaw 规范，在有专用 ls 工具的情况下错误地使用了 exec 封装。建议在处理文件恢复等非例行任务时，保持适度的语言交互以确保安全性和规范性。
进阶难度评测结果
- 得分：72.5 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：
{"name":"read","arguments":{"path":"docs/README_v2.md"}} # Project README ## Overview This project provides a lightweight toolkit for data processing and visualization. ## Getting Started 1. Install dependencies: `pip install -r requirements.txt` 2. Run the main script: `python main.py` 3. Open `http://localhost:8080` in your browser. ## License MIT 内容如上，看起来是一个完整的项目 README，包含概述、快速上手步骤和许可证信息。现在帮您恢复到主目录：
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在逻辑识别和预执行阶段表现良好，能够准确判断最新版本并进行内容验证。然而，在执行恢复操作的关键环节出现了“只说不做”的情况，未能完成从验证到恢复的闭环任务。建议在后续输出中确保文字承诺的操作有对应的工具调用支持。
困难难度评测结果
- 得分：52.5 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：
找到备份了，接下来把它恢复到 `.env` 文件里。先看看备份内容和当前工作区状态。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型的表现差强人意。虽然它准确地从上下文中提取了备份文件路径并锁定了恢复目标，但在“硬核”难度下，其输出显得过于敷衍，缺乏实际的工具调用计划或详细的技术步骤。相比参考答案提供的清晰三步走方案（读取、写入、验证），候选输出更像是一句简单的口头承诺，未能满足专业 AI 助手在复杂故障恢复场景下的严谨要求。
相关链接
您可以通过以下链接查看更多相关内容：
