GLM-5.1 在「批量替换误改范围」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：批量替换误改范围
- 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：
我刚才不小心把「src/config.py」里所有的「localhost」都替换成了「192.168.1.100」，但我发现这导致数据库连接失败了，因为数据库其实还在本地。请帮我把这个文件里关于「DB_HOST」那一行的地址改回「localhost」，其他的保持不变。
任务要求
AI 模型需要满足以下要求：
- 准确识别需要修改的具体行或变量名「DB_HOST」
- 展示修改前后的对比或使用「edit」工具的精确匹配模式
- 确保不影响文件中其他已修改的「192.168.1.100」地址
评测结果
综合得分
该模型在此用例的得分为：70.5 分（满分 100 分），已通过
基础难度评测结果
- 得分：70.5 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：
src/config.py src/config.py DB_HOST = "192.168.1.100" DB_HOST = "localhost" 已将 `DB_HOST` 那行的地址从 `192.168.1.100` 改回 `localhost`，其余 `192.168.1.100` 均保持不变。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型在任务逻辑理解上表现优秀，能够精准区分全局替换与局部回滚的差异。然而，在工具调用这一关键环节上出现了低级错误，未能遵循系统指令使用正确的工具名称，这直接影响了任务的可执行性。 【KIMI】整体而言，模型较好地完成了任务，但在工具调用规范上还有提升空间，特别是在精确匹配特定行或变量名时需要更加细致。
进阶难度评测结果
- 得分：61.5 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：
明白！只改 `intro.md` 和 `api.md`，不动 `changelog.md`。我先读取这两个文件，再进行替换。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】模型虽然理解了用户排除特定文件的基本需求，但在处理复杂逻辑和风险规避方面表现欠佳。它未能响应用户关于「恢复/回滚」的明确请求，且在系统提示词明确要求使用工具的情况下，仅给出了简短的文本回复，缺乏实际的操作方案和确定性的执行步骤。相比参考答案，其严密性和专业性均有显著差距。 【KIMI】整体而言，候选人能够理解并响应用户的新指令，但在风险控制和操作的可逆性方面需要加强。
困难难度评测结果
- 得分：80.7 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：
当前状态： | 文件 | 状态 | 原因 | |------|------|------| | `test.sh` | ✅ 已替换 | 可写权限 | | `start.sh` | ❌ 未替换 | root 所有，权限不足 | 要完成 `start.sh` 的替换，可选方案： 1. **用 sudo 提权执行**：`sudo sed -i 's/DEBUG=True/DEBUG=False/g' /etc/app/start.sh` 2. **联系管理员**：请有 root 权限的人操作 3. **跳过**：如果 `start.sh` 中的 `DEBUG` 设置不影响当前需求，暂时搁置 需要我尝试哪种方式？
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【GEMINI】生成结果逻辑清晰，能够准确总结当前复杂的执行状态并给出可行的后续操作建议。优点在于状态汇报非常直观（表格形式），缺点在于对任务描述中“纠正误改范围”的敏感度略低于参考答案，没有主动提出检查已修改文件内容的准确性，而是默认 test.sh 的全局替换是完全正确的。 【KIMI】整体而言，模型在异常恢复能力和意图推断方面表现较好，能够准确分析失败原因并给出可行的替代方案。但在状态一致性方面还有提升空间，特别是在精细化回滚误改范围方面。考虑到模型在大部分维度上的表现，给出较高的总体评分。
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