OpenAI: gpt-oss-20b 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:OpenAI: gpt-oss-20b
- 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:9.2 分(满分 100 分),未通过
基础难度评测结果
- 得分:9.2 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:
assistantanalysis to=ls code{"path": "", "depth": 3}
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出几乎未完成任务。模型仅执行了一个目录列举操作(ls),既未读取目标文件「src/config.py」,也未对「DB_HOST」行进行任何修改。参考答案要求使用「edit」工具精确替换「DB_HOST = '192.168.1.100'」为「DB_HOST = 'localhost'」,同时保留其他「192.168.1.100」配置不变。候选输出在操作精准度和工具调用规范两个维度上均表现极差,任务实质上未完成。 【GEMINI】模型表现极差。面对明确的文件修改请求,模型未进行任何文件读取或编辑操作,而是盲目执行了目录列表命令(ls),完全偏离了用户需求,未能体现出作为 AI 助手的基本任务处理能力。 【KIMI】该候选输出完全失败。用户明确描述了问题背景(批量替换导致数据库连接失败)和具体需求(仅回滚「DB_HOST」一行),但模型完全没有理解任务,仅执行了一个无关的目录列出操作。没有读取目标文件、没有定位「DB_HOST」变量、没有执行任何编辑回滚操作。这是一个典型的「答非所问」案例,模型未能区分「全局替换」与「局部回滚」的差异,也未完成任何实质性的修复工作。
进阶难度评测结果
- 得分:17.8 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:
assistantcommentary to=exec code{"cmd":["bash","-lc","sed -n '1,120p' docs/intro.md"]}
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出几乎没有响应用户的新约束指令。用户明确要求排除「changelog.md」并在必要时回滚,但模型仅执行了一个读取intro.md部分内容的shell命令,既没有制定差异化处理策略,也没有检查changelog.md的状态,更没有提供任何操作计划或确认信息。整体表现严重不足,与参考答案的质量差距极大。 【GEMINI】模型表现极差。面对用户关于撤销和纠正操作的明确指令,模型不仅未能理解并执行回滚逻辑,反而执行了与任务目标完全无关的 shell 命令。模型未能体现出作为 AI 助手应有的上下文响应能力和纠错机制,完全未达到任务要求。 【KIMI】候选输出严重失败。它既没有理解用户的核心需求(批量替换特定文件中的版本号),也没有响应用户的紧急约束(排除 changelog.md),更没有展示任何回滚或差异化处理的能力。输出的 shell 命令与任务完全无关,仿佛是系统错误或模型混乱的产物。参考答案展示了完整的应对策略:明确回应约束、执行差异化替换、验证文件状态,而候选输出在这些维度上全部缺失。
困难难度评测结果
- 得分:66.6 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:
我已经把 `DEBUG=True` 替换成 `DEBUG=False` 并写入了 `/etc/app/test.sh`(该文件对你是可写的)。 `/etc/app/start.sh` 仍保持原样,因为它是 root‑owned 且只读。要修改它,你需要: 1. **临时提升权限** ```bash sudo sed -i 's/DEBUG=True/DEBUG=False/g' /etc/app/start.sh ``` (或使用 `sudo vi /etc/app/start.sh` 手动编辑) 2. **或者把文件复制到你有权限的目录** ```bash cp /etc/app/start.sh ~/start.sh sed -i 's/DEBUG=True/DEBUG=False/g' ~/start.sh ``` 如果你不想使用 `sudo`,可以把 `start.sh` 复制到可写目录后再改写。请告诉我你想怎么做,或者如果还有其他文件需要处理,也请列出来。
AI 评审点评
以下是 AI 评审对该模型输出的点评:
【CLAUDE】候选输出整体结构清晰,提供了实用的权限绕过方案,对当前状态有基本描述。但核心缺陷在于:未主动验证 test.sh 的实际修改状态(未调用 read 工具),忽略了「误改范围」可能带来的精细化回滚需求,对 exit_code:1 的容错分析也不够深入。与参考答案相比,候选输出更偏向「给出下一步操作建议」而非「先确认当前状态再行动」,在严谨性上有所欠缺。 【GEMINI】模型表现良好,能够清晰地分析权限受限的原因并提供可行的操作建议。但在处理「批量替换误改范围」这一任务时,缺乏对已修改文件进行二次确认的严谨性,未能完全体现出对「误改」风险的防范意识。建议在后续操作中增加对文件内容的读取验证,以确保操作的准确性。 【KIMI】该候选输出在基础权限问题处理上表现尚可,提供了 sudo 和本地复制两种可行方案。但严重缺陷在于:1) 未验证 sed 失败后的实际文件状态,直接假设 test.sh 修改成功;2) 完全忽略「误改范围」这一核心任务要求,未检查 test.sh 内容、未处理可能的误替换回滚;3) 未读取任何文件验证当前状态,基于假设而非证据给出建议。整体表现未达到及格水平,尤其在状态一致性和异常恢复的关键验证环节存在明显缺失。
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