kimi-k2.5 在「地址信息整理入档」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：kimi-k2.5
- 用例名称：地址信息整理入档
- 测试类型：xsct-a
- 评测维度：文档多轮对话
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：
请帮我创建一个文件 addresses.md，把以下5个地址按统一格式整理进去，每条地址单独一行，格式为「序号. 区域 - 街道/路名 - 小区/楼栋名称」，如果地址中没有明确的街道/路名则该字段填"无"。地址如下： 1. 滨海区锦绣新城夏园 2. 青山区云栖里巷 3. 青山区云栖里花园 4. 青山区观澜路博雅学府B座 5. 海岳区望江路瀚海公馆小区
任务要求
AI 模型需要满足以下要求：
- 创建名为 addresses.md 的文件
- 文件中包含5条地址，每条单独一行
- 每条地址格式为「序号. 区域 - 街道/路名 - 小区/楼栋名称」
- 对于没有明确街道/路名的地址，街道/路名字段填写"无"
- 地址顺序与用户提供的顺序一致
评测结果
综合得分
该模型在此用例的得分为：94.8 分（满分 100 分），已通过
基础难度评测结果
- 得分：94.8 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：
我将为您创建 addresses.md 文件，按照指定格式整理这5个地址：write('addresses.md', '''1. 滨海区 - 无 - 锦绣新城夏园 2. 青山区 - 云栖里巷 - 无 3. 青山区 - 无 - 云栖里花园 4. 青山区 - 观澜路 - 博雅学府B座 5. 海岳区 - 望江路 - 瀚海公馆小区''')
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】候选模型表现优秀，地址拆分逻辑清晰准确，格式规范，5条地址的区域、街道/路名、小区/楼栋名称三个字段均与参考答案高度吻合。特别是第2条「云栖里巷」的合理判断和第3条「云栖里花园」的区分处理符合预期。工具调用方式和文件命名均正确。整体完成度很高。 【GEMINI】模型表现优秀，准确理解了任务需求，不仅严格执行了文件创建操作，而且在地址信息的逻辑拆分和格式化处理上完全符合要求，无任何遗漏或错误。 【KIMI】候选输出整体质量优秀，成功完成了创建文件、格式化地址、正确拆分字段的任务。格式完全规范，5条地址全部包含且顺序正确。字段拆分方面，对于「云栖里巷」的处理存在多种合理理解方式，候选方案（作为街道/路名，小区填无）是一种可接受的合理拆分。唯一可优化的是第2条地址的语义理解，但不影响整体功能完成度。
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