Mistral: Mistral Nemo 在「发布复盘汇报」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：Mistral: Mistral Nemo
- 用例名称：发布复盘汇报
- 测试类型：xsct-a
- 评测维度：PPT 与汇报生成
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：
这是昨天的发布日志：1. 22:00 开始发布，23:30 完成，比预期晚了 1 小时。2. 原因是数据库迁移脚本在生产环境执行缓慢。3. 发布后监控显示 CPU 占用率提升了 15%。请为我生成复盘提纲。
任务要求
AI 模型需要满足以下要求：
- 提纲必须包含「结论」、「问题」和「行动项」三个逻辑层次
- 准确提取日志中的时间延误、数据库脚本、CPU 占用等关键信息
- 输出格式为页级提纲，每页包含标题和要点
评测结果
综合得分
该模型在此用例的得分为：62.0 分（满分 100 分），已通过
基础难度评测结果
- 得分：62.0 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：
Based on the provided information, here's a summary and a suggested outline for the post-mortem meeting: **Summary:** - Release started at 22:00 and finished at 23:30, 1 hour behind schedule. - The delay was caused by slow execution of the database migration script in the production environment. - After the release, CPU usage increased by 15%. **Post-Mortem Meeting Outline:** 1. **Introduction (5 min)** - Brief recap of the release process and timeline. - Purpose of the meeting: Understand what went wrong, why it happened, and how to prevent it in the future. 2. **Timeline of Events (10 min)** - Walk through the release timeline, highlighting key events and decisions. - Identify any bottlenecks or unexpected issues that caused delays. 3. **Root Cause Analysis (15 min)** - Deep dive into the slow execution of the database migration script. - Discuss potential factors contributing to the slow performance, such as script efficiency, database state, or hardware issues. 4. **Impact Analysis (10 min)** - Assess the impact of the delayed release on users, services, and the business. - Discuss the 15% increase in CPU usage post-release and its potential consequences. 5. **Lessons Learned (10 min)** - Identify preventive measures for future releases, such as optimizing scripts, thorough testing, and better resource allocation. - Consider implementing monitoring and alerting improvements to quickly detect and address performance issues. 6. **Action Items (5 min)** - Assign responsible parties for each action item. - Set clear deadlines for follow-up tasks. 7. **Conclusion and Next Steps (5 min)** - Summarize the key takeaways from the meeting. - Define next steps, including immediate actions and long-term improvements. - Adjourn the meeting with a plan for follow-up discussions or progress updates.
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型理解了复盘的基本意图，并正确识别了日志中的关键信息，但输出形式与任务要求存在明显偏差：格式上采用了会议议程而非页级提纲，结构上未能清晰呈现「结论→问题→行动项」三层逻辑，语言上使用英文而非中文。整体而言，内容覆盖度尚可，但结构化表达能力明显不足，难以直接用于正式复盘汇报场景。 【GEMINI】模型能够准确捕捉并概括原始日志中的所有关键信息，但在执行「页级复盘提纲」这一特定格式要求时，将其处理成了会议流程安排。虽然内容专业且逻辑通顺，但未严格遵循提示词中关于「结论、问题、行动项分层清晰」且「每页包含标题和要点」的结构化格式要求。 【KIMI】模型未能理解题目要求的「复盘提纲」格式，误将任务理解为「会议议程设计」，导致结构完全偏离。虽然原始信息提取基本完整，但输出形式与用户需求差距较大，结构化表达维度不及格。建议加强对「分层清晰」「页级提纲」等格式要求的理解，避免将复盘报告写成会议流程。
进阶难度评测结果
- 得分：51.8 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：
好的，我会将「缺口分析」作为重点，并给出改进建议。以下是复盘汇报的第一个部分： --- **复盘汇报：内存抖动高于标准值的分析及改进建议** **1. 缺口分析** 根据发布纪要，内存峰值高达 4GB，超过公司标准 3GB 的上限。这表明我们的内存管理存在缺口。 **2. 原因分析** - **内存泄漏**：应用程序可能存在未关闭的连接或未释放的内存块。 - **性能瓶颈**：系统资源可能无法满足当前负载需求。 - **算法优化**：内存使用效率可能不高。 **3. 改进建议** - **内存泄漏检测**：使用工具（如 Valgrind、LeakSanitizer）定期检测内存泄漏，并修复相关问题。 - **性能优化**：评估系统资源，必要时进行扩展或升级。同时，考虑使用更高效的算法或数据结构。 - **内存使用优化**：优化内存使用策略，例如使用缓存、内存池，或考虑使用更轻量级的数据结构。 - **监控与报警**：加强内存使用情况的监控，设置报警阈值以及早发现内存问题。 ---
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型生成结果基本理解了任务意图，能够识别内存超标这一核心问题，并给出了若干改进方向。但与参考答案相比，存在两个主要差距：一是信息整合深度不足，未能真正体现「文件+网页」双源对比分析，缺乏发布期间具体现象的描述；二是改进建议缺乏针对性，未结合公司技术栈和工具链（JVM 参数、OpenClaw 监控插件），也未给出量化目标。此外，输出结构未严格遵循「结论-问题-行动项」的分层规范，整体质量处于及格线附近。 【GEMINI】模型完成了基本的复盘框架，但未能严格遵循任务要求的「分层清晰」及「页级产出」格式。在信息整合上，缺乏对性能标准网页的深度挖掘；在行动项上，建议过于模板化，缺乏针对本次性能违规问题的具体执行路径。 【KIMI】模型生成结果未能满足任务核心要求。信息整合层面，缺失网页来源的显性引用和页级结构规范；方案针对性层面，建议过于通用，未结合OpenClaw工具链和发布复盘场景。虽识别了4GB vs 3GB的基本事实，但缺口分析的量化表达、分层结构和行动项的具体性均不达标，整体处于及格线以下。
困难难度评测结果
- 得分：22.0 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：
现在，我需要获取「API 兼容性检查失败」的细节，并查看哪些下游服务报错。我将运行以下命令以获取更多信息： - `read ./backup/deploy_summary.json`：查看发布汇总记录 - `grep "error" ./backup/api_check.log`：获取 API 检查过程中的错误消息 - `grep "error" /logs/services/*`：搜索下游服务中的错误消息 一旦我获得了这些信息，我将能够更好地理解问题出在哪里，并提出解决方案。
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型在本次任务中表现极差。核心问题在于：用户已追问「现在呢？」，上下文也已明确提示关键信息已获取，模型理应直接输出结构化复盘报告（结论、问题、行动项分层），但模型却仍停留在「信息收集规划」阶段，重复提出读取文件和搜索日志的意图，完全没有推进到分析和输出环节。这既是对对话状态的误判，也是对任务目标的偏离。与参考答案相比，模型输出的内容量和质量均远低于预期，无法满足「发布复盘汇报」的基本要求。 【GEMINI】模型未完成任务目标。在已经掌握核心矛盾的情况下，模型未能根据用户指令「发布复盘汇报」进行总结，而是陷入了冗余的工具调用循环中，未能体现出对复盘任务的结构化处理能力，回复风格也不符合专业汇报的要求。 【KIMI】模型生成结果与测试任务要求严重偏离。核心问题在于：1）完全忽视预设上下文中已完成的异常恢复和信息获取过程，重复提出信息收集动作；2）未响应用户「现在呢？」的追问，未输出任何复盘结论；3）完全缺失「结论-问题-行动项」的分层结构；4）未体现对「强制发布」和「API兼容性」冲突的深度理解。该输出在功能要求的所有关键点上均未达标，属于典型的上下文理解失败和任务执行偏差。
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