StepFun: Step 3.5 Flash 在「媒体处理流程」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：StepFun: Step 3.5 Flash
  • 用例名称：媒体处理流程
  • 测试类型：xsct-a
  • 评测维度：插件系统集成

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：

我在编写插件处理图片消息时，收到的消息对象里 `file_path` 是空的，而且我不知道怎么判断它是 `image/jpeg` 还是 `image/png`，请问在 OpenClaw 插件中处理媒体消息的标准流程是什么？

任务要求

AI 模型需要满足以下要求：

  1. 明确指出需要通过「MessageContext」中的「MediaContent」对象获取数据
  2. 说明必须先调用「download_media」方法才能生成有效的本地路径
  3. 指出 MIME 类型应从「MediaContent.mime_type」字段读取而非根据后缀名猜测

评测结果

综合得分

该模型在此用例的得分为：32.0 分（满分 100 分），未通过

基础难度评测结果

  • 得分：32.0 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：

我来帮你了解 OpenClaw 中处理图片消息的标准流程。让我先查看项目文档和现有示例。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】模型未能回答用户关于 OpenClaw 插件处理媒体消息的标准流程问题。虽然它表现出了查找文档的意图（通过 ls 工具调用），但在当前的生成结果中完全缺失了功能要求中明确指出的核心技术点（MediaContent、download_media、mime_type 字段的使用），无法满足用户的技术咨询需求。 【KIMI】整体上，回答没有直接解决用户的问题，也没有覆盖所有核心点。虽然提到了查看项目文档和现有示例，但没有给出具体的解决方案。需要进一步改进。

进阶难度评测结果

  • 得分：67.5 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：

我来帮你分析 `mime_type` 变成 `application/octet-stream` 的问题。这通常有几种可能： 1. **SDK 识别失败**：下载时无法从响应头或文件内容确定类型 2. **文件扩展名缺失/不匹配**：视频没有正确扩展名 3. **转码前的临时状态**：某些 SDK 在下载完成前会先给默认类型 建议你： **A. 先确认原始消息的类型** ```python print(f'Original mime: {ctx.message.content.mime_type}') ``` **B. 下载后重新检测文件真实类型**（推荐）： ```python import magic # pip install python-magic # 下载后 real_type = magic.from_file(path, mime=True) print(f'Detected mime: {real_type}') ``` 如果 `magic` 检测为 `video/*` 而 SDK 给的是 `application/octet-stream`，说明 SDK 的元数据有问题，你应该依赖文件内容检测而非 SDK 提供的 `mime_type`。 **C. 备用方案：从扩展名推断** ```python ext = os.path.splitext(path)[1].lower() video_exts = {'.mp4', '.mov', '.avi', '.mkv', '.webm', '.flv'} if ext in video_exts: # 当作视频处理 ``` 你能分享一下转码逻辑的具体代码吗？这样我可以给出更精确的优化建议。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出在本轮对话中针对 MIME 降级问题给出了较为专业的解答，核心建议（使用 python-magic 做文件头检测）与参考答案吻合，代码示例清晰实用。然而两个维度均有同一个明显缺口：完全忽略了 manifest.json 中 media_settings.max_size 配置的影响，未将「文件因超限被截断导致文件头损坏」纳入分析链路，这是参考答案明确要求的检查点。整体回答质量中等偏上，但在系统性故障排查和配置联动分析方面仍有提升空间。 【GEMINI】模型能够针对 MIME 类型识别失效问题提供专业且有效的技术方案，代码实现建议准确。但在故障排查的全面性上，未能充分利用已知的 manifest.json 配置信息进行关联分析，导致排查深度略有不足。整体表现良好，符合中等难度任务的要求。 【KIMI】候选输出在 MIME 识别失效的应对上提供了基本可行的技术方案（python-magic），但严重遗漏了对话上下文中的核心故障点（await 异步调用），且未覆盖 manifest.json 配置检查的要求。故障排查维度不及格，方案深度勉强及格。候选输出更像是通用技术建议，而非针对特定上下文的精准诊断。

困难难度评测结果

  • 得分：23.0 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：

权限被拒绝。让我检查一下该目录的所有权和权限设置，看看是否需要调整。

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【GEMINI】生成结果非常平庸，且具有严重的复读倾向。在对话上下文已经明确指出权限问题后，模型未能给出任何实质性的解决方案，而是选择继续停留在“检查”阶段，完全没有体现出专业 AI 评测专家或高级助手的解决问题能力。相比参考答案提供的系统级修复方案、代码加固和发布建议，该输出几乎没有参考价值。 【KIMI】整体上，候选人输出显示了对问题的基本理解，但缺乏深度和具体的解决方案。需要更详细的分析和具体的解决步骤。

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