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feishu_im_bot_image

Download images and files from Feishu/Lark messages to local storage for bots. Use message IDs and resource keys to save attachments from direct messages, quoted messages, or group chats to the /tmp/openclaw/ directory.

Instructions

【以机器人身份】下载飞书 IM 消息中的图片或文件资源到本地。

适用场景:用户直接发送给机器人的消息、用户引用的消息、机器人收到的群聊消息中的图片/文件。即当前对话上下文中出现的 message_id 和 image_key/file_key,应使用本工具下载。 引用消息的 message_id 可从上下文中的 [message_id=om_xxx] 提取,无需向用户询问。

文件自动保存到 /tmp/openclaw/ 下,返回值中的 saved_path 为实际保存路径。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
message_idYes消息 ID(om_xxx 格式),引用消息可从上下文中的 [message_id=om_xxx] 提取
file_keyYes资源 Key,图片消息的 image_key(img_xxx)或文件消息的 file_key(file_xxx)
typeYes资源类型:image(图片消息中的图片)、file(文件/音频/视频消息中的文件)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the tool downloads resources to a specific local directory (/tmp/openclaw/), returns a saved_path in the response, and handles both images and files. However, it doesn't mention potential errors, rate limits, or authentication requirements, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized, with clear sections for purpose, usage scenarios, and behavioral details. Every sentence adds value, though it could be slightly more concise by integrating some details more tightly without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 required parameters, no output schema, no annotations), the description does a good job covering purpose, usage, and key behaviors like file saving and return values. However, it lacks details on error handling, file size limits, or format specifics, which could be important for a download tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds minimal value beyond the schema by reinforcing the context for message_id extraction and mentioning image_key/file_key, but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('download') and resources ('image or file resources from Feishu IM messages to local'), and distinguishes it from sibling tools by specifying its unique role in handling bot-received messages with message_id and image_key/file_key from the current conversation context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage scenarios ('user messages to bot, referenced messages, group chat messages to bot'), specifies when to use it ('current conversation context with message_id and image_key/file_key'), and gives practical guidance on extracting message_id from context without asking the user, making it highly actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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