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feishu_read_bitable

Retrieve records from Feishu multi-dimensional tables and convert them into Markdown-formatted tables for data analysis and reporting.

Instructions

读取飞书多维表格的记录。返回 Markdown 格式的表格。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_tokenYes多维表格 app_token 或完整 URL
table_idNo数据表 ID,不指定则使用默认表
page_sizeNo每页记录数,默认 20
Behavior2/5

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 mentions the return format ('Markdown 格式的表格' meaning 'Markdown format table') which is valuable context, but doesn't address important behavioral aspects like whether this is a read-only operation (implied but not stated), authentication requirements, rate limits, pagination behavior (though 'page_size' parameter hints at it), or error conditions. For a tool with zero annotation coverage, this leaves significant gaps.

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

Conciseness5/5

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

The description is extremely concise - a single sentence that efficiently communicates the core functionality and output format. Every word earns its place with no wasted text. It's appropriately sized for the tool's complexity and gets straight to the point.

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

Completeness3/5

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

Given the tool has 3 parameters with full schema coverage but no annotations and no output schema, the description provides the basic purpose and output format. However, for a data retrieval tool that presumably interacts with an external API, it should ideally mention authentication requirements, rate limits, or error handling. The return format information is helpful, but without an output schema, more detail about the structure of returned data would be beneficial.

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?

The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema (app_token, table_id, page_size with their descriptions). According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter info in the description, which applies here.

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

Purpose4/5

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

The description clearly states the action ('读取' meaning 'read') and resource ('飞书多维表格的记录' meaning 'Feishu multi-dimensional table records'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'feishu_read_document' or 'feishu_read_spreadsheet' which also read different Feishu resources, so it doesn't reach the highest level of sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools that read different Feishu resources (documents, spreadsheets), there's no indication of when this specific table-reading tool is appropriate versus other read operations. No context, exclusions, or alternatives are mentioned.

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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