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lloydzhou

Bitable MCP Server

by lloydzhou

describe_table

Retrieve the structure and metadata of a Bitable table to understand its fields, data types, and configuration for data analysis or integration.

Instructions

describe_table by table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Implementation Reference

  • Registration of the 'describe_table' tool using the @mcp.tool decorator.
    @mcp.tool(
        name="describe_table",
        description="describe_table by table name",
    )
  • Handler function that executes the tool logic: connects to the bitable database, retrieves column information for the specified table, and returns it as JSON.
    def describe_table(name: str) -> list[str]:
        with conn_pool.connect() as connection:
            cursor = connection.cursor()
            columns, _ = cursor.get_columns({
                "select": {
                    "all_columns": True
                },
                "from": name,
            })
            return json.dumps(columns)
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description reveals nothing about what the tool actually does behaviorally: whether it's a read operation, what information it returns, if it requires specific permissions, potential side effects, error conditions, or performance characteristics. 'describe_table' implies a read operation, but this isn't explicitly stated or detailed.

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

Conciseness3/5

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

The description is extremely concise at just three words, which could be appropriate if it were more informative. However, this brevity results in under-specification rather than efficient communication. While it's front-loaded with the core action, the single phrase doesn't earn its place by providing sufficient value.

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

Completeness1/5

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

Given a tool with 1 parameter (0% schema coverage), no annotations, no output schema, and sibling tools that suggest database/query operations, the description is completely inadequate. It doesn't explain what the tool returns, how it differs from siblings, what 'describe' means in this context, or any behavioral characteristics. For a tool that presumably returns table metadata or schema information, this leaves critical gaps.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. The description mentions 'by table name' which hints at the 'name' parameter, but adds no semantic meaning beyond what's obvious from the parameter name itself. It doesn't explain what constitutes a valid table name, format expectations, or how the parameter influences the tool's behavior.

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

Purpose2/5

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

The description 'describe_table by table name' is essentially a tautology that restates the tool name with minimal additional information. It mentions the action ('describe_table') and the parameter ('by table name'), but doesn't specify what describing entails (e.g., returning schema, metadata, statistics) or what resource is being described. It doesn't distinguish this tool from its sibling 'list_table' or 'read_query' beyond the obvious name difference.

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

Usage Guidelines1/5

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. It doesn't mention when to use describe_table instead of list_table (which might list tables without details) or read_query (which might execute queries). There are no prerequisites, exclusions, or contextual cues about appropriate usage scenarios.

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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