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sam2332

SQLite MCP Server

by sam2332

describe_table

Retrieve the schema and structure of a specific SQLite database table to understand its columns, data types, and constraints.

Instructions

Get the schema/structure of a specific table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesName of the table to describe

Implementation Reference

  • Executes the describe_table tool: checks database connection, runs PRAGMA table_info(?), formats columns with types, nullability, PK, defaults, and returns formatted schema text.
    private async describeTable(args: { table_name: string }): Promise<CallToolResult> {
      if (!this.db) {
        throw new Error("No database connected. Use connect_database first.");
      }
    
      try {
        const columns = this.db
          .prepare("PRAGMA table_info(?)")
          .all(args.table_name) as {
            cid: number;
            name: string;
            type: string;
            notnull: number;
            dflt_value: any;
            pk: number;
          }[];
    
        if (columns.length === 0) {
          throw new Error(`Table '${args.table_name}' not found`);
        }
    
        const schema = columns
          .map(col => {
            const nullable = col.notnull === 0 ? "NULL" : "NOT NULL";
            const pk = col.pk > 0 ? " PRIMARY KEY" : "";
            const defaultVal = col.dflt_value !== null ? ` DEFAULT ${col.dflt_value}` : "";
            return `  ${col.name} ${col.type} ${nullable}${pk}${defaultVal}`;
          })
          .join("\n");
    
        return {
          content: [
            {
              type: "text",
              text: `Table: ${args.table_name}\n\nSchema:\n${schema}`,
            } satisfies TextContent,
          ],
        };
      } catch (error) {
        throw new Error(`Failed to describe table: ${error instanceof Error ? error.message : String(error)}`);
      }
    }
  • src/index.ts:86-99 (registration)
    Registers the describe_table tool in the ListTools response, including name, description, and input schema.
    {
      name: "describe_table",
      description: "Get the schema/structure of a specific table",
      inputSchema: {
        type: "object",
        properties: {
          table_name: {
            type: "string",
            description: "Name of the table to describe",
          },
        },
        required: ["table_name"],
      },
    },
  • Defines the input schema for describe_table: object with required 'table_name' string property.
    inputSchema: {
      type: "object",
      properties: {
        table_name: {
          type: "string",
          description: "Name of the table to describe",
        },
      },
      required: ["table_name"],
    },
  • Dispatches call_tool requests for describe_table to the describeTable method.
    case "describe_table":
      return await this.describeTable(args as { table_name: string });
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 states the tool retrieves schema information but doesn't mention whether this is a read-only operation, if it requires specific permissions, what format the output is in, or any error conditions. This leaves significant gaps for a tool that interacts with database structures.

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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It is front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse quickly.

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's low complexity (one parameter) and lack of annotations or output schema, the description is minimally adequate but incomplete. It covers the basic purpose but misses behavioral details like output format or error handling, which are important for a schema retrieval tool in a database context.

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 input schema has 100% description coverage, with the 'table_name' parameter clearly documented. The description adds no additional meaning beyond what the schema provides, such as examples or constraints on table names. This meets the baseline for high schema coverage but doesn't enhance parameter understanding.

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 tool's purpose with a specific verb ('Get') and resource ('schema/structure of a specific table'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_table_info' or 'list_tables', which might have overlapping functionality, preventing a perfect score.

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 such as 'get_table_info' or 'list_tables'. It lacks context about prerequisites (e.g., needing a database connection) or exclusions, leaving the agent to infer usage from the purpose alone.

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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