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Get Tool Information

tool_info

Retrieve complete information about a specific tool, including all details about its input schema and purpose.

Instructions

Get complete information about a specific tool including all details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tool_nameYesName of the tool to get complete information for.

Implementation Reference

  • TypeScript implementation of the 'tool_info' tool handler. Fetches tool details from the UTCP client's tool repository by name and returns them as JSON.
    mcp.registerTool("tool_info", {
        title: "Get Tool Information",
        description: "Get complete information about a specific tool including all details.",
        inputSchema: {
            tool_name: z.string().describe("Name of the tool to get complete information for."),
        },
    }, async (input) => {
        const client = await initializeUtcpClient();
        try {
            const tool = await client.config.tool_repository.getTool(input.tool_name);
            if (!tool) {
                return { content: [{ type: "text", text: JSON.stringify({ success: false, error: `Tool '${input.tool_name}' not found` }) }] };
            }
            return { content: [{ type: "text", text: JSON.stringify({ success: true, tool: tool }) }] };
        } catch (e: any) {
            return { content: [{ type: "text", text: JSON.stringify({ success: false, error: e.message }) }] };
        }
    });
  • index.ts:178-195 (registration)
    Registration of the 'tool_info' tool on the MCP server via mcp.registerTool().
    mcp.registerTool("tool_info", {
        title: "Get Tool Information",
        description: "Get complete information about a specific tool including all details.",
        inputSchema: {
            tool_name: z.string().describe("Name of the tool to get complete information for."),
        },
    }, async (input) => {
        const client = await initializeUtcpClient();
        try {
            const tool = await client.config.tool_repository.getTool(input.tool_name);
            if (!tool) {
                return { content: [{ type: "text", text: JSON.stringify({ success: false, error: `Tool '${input.tool_name}' not found` }) }] };
            }
            return { content: [{ type: "text", text: JSON.stringify({ success: true, tool: tool }) }] };
        } catch (e: any) {
            return { content: [{ type: "text", text: JSON.stringify({ success: false, error: e.message }) }] };
        }
    });
  • Input schema for 'tool_info' - requires a 'tool_name' string parameter validated with Zod.
    inputSchema: {
        tool_name: z.string().describe("Name of the tool to get complete information for."),
    },
  • Python implementation of the 'tool_info' tool handler using FastMCP decorator. Fetches tool details using model_dump().
    @mcp.tool()
    async def tool_info(tool_name: str) -> Dict[str, Any]:
        """Get complete information about a specific tool including all details using model_dump().
        
        Args:
            tool_name: Name of the tool to get complete information for
            
        Returns:
            Dictionary with success status and complete tool information with model_dump()
        """
        client = await initialize_utcp_client()
        
        try:
            # Search for the specific tool
            tool = await client.config.tool_repository.get_tool(tool_name)
            
            if not tool:
                return {
                    "success": False,
                    "error": f"Tool '{tool_name}' not found"
                }
            
            # Return complete tool information with model_dump()
            return {
                "success": True,
                "tool": tool.model_dump()
            }
        except Exception as e:
            return {
                "success": False,
                "error": str(e)
            }
  • Registration of the 'tool_info' tool via the @mcp.tool() decorator in the Python bridge.
    @mcp.tool()
    async def tool_info(tool_name: str) -> Dict[str, Any]:
Behavior2/5

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

Annotations lacking; description does not reveal behavioral traits such as whether tool info is cached, operation speed, or authentication requirements. 'Complete information' is ambiguous, leaving the agent uncertain about return structure.

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?

Single sentence is concise but lacks specificity; could be improved by front-loading key qualifiers.

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?

Without output schema, the description should clarify that the response contains fields like name, description, parameters, etc., but it does not. Tool complexity is low, but description under-specifies return value.

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 sole parameter 'tool_name' is already fully described in the schema (100% coverage). The description adds no additional semantic insight beyond the schema.

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 action (Get) and the target (tool information), and specifies granularity (complete info for a specific tool), distinguishing it from list_tools and search_tools.

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?

No guidance on when to use this tool versus its siblings; missing use-case context like 'use this when you need all details of a single tool'.

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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