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tool-function-schema-designer

tool-function-schema-designer

github.com/patricio0312revAgent workflows63246 installsUpdated 41w ago
Repository

About tool-function-schema-designer

A design guide for developers building tools that LLMs can invoke. It covers schemas, TypeScript types, validation, registries, and error handling.

Key features

  1. 01Design function-calling JSON schemas
  2. 02Define TypeScript interfaces
  3. 03Validate inputs with Zod
  4. 04Organize a tool registry
  5. 05Plan errors and example calls

Use cases

  1. 01Define parameters for documentation search
  2. 02Validate tool inputs from an LLM
  3. 03Link implementations with tool schemas

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/patricio0312rev/skills --skill tool-function-schema-designer

After installing, type/tool-function-schema-designerin Claude Code to confirm it loaded.

Details

From the project README

Tool/Function Schema Designer

Design robust tool schemas that LLMs can reliably invoke.

Function Schema Format

// OpenAI function calling format
const searchDocsTool = {
  type: "function",
  function: {
    name: "search_documentation",
    description:
      "Search through product documentation using semantic search. Use this when the user asks about features, how-tos, or troubleshooting.",
    parameters: {
      type: "object",
      properties: {
        query: {
          type: "string",
          description: "The search query, phrased as a question or keywords",
        },
        filters: {
          type: "object",
          properties: {
            category: {
              type: "string",
              enum: ["api", "guides", "tutorials", "troubleshooting"],
              description: "Filter by documentation category",
            },
            version: {
              type: "string",
              description: "Filter by product version (e.g., 'v2.0')",
            },
          },
        },
        max_results: {
          type: "integer",
          minimum: 1,
          maximum: 10,
          default: 5,
          description: "Maximum number of results to return",
        },
      },
      required: ["query"],
    },
  },
};

Typed Interfaces

// TypeScript types matching schema
interface SearchDocsParams {
  query: string;
  filters?: {
    category?: "api" | "guides" | "tutorials" | "troubleshooting";
    version?: string;
  };
  max_results?: number;
}

// Implementation
async function search_documentation(
  params: SearchDocsParams
): Promise<SearchResult[]> {
  const { query, filters = {}, max_results = 5 } = params;

  // Implementation
  return await vectorStore.search(query, {
    filter: filters,
    limit: max_results,
  });
}

Validation Strategy

import { z } from "zod";

// Zod schema for runtime validation
const searchDocsSchema = z.object({
  query: z.string().min(1, "Query cannot be empty"),
  filters: z
    .object({
      category: z
        .enum(["api", "guides", "tutorials", "troubleshooting"])
        .optional(),
      version: z.string().optional(),
    })
    .optional(),
  max_results: z.number().int().min(1).max(10).default(5),
});

// Validate before execution
function validateAndExecute(toolName: string, params: unknown) {
  const validated = searchDocsSchema.parse(params);
  return search_documentation(validated);
}

Tool Registry

export const TOOLS = {
  search_documentation: {
    schema: searchDocsTool,
    implementation: search_documentation,
    validator: searchDocsSchema,
  },
  create_ticket: {
    schema: createTicketTool,
    implementation: create_ticket,
    validator: createTicketSchema,
  },
  // ... more tools
};

// Execute tool safely
async function executeTool(name: string, params: unknown) {
  const tool = TOOLS[name];
  if (!tool) throw new Error(`Unknown tool: ${name}`);

  const validated = tool.validator.parse(params);
  return tool.implementation(validated);
}

Example Calls

// Example 1: Simple search
{
  "name": "search_documentation",
  "parameters": {
    "query": "How do I authenticate API requests?"
  }
}

// Example 2: With filters
{
  "name": "search_documentation",
  "parameters": {
    "query": "rate limiting",
    "filters": {
      "category": "api",
      "version": "v2.0"
    },
    "max_results": 3
  }
}

Error Handling

interface ToolResult {
  success: boolean;
  data?: any;
  error?: {
    code: string;
    message: string;
  };
}

async function safeExecuteTool(
  name: string,
  params: unknown
): Promise<ToolResult> {
  try {
    const data = await executeTool(name, params);
    return { success: true, data };
  } catch (error) {
    if (error instanceof z.ZodError) {
      return {
        success: false,
        error: {
          code: "VALIDATION_ERROR",
          message: `Invalid parameters: ${error.message}`,
        },
      };
    }
    return {
      success: false,
      error: {
        code: "EXECUTION_ERROR",
        message: error.message,
      },
    };
  }
}

Best Practices

  1. Clear descriptions: Explain when to use the tool
  2. Specific types: Use enums, ranges, patterns
  3. Sensible defaults: Reduce required parameters
  4. Validate rigorously: Don't trust LLM output
  5. Error messages: Help LLM correct mistakes
  6. Example calls: Show success cases
  7. Type safety: TypeScript interfaces

Output Checklist

  • JSON schema defined
  • TypeScript interface
  • Validation with Zod
  • Implementation function
  • Error handling
  • Example calls (3+)
  • Tool registry entry
  • Documentation

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