tool-function-schema-designer

v2026.09.24

Designs robust function/tool calling schemas for LLMs with JSON schemas, validation strategies, typed interfaces, and example calls. Use when implementing "function calling", "tool use", "LLM tools", or "agent actions".

GitHub
Install command
npx skhub add patricio0312rev/tool-function-schema-designer
Markdown
SKILL.md

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
Discovery
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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

MIT

Source path

ai-engineering/tool-function-schema-designer

Default branch

main

Latest commit

79ea6af

Tree SHA

d2efd68