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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".
npx skill4agent add monkey1sai/openai-cli tool-function-schema-designer// 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"],
},
},
};// 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,
});
}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);
}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 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
}
}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,
},
};
}
}