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maasy_generate_content

Generate social media content aligned with your brand identity. Supply a creation prompt and optionally specify platform. Content respects brand DNA, tone, and ideal customer profile.

Instructions

Generate on-brand social content using maasy AI. Respects brand DNA, tone, ICP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoBrand UUID
promptYesWhat to generate (e.g. '3 Instagram posts about our product launch')
platformNogeneral

Implementation Reference

  • src/index.ts:248-260 (registration)
    Registers the 'maasy_generate_content' tool with the MCP server, defining its input schema (project_id, prompt, platform) and delegating execution to toolHandler('generate_content').
    server.tool(
      "maasy_generate_content",
      "Generate on-brand social content using maasy AI. Respects brand DNA, tone, ICP.",
      {
        project_id: z.string().optional().describe("Brand UUID"),
        prompt: z.string().describe("What to generate (e.g. '3 Instagram posts about our product launch')"),
        platform: z
          .enum(["instagram", "facebook", "linkedin", "twitter", "tiktok", "general"])
          .optional()
          .default("general"),
      },
      toolHandler("generate_content")
    );
  • Zod schema for maasy_generate_content: optional project_id, required prompt string, optional platform enum (instagram, facebook, linkedin, twitter, tiktok, general) defaulting to 'general'.
    {
      project_id: z.string().optional().describe("Brand UUID"),
      prompt: z.string().describe("What to generate (e.g. '3 Instagram posts about our product launch')"),
      platform: z
        .enum(["instagram", "facebook", "linkedin", "twitter", "tiktok", "general"])
        .optional()
        .default("general"),
    },
  • Generic toolHandler wrapper that calls callGateway(toolName, args) to invoke the 'generate_content' tool via the Supabase edge function gateway, returning the result as text content.
    function toolHandler(toolName: string, argsFn?: (args: Record<string, unknown>) => Record<string, unknown>) {
      return async (args: Record<string, unknown>) => {
        try {
          const gatewayArgs = argsFn ? argsFn(args) : args;
          // Auto-inject default project_id if not provided
          if (DEFAULT_PROJECT_ID && !gatewayArgs.project_id) {
            gatewayArgs.project_id = DEFAULT_PROJECT_ID;
          }
          const result = await callGateway(toolName, gatewayArgs);
          return { content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }] };
        } catch (e: unknown) {
          return {
            content: [{ type: "text" as const, text: `Error: ${e instanceof Error ? e.message : String(e)}` }],
            isError: true,
          };
        }
      };
    }
  • The callGateway function that sends the tool name ('generate_content') and args to the mcp-gateway Supabase edge function, handling auth and response parsing.
    export async function callGateway(tool: string, args: Record<string, unknown> = {}): Promise<unknown> {
      const res = await fetch(gatewayUrl, {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
          [authHeader.name]: authHeader.value,
        },
        body: JSON.stringify({ tool, args }),
      });
    
      const data = await res.json();
    
      if (!res.ok) {
        throw new Error(data.error || `Gateway error (${res.status})`);
      }
    
      return data.result;
    }
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It states the tool respects brand DNA, tone, and ICP, but does not disclose error handling, authorization needs, rate limits, or side effects. The description is moderately transparent but lacks depth about consequences.

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 extremely concise with two sentences: one for the primary action and one for key constraints. No unnecessary words, front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (3 parameters, no output schema), the description adequately covers purpose and constraints. It could mention output format or typical response, but not required. Overall complete for a straightforward generation tool.

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 67% description coverage, and the description adds little beyond what is already in the schema. It does not elaborate on parameter formats or usage, but the schema itself is clear. Baseline 3 is appropriate.

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 tool generates on-brand social content using maasy AI, with specific verbs ('generate') and resource ('social content'). It respects brand DNA, tone, and ICP, which distinguishes it from siblings like maasy_generate_ads (ads) and maasy_create_landing (landing pages).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for social content generation but provides no explicit guidance on when to use this tool versus alternatives (e.g., maasy_generate_ads) or when not to use it. No prerequisites or exclusions are mentioned.

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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