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BRNDMK

brandomica-mcp-server

Full Brand Check

brandomica_check_all
Read-onlyIdempotent

Check brand name availability across domains, social handles, trademarks, and app stores with structured scoring and safety assessment.

Instructions

Check brand name availability across domains (with pricing), social handles, trademarks, app stores, and SaaS channels. Returns structured JSON with a 0-10 availability score and a 0-100 safety assessment. Use mode='quick' for faster results with fewer checks (domains without pricing, GitHub only, npm only, trademarks, no app stores or web presence).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_nameYesThe brand name to check
modeNoCheck mode: 'full' runs all checks with pricing, 'quick' runs essential checks only (~3-4 API calls)full

Implementation Reference

  • src/index.ts:327-346 (registration)
    The tool "brandomica_check_all" is registered in src/index.ts. It calls the "check-all" API endpoint.
    server.registerTool(
      "brandomica_check_all",
      {
        title: "Full Brand Check",
        description:
          "Check brand name availability across domains (with pricing), social handles, trademarks, app stores, and SaaS channels. Returns structured JSON with a 0-10 availability score and a 0-100 safety assessment. Use mode='quick' for faster results with fewer checks (domains without pricing, GitHub only, npm only, trademarks, no app stores or web presence).",
        inputSchema: z.object({
          ...brandNameInput,
          mode: z.enum(["full", "quick"]).default("full").describe("Check mode: 'full' runs all checks with pricing, 'quick' runs essential checks only (~3-4 API calls)"),
        }).strict(),
        annotations: toolAnnotations,
      },
      async ({ brand_name, mode }) => {
        const extra = mode && mode !== "full" ? { mode } : undefined;
        const data = (await fetchApi("check-all", brand_name, extra)) as CheckAllResponse;
        return {
          content: [{ type: "text" as const, text: JSON.stringify(data) }],
        };
      }
    );
Behavior4/5

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

The description adds valuable context beyond annotations: it explains the tool's output format ('structured JSON with a 0-10 availability score and a 0-100 safety assessment') and performance characteristics ('~3-4 API calls' for quick mode). Annotations already indicate it's read-only, non-destructive, idempotent, and open-world, so the description doesn't contradict them but provides additional behavioral details.

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 front-loaded with the core purpose, followed by output details and usage guidance. Both sentences are essential: the first defines the tool's scope and output, the second explains the mode parameter's practical implications. There is no wasted text, making it highly efficient.

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 complexity (multiple check types) and lack of output schema, the description does well by specifying the output format (structured JSON with scores). However, it could be more complete by detailing what the '0-10 availability score' and '0-100 safety assessment' mean or listing specific checks included. Annotations cover safety aspects, but the description adds useful context without being exhaustive.

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?

Schema description coverage is 100%, so the schema fully documents both parameters. The description adds some semantic context by explaining the 'mode' parameter's impact ('quick' for faster results with fewer checks), but doesn't provide additional meaning beyond what the schema already covers. This meets the baseline for high schema coverage.

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's purpose: 'Check brand name availability across domains (with pricing), social handles, trademarks, app stores, and SaaS channels.' It specifies the verb ('Check') and resources (domains, social handles, trademarks, etc.), and distinguishes it from siblings like 'brandomica_check_domains' or 'brandomica_check_social' by covering multiple aspects in one tool.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool vs. alternatives: 'Use mode='quick' for faster results with fewer checks (domains without pricing, GitHub only, npm only, trademarks, no app stores or web presence).' It specifies the trade-offs between 'full' and 'quick' modes, helping the agent choose based on speed vs. comprehensiveness.

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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