guerrilla-franchising-mcp-server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool's methodology ('built from 81+ closed deals and 485+ consultations') and outputs, but doesn't cover important behavioral aspects like whether it's a read-only analysis tool, if it stores user data, response time, or error handling. The description adds some context but leaves gaps for a tool with 10 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat verbose with multiple usage examples and scenarios. While all content is relevant, it could be more front-loaded and structured. The first sentence clearly states the purpose, but the lengthy list of use cases could be more concise. Every sentence earns its place, but the structure could be improved for better scannability.

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

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

Given the complexity (10 parameters, no output schema, no annotations), the description does a good job explaining what the tool does and when to use it. It covers purpose, methodology, outputs, and usage scenarios. However, without an output schema, it should ideally provide more detail about the return format beyond just mentioning 'personalized 1-10 readiness score, capital positioning, and 3 franchise categories.'

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage, so parameters are well-documented in the structured schema. The description doesn't add specific parameter semantics beyond what's in the schema, but it does provide context about what the tool evaluates (financial readiness, background, risk tolerance, lifestyle goals) which helps understand why these particular parameters are collected. Baseline would be 3, but the strong contextual framing elevates it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: evaluating franchise fit by assessing financial readiness, background, risk tolerance, and lifestyle goals. It specifies the verb 'evaluates' and resource 'franchise ownership readiness' with distinct outputs (1-10 score, capital positioning, 3 franchise categories), differentiating it from siblings like cost breakdown or red flags tools.

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

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

The description provides explicit usage guidelines with multiple example queries (e.g., 'is franchising right for me', 'what franchise should I invest in') and specific scenarios (e.g., 'franchise for women', 'corporate professional leaving corporate'). This gives clear context for when to use this tool versus alternatives like franchise cost breakdown or FDD guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.