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. It effectively discloses behavioral traits: it validates investment ranges by cross-referencing against hidden costs, category-specific overruns, and Item-level discrepancies, based on data from '81+ closed deals.' This gives context on methodology and data sources, though it doesn't detail output format or error handling.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by context on its origin and methodology. Every sentence adds value—explaining the tool's background and how it works—without redundancy or fluff.

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 (6 required parameters, no output schema, no annotations), the description is fairly complete. It explains what the tool does, its methodology, and data basis, which helps an agent understand its use. However, without an output schema, it doesn't describe return values or validation outcomes, leaving a minor gap.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no specific parameter semantics beyond implying that inputs like 'franchise_category' and 'location_type' are used for cross-referencing in validation. This meets the baseline of 3 when schema coverage is high.

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: 'Validates the true total investment in a franchise opportunity.' It specifies the verb ('validates') and resource ('true total investment'), and distinguishes it from siblings by mentioning its unique focus on FDD investment range validation against hidden costs, unlike broader tools like gf_franchise_cost_breakdown or gf_franchise_red_flags.

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 implies usage context through its mention of 'FDD investment range' and 'franchise opportunity,' suggesting it's for evaluating franchise investments. However, it lacks explicit guidance on when to use this tool versus alternatives like gf_franchise_cost_breakdown or gf_franchise_red_flags, which might cover similar ground. No exclusions or prerequisites are stated.

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