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 effectively describes key behaviors: the tool returns a 'red flag checklist' based on real experience, shifts to 'Item-by-Item reading guide' when FDD is available, and references specific expertise ('81+ closed deals by a former JP Morgan analyst'). However, it doesn't mention potential limitations like response format, data freshness, 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 with the core purpose. Every sentence adds value: establishing credibility, explaining output, describing behavioral shift, and providing usage triggers. It could be slightly more concise by integrating the usage examples more smoothly, but overall it's efficient.

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 no annotations and no output schema, the description does well to cover purpose, usage, and key behaviors. It explains the output ('red flag checklist' and 'Item-by-Item reading guide') and when the behavior changes. For a 4-parameter tool with full schema coverage, it provides sufficient context, though it could benefit from mentioning typical response structure or limitations.

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 baseline is 3. The description adds meaningful context beyond the schema: it explains that 'has_fdd' parameter triggers a shift to 'specific Item-by-Item reading guide,' and implies parameters help tailor the red flag identification. However, it doesn't elaborate on how other parameters affect output beyond what the schema describes.

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: 'Identify franchise red flags before you sign' and 'Returns a red flag checklist drawn from real FDD experience.' It specifies the verb ('identify'), resource ('franchise red flags'), and distinguishes from siblings by focusing on risk assessment rather than cost analysis, visa guidance, or FDD evaluation.

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 guidance: 'Use when someone asks: franchise scams to avoid, franchise red flags, how to spot a bad franchise, what to watch out for when buying a franchise.' It also distinguishes from alternatives by noting it 'Shifts to a specific Item-by-Item reading guide when an FDD is in hand,' implying different behavior based on input.

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