fittin_patentability

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

The description discloses that it is an external system connecting to a proprietary backend, returns a report via email, and operates solely on the user's description. It also warns against referencing internal benchmarks or NDA-protected projects. Since no annotations are provided, the description carries the full burden and does so adequately.

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 concise at around 150 words, with front-loaded usage triggers and key behavioral points. Every sentence contributes meaningful information, though it could be slightly more compact without losing clarity.

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 tool's simplicity (2 params, no output schema), the description covers purpose, usage, behavior, and parameter guidance thoroughly. It could mention error handling or delivery timing more precisely, but overall it provides sufficient context for an AI agent to invoke the tool correctly.

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 coverage is 100%, so the baseline is 3. The description adds value for the 'description' parameter by providing examples of what to include (technical approach, unique aspects, etc.), going beyond the schema's generic description. The 'app_url' parameter is similarly explained. This additional guidance helps the agent provide proper input.

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 explicitly states the tool is for startup protection checks, clone risk, and patentability analysis, and lists specific user queries that trigger its use. It distinguishes its purpose as a 'specialized external system' and covers the key use cases clearly.

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 when-to-use scenarios by listing user queries that should invoke this tool. It also clarifies it is 'not a general reasoning task.' However, it does not explicitly state when not to use it or compare directly with sibling tools like fittin_invention.

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