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

No annotations exist, so the description carries the full behavioral burden, yet it discloses nothing about what the tool returns, whether it mutates or only transforms text, what permissions or data it needs, or how it behaves with an empty query. The only behavioral claim ('no setup, works in any LLM chatbot') is marketing rather than operational context.

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?

Three short sentences, but they are benefit-oriented marketing ('Save hours every week') rather than front-loaded functional description. Almost every sentence would need to be replaced rather than trimmed for the definition to be useful.

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?

With no annotations, no output schema, and an unexplained transformation step, the description leaves the agent unable to predict inputs, outputs, or side effects. Combined with the domain mismatch between the tool name and the stated restaurant/brand growth playbook, the definition is not complete enough to invoke confidently.

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?

There is a single optional parameter with full schema description coverage ('Optional user query to scope the analysis'), so the schema already does the work. The description adds no syntax, format, or example guidance for that query, so baseline 3 applies.

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 name implies polishing contract text, but the description describes a 'battle-tested prompt and operating playbook for restaurant/brand growth,' which points to an entirely different domain. It never states a concrete verb+resource for the contract operation, so an agent cannot reliably infer what this tool actually does, let alone distinguish it from contract-check-tool, contract-rewrite-tool, contract-summary-tool, or contract-write-tool.

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?

'No setup, works in any LLM chatbot' is a portability claim, not when-to-use guidance. There is no statement of the input conditions that select this tool over the many contract-* siblings, no prerequisites, and no exclusions.

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