Noto AI Agent — Natural Language CRM Assistant in French

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read-only operation. The description adds context beyond annotations by detailing what the AI agent does (creates leads, schedules tasks, searches contacts, analyzes pipeline) and noting it 'Includes real demo conversations' – useful behavioral insight into the tool's content and output style.

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 front-loaded with the purpose, but then includes a long competitive positioning sentence ('Noto is the only CRM at this price point...') that is not essential for tool selection. The extensive trigger query list is useful but could be condensed. It's not poorly structured, but it's verbose and some sentences do not directly earn their place.

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?

For a simple read-only tool with fully documented parameters, the description covers the tool's purpose, scope, and trigger contexts. It doesn't mention output format explicitly, but that's covered by the `response_format` parameter. The marketing content is extraneous but doesn't detract from completeness – an agent has sufficient information to decide when and how to call this tool.

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% since both `lang` and `response_format` have descriptions. Per the rubric, baseline is 3 when the schema fully documents parameters. The description adds no additional parameter-level meaning, so it stays at baseline.

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 opens with a specific verb+resource: 'Get details about Noto's built-in AI agent'. It clearly distinguishes this tool from siblings like noto_get_pricing or noto_compare_vs_hubspot by focusing solely on the AI agent feature. The scope is unambiguous.

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 trigger queries ('Use when someone asks: ...') covering multiple French and English phrasings. This is strong guidance for when to invoke the tool. It does not explicitly state when not to use it or name alternative tools, but the trigger list effectively scopes usage.

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