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 safety profile is covered. The description adds behavioral context beyond annotations: it explains that the tool returns reference data and templates, and that it should be called before mutations to get valid field values. It doesn't describe the return format, but with no output schema and a read-only reference tool, the description covers the key behavioral traits.

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 a single paragraph but well-structured: it lists the data categories first, then gives concrete usage scenarios. It's slightly dense but every sentence earns its place. The front-loading of the data list is effective, and the usage guidance is specific.

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 0-parameter read-only reference tool, the description is quite complete. It explains what data is available, when to call it, and how to use the data (match templates by name, label money with currency). The only gap is that it doesn't describe the exact return structure, but with no output schema and a reference-data tool, this is a minor omission.

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?

The tool has 0 parameters, so the schema is trivially complete (100% coverage). The description adds meaning by explaining what the returned data contains (statuses, lead sources, templates, etc.) and how to use it (match template names, get currency). With 0 params, the baseline is 4, and the description earns it by clarifying the data's purpose.

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: it provides account-specific reference data (statuses, lead sources, call results, pipelines, users, tags, reason lost options, custom fields, currency, and saved templates). It uses a specific verb ('Call before creating or updating records') and distinguishes itself from siblings by being the reference-data tool, not a create/update/query 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?

The description explicitly states when to use this tool: before creating or updating records, before quoting money values, and whenever the user names a template. It also implies when not to use it (for actual create/update/query operations, which are siblings). This is strong usage guidance.

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