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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the bar for additional behavioral disclosure is lower. The description still adds substantial context: beta/QA-gated status, Plus/Pro section requirements, responsible-use limits, exclusion of named-person grant recipients, and the private-foundation-only constraint. No contradiction with annotations.

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 long but every sentence carries distinct information: purpose, coverage, plan tiers, return semantics, exclusions, and quota behavior. It is well organized and front-loaded with the core purpose before diving into section-specific details.

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 complex 12-parameter, 5-section tool with no output schema, the description covers scope, access tiers, exclusions, and return semantics for key sections. It does not describe the overall response envelope or error behavior, but the detail provided is strong enough for an 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 because the schema already documents every parameter. The description adds genuine meaning beyond the schema by explaining what each section returns and the access tier required—particularly for section, leadership, and federal_connections—which helps an agent choose parameter values correctly.

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 and resource: 'Get the current profile for a PRIVATE foundation by EIN.' It further clarifies the tool's scope by naming exact sections (grant history, repeat grantees, leadership, federal connections) and exclusions, so an agent can distinguish this from broader foundation-search siblings.

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 gives clear context: this is for private foundations with known EINs, covers IRS tax years 2018–2026, and does not count toward monthly searches. It does not explicitly name an alternative tool for discovery or broad searching, so it stops short of full when-to-use versus when-not-to-use guidance.

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