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 operation. The description adds value beyond annotations by noting the search counts toward monthly searches (a usage limit) and that the dataset is QA-gated (a quality/access constraint). It does not explain return format or error handling, but given the strong annotation coverage, this is adequate.

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 sentences with no fluff. The scoping statement ('full legal name or EIN') is front-loaded, followed by what is withheld, and then a usage note. Every sentence earns its place, and the description is short enough an agent can parse quickly.

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?

The tool is simple with 4 parameters, all documented in schema, and an output schema is absent (so no need to describe return format). The description covers the main constraints: exact-name/EIN search, QA-gated data, withheld capabilities, and monthly counting. The only minor gap is the lack of detail on default behavior or edge cases, but for this complexity it's nearly complete.

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%, so the schema already documents all parameters. The description adds a note about query examples and reiterates that mission queries are not available, which reinforces a caution but doesn't add fundamentally new semantics beyond the schema. Baseline 3 is appropriate because the schema does the heavy lifting.

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 looks up private foundations by full legal name or EIN, and specifies the exact dataset (QA-gated release with 3,678 profiles). It distinguishes itself from siblings like funders_for_cause or find_funders_of by explicitly noting that mission/topic discovery and grant-purpose search are withheld, which is crucial given the sibling list includes search_grantsplus and search_procurement.

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 makes it explicit when to use this tool: for full legal name or EIN lookups in the active release. It clearly states what is not available (mission/topic search) and that counts toward monthly searches, which is important for an agent to decide between this and alternatives. It also implicitly warns that mission queries will fail, so an agent should not attempt them.

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