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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds valuable behavioral detail beyond annotations: fuzzy matching tolerates word reordering and minor spelling differences, returns ranked results, and includes EIN, location, and IRC subsection. This gives the agent a clear model of what the tool does without contradicting the 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 compact and front-loaded: the core purpose appears in the first sentence, followed by matching behavior, return contents, and downstream tool guidance. Every sentence earns its place with no redundancy or filler.

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 read-only search tool with three fully schema-documented parameters and no output schema, the description provides sufficient completeness. It explains matching behavior, result contents, ranking, and how to proceed with the returned EIN, so an agent can invoke it correctly and understand the result.

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 input schema already provides full parameter descriptions for name, limit, and state (100% coverage). The description adds only minimal semantic context beyond the schema, such as the fuzzy-search nature and optional state filtering, so the baseline score of 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 description states a specific verb ('Fuzzy-search') and resource ('tax-exempt organizations by name'), and distinguishes this tool from sibling tools like nonprofit_lookup_ein and nonprofit_search_location by anchoring it to name-based fuzzy matching. It also mentions optional state filtering, making the tool's purpose immediately clear.

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 clearly conveys when to use this tool: when searching by organization name, especially with uncertainty about exact spelling or word order, and optionally narrowing by state. It also tells the agent to use the returned EIN with nonprofit_details or nonprofit_lookup_ein, but it does not explicitly state when not to use this tool in favor of those exact-lookup tools.

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