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

The annotations already mark this as read-only and idempotent, and the description adds significant behavioral context: sources degrade gracefully, federal dollars are name-matched and should be verified, and Grants.gov opportunities are clearly labeled as NOT awards. These are exactly the caveats an agent needs to interpret results correctly.

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 dense but not bloated, and it front-loads the core purpose with 'One-call federal-money + nonprofit profile.' Each clause adds useful information, though the phrase 'premium cross-source synthesis' is a bit promotional and not strictly necessary.

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 multi-source aggregate tool with no output schema, the description covers the main content areas, lookup paths, optional behavior, and important caveats. It does not specify the exact response structure, but the logged data elements and degradation note provide enough contextual grounding for an agent to call it 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?

The input schema already describes all four parameters, including the optional EIN exact-match behavior, state disambiguation, and the include_opportunities default. The description mostly reinforces these details rather than adding new parameter-level meaning, so the baseline of 3 is appropriate.

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 produces a combined profile of federal money and nonprofit data for an organization, naming the specific sources and data elements. It is distinct from narrower siblings like spending_recipient_summary or nonprofit_details, though it does not explicitly name them.

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: use this when you want federal funding and nonprofit 990 data in one call, and optionally include Grants.gov opportunities. It also usefully clarifies that opportunities are available funding, not awarded funds. However, it does not explicitly state when to prefer a more specialized sibling tool.

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