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

Goes well beyond annotations by disclosing the exact cost ($0.005/call), the currency and chain (USDC on Solana), the x402 payment handshake, and an HTTP equivalent endpoint. This explains why readOnlyHint=false despite it being a data read — the call spends money. It stops short of describing the return payload (units, date range, series frequency), which with no output schema would be useful.

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?

Front-loads the dataset and then the payment cost, followed by the invocation recipe — a sensible order. It is dense but nearly every clause (cost, x402 flow, HTTP fallback) earns its place; the raw URL is the only slightly expendable element.

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-param tool with no output schema and openWorldHint=true, the description covers what the data is and exactly how to complete a paid call, which is the hard part. The remaining gap is the shape of the result (series values, units, dates), which an agent must discover at runtime.

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?

Zero parameters, so there is nothing to disambiguate and the baseline of 4 applies. The description correctly implies a parameterless GET-style data fetch.

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?

States a specific resource (federal funds rate) and source (FRED, public domain), so an agent knows exactly what data comes back. It does not explicitly distinguish itself from sibling macro tools like macro_cpi or macro_unemployment, relying on the name for that differentiation.

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 thoroughly explains HOW to invoke the paid flow (challenge → retry with _meta["x402/payment"]), but gives no guidance on WHEN to prefer this over sibling macro_* series or alternatives. Usage is only implied by the dataset name.

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