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

With no annotations provided, the description carries the full burden for behavioral disclosure. It states what is returned and what is deliberately omitted, which is useful. Yet it offers no details on data recency, source, error behavior, or other operational traits, leaving some behavioral aspects undisclosed.

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 extremely concise, using two short sentences (plus a positioning tag) that pack all key information. It is front-loaded with the core purpose and every clause adds value, making it highly efficient.

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 parameterless tool with no output schema, the description adequately covers the main purpose, return fields, and explicit non-goals. It leaves some ambiguity about field formats or interpretation, but overall it is sufficiently complete for an agent to understand and 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?

The tool has zero parameters, so the baseline is 4 per the rubric. The description doesn't need to explain parameter semantics; instead it focuses on output semantics, listing the returned fields. This is appropriate and consistent.

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 returns Fed Funds Rate evidence with specific fields (signal_strength, risk_band, reason_codes, action categories). The phrase 'as evidence only' and 'Product positioning: evidence_infrastructure' distinguish it from advisory or recommendation tools, and the 'Returns' verbs signal its data-fetching role.

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 provides clear context that this is an evidence-only tool and explicitly lists what it does NOT do (no recommendations, no sizing, no venue picks), giving the agent usage boundaries. However, it does not name alternative tools for those other purposes, so it lacks explicit 'use this instead' guidance.

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