rates

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

No annotations are provided, so the description carries the full behavioral burden. It names the data source (FRED) but says nothing about whether it is a read, rate limits, auth requirements, caching, or the shape of the response.

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 core sentence is duplicated verbatim (repeated after a dash separator), which is pure waste and makes the description look malformed. The one useful piece, the example endpoint, is buried at the end.

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?

With no output schema and no annotations, the description should carry more load. It conveys the data domain and source but omits return format, defaults when 'series' is omitted, and the safety/read profile, leaving real gaps for a data-fetch tool.

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 coverage is 100%, so the single 'series' parameter is already fully documented in the schema. The description adds only the data domain (1M–30Y curve, spread series) but no extra semantics about how 'series' interacts with it, so baseline 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?

States a specific resource (US Treasury yield curve 1M–30Y plus recession-indicator spreads 10y-2y/10y-3m) and its source (FRED). An agent can tell what data this returns, though it offers no explicit differentiation from sibling data tools like macro_calendar or market_overview.

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?

There is no when-to-use guidance, no mention of alternatives among the many sibling tools, and no exclusions or prerequisites. The agent is left to infer that this is the yield-curve lookup versus e.g. macro_calendar.

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