get_rates_and_curveUS Treasury yields, the 2s10s and other spreads, and the curve regime (bull or bear, steepener or flattener) with the time it flipped. Prices are live on Pro and Ultimate, one hour behind on Starter, and answer with upgrade steps on the free tiers.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 useful non-obvious behavioral details: prices are live on Pro/Ultimate, delayed on Starter, and free tiers receive upgrade steps instead of the full answer.
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?
Two compact, front-loaded sentences cover both data content and access-tier behavior without redundancy or boilerplate. Every phrase adds practical information.
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 read-only tool, this description is largely complete: it names the data, the included spreads, the regime regime, and the pricing tiers. The main omission is the exact return shape, but no output schema exists and the content is reasonably covered.
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 description carries no parameter burden. It does, however, set expectations about the data returned, including yields, spreads, and curve-regime timing.
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 identifies the resource: US Treasury yields, spreads like 2s10s, and the curve regime with the time it flipped. This makes the tool meaningful relative to many siblings, though it does not explicitly distinguish itself from the closely related get_treasury_curve.
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 no guidance about when to use this tool versus the many get_* siblings. There is no mention of alternatives or exclusion criteria, so an agent must infer selection from naming and content alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.