Get LMP prices

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds important context that this is 'settled/observed prices,' clarifying the data is historical/actual, not a forecast. It also implies a read-only operation. However, it does not mention potential rate limits, pagination, or response structure, but those are less critical for a simple data-retrieval tool. The key behavioral trait (observed vs. forecast) is disclosed.

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 compact and front-loaded: the first sentence states the core purpose, the second adds key parameter details and an alternative tool. Every sentence contributes actionable information with no filler. The structure is clear and easy to parse, earning a top score.

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 tool with 6 parameters, 1 required, and no output schema, the description covers the main use case, key parameter choices, and tool alternatives. It does not explicitly describe the return format, but given the tool's simplicity and the fact that no output schema exists, the description is sufficiently complete. A slight gap is the lack of guidance on date ranges or limits, but these are documented in the schema.

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% with detailed descriptions for all six parameters. The description adds no new semantic meaning beyond the schema: it repeats market values (RT/DA) and node_id optionality, which are already documented in the schema. Per the baseline rule, a score of 3 is appropriate when schema does the heavy lifting and description offers minimal additional parameter insight.

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 'Locational marginal prices (LMP) for a US ISO,' using a specific resource (LMP) and scope (US ISO). It distinguishes itself from sibling tools by explicitly noting it provides 'settled/observed prices' and directing to get_spread_forecast for forward forecasts, eliminating ambiguity.

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 explains the primary use (retrieving LMP) and key parameters (market=RT or DA, optional node_id). It provides an explicit alternative: 'for Kardashev's forward RT−DA spread forecast use get_spread_forecast instead,' which clearly tells the agent when to use a different tool. This is excellent usage guidance.

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