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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It mentions pricing, coverage, and that carbon-intensity returns 'live' data, but it does not disclose rate limits, authentication, error behavior, or whether the tool is read-only. The lack of any mention of side effects or external dependencies is a significant gap for an API aggregator.

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 organized with a bold header, a brief summary, and a bulleted list of endpoints with pricing. It is front-loaded with the main purpose and fairly concise given the number of endpoints. The redundant repetition of the action enum from the schema is a minor inefficiency, but overall it is well-structured and scannable.

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?

The tool has 22 parameters, no output schema, and no annotations, so the description must provide substantial context. It covers high-level capabilities and pricing but fails to explain return formats, units, or how to combine parameters with actions. The endpoint descriptions are terse ('Electricity prices by state') without details on response structure or data granularity, leaving the agent ill-equipped to correctly interpret results.

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 input schema already describes all 22 parameters with 100% coverage, so the baseline is 3. The description does not add parameter-specific meaning beyond the schema, but it does provide endpoint names that imply which parameters are relevant (e.g., 'compute-window' likely uses hours, mw, goal). This is a minor enhancement, but not enough to elevate the score.

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 tool as 'Global energy grid intelligence API' with a list of specific endpoints covering solar, rates, EV charging, and more. This distinguishes it from siblings by domain (energy grid vs. other 'pulse' tools). However, it lacks a single crisp verb like 'analyze' or 'retrieve', and the purpose is somewhat diffuse across many use cases.

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 implies usage through its list of endpoints and example use cases ('Home solar feasibility, electricity rate analysis, time-of-use optimization'). It does not mention alternatives or explicitly say when not to use this tool, leaving the agent to infer from the domain context. There is some implicit guidance based on geographic coverage and endpoint names.

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