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

Beyond the readOnly/idempotent annotations, the description discloses significant behaviors: no pagination, no row cap, mixed-currency handling with per-currency row splitting, timezone bucketing, and default psr_types behavior. It even warns against summing price columns across currencies and explains that summing total_gen_mwh across split rows is correct. This is rich, non-obvious behavioral context.

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 long but dense and front-loaded with the core purpose, followed by concrete examples. Each paragraph contributes unique information, though it is a continuous block without headings and could be trimmed for the less-common slugs. It is appropriately sized for the tool's complexity.

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?

capture_price, tb_spread, and emissions receive detailed documentation, but negative_price_hours, residual_load, and res_share are merely listed without explanation. Combined with the absence of to_zone/from_zone semantics, this leaves meaningful gaps for an agent trying to select or configure the right slug, despite the presence of an output 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?

With 0% schema description coverage, the description compensates thoroughly for most parameters: slug values, aggregation semantics, zone multi-zone behavior, psr_types examples, tz examples, and date formatting via examples. However, to_zone and from_zone are never mentioned, leaving two parameters without any semantic guidance.

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 opens with a specific action—'Compute capture price, capture rate, TBx battery-arbitrage spreads, and other generation-weighted market metrics server-side from landed Parquet'—and enumerates the available slug keys. It differentiates from get_tb_spread by explicitly routing single-day timestamp requests to that sibling. An agent can confidently tell this tool apart from other data endpoints.

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?

It states exactly when to prefer this tool: 'Use this instead of fetching hourly prices + hourly generation yourself and weighting them client-side' and justifies with 'no row cap and no pagination.' It also points to get_tb_spread for a different use case and references list_derivations() for slug keys, giving clear routing advice.

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