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

With no annotations, the description carries the full burden and delivers: provenance ('every value has its document URL'), freshness caveats ('records are unofficial until final settlement'), data-integrity policy ('incomplete days are flagged, never filled'), and the auth/tier model ('free: most recent 30 days; Pro unlocks full history'). It does not cover error behavior or rate limits, so not a 5.

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?

Front-loaded with the tool's purpose and dataset taxonomy before the licensing boilerplate. A single dense paragraph, but it earns most of its length; the provenance claim is repeated twice ('every value has its document URL' / 'with unit, date and original source URL'), which is mild redundancy.

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?

No output schema and no annotations, so the description must do the work — and it covers dataset semantics, tier limits, caveats, and a hint at row contents (unit, date, source URL). What remains unstated is pagination/return-shape behavior and failure modes.

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 60% and the 'dataset' enum has no description in the schema at all, yet the description defines all five enum values (monthly, queue, batch_zero, peak_demand, forecast) and explains the date-range gating on 'start' tied to the free tier. That materially exceeds the schema, though start/end/limit/offset still rely on the schema.

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 verb and resource — ERCOT large loads (data centers and other 75 MW+ loads), peak demand records and forecasts — and enumerates exactly which series it serves. An agent can distinguish this from market_grid_demand or market_outlook purely from the description, without any sibling differentiation sentence.

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?

Gives clear routing context ('for the page with context see electricity_data_product slug large-load-demand') and states the free-vs-Pro gate that determines which date ranges are usable. It lacks an explicit 'use X instead when Y' exclusion, so it falls short of a 5.

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