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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds real behavioral context beyond them: 'No forward filling, trading or collection on read,' 'Missing history/rights is explicit,' 'forecasts not observed prices,' 'history returns capped genuine observations,' and 'Returns are fractions.' These are useful operational caveats an agent couldn't get from the annotations.

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?

It is a single hundred-plus-word run-on paragraph stuffed with parentheticals, so the core purpose is not front-loaded and the three views are harder to extract than they should be. The content is mostly informative, but the structure actively impedes scanning.

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?

Against 8 params, 0% schema coverage, no output schema, and open-world behaviour, the description does a lot to explain data sources and result semantics, but it leaves half the parameters (start/end/interval/symbol/max_points) undefined for an agent that must construct calls.

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 0% across 8 parameters, so the description must compensate. It explains the view enum thoroughly and implies series_id (catalog discovery) and lag behaviour ('calendar-day lag' ties loosely to lag_days), but start, end, interval, symbol, and max_points are never addressed, leaving most of the surface undocumented.

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 (read) and a well-scoped resource: stored compute/GPU pricing plus forecasts and a correlation view against equities. It is distinguishable from get_prices/get_bars by the GPU-rental and forecast framing, though the dense parenthetical enumerations of vendors (OpenRouter, Pricify, ORNN, Databento) crowd out the one-line purpose.

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 implicit workflow is inferable: use view=catalog to discover series_id before history/correlation, so an agent can figure out sequencing. But there is no explicit when-to-use/when-not, no mention of when to prefer get_prices or get_symbol_research instead, and the view semantics are buried mid-sentence.

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