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

With no annotations, the description carries the full behavioral burden, and it delivers: it discloses that the forecast is distribution-free, deterministic, never-under-protective, calibrated on real cross-card price history, and honest out-of-sample, and it explains the meaning of the stated risk. It also notes the two plain-English letter grades, giving an agent a solid model of what to expect.

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?

Three compact sentences front-load the core purpose, then add only high-signal behavioral detail. There is no filler, repetition, or schema duplication.

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 single-parameter read-style tool with an output schema and strong behavioral description, the definition is nearly complete. It could be slightly stronger by naming simulate_price explicitly as the alternative and stating any prerequisites for using this forecast, but nothing essential is missing.

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% and there is only one parameter, card_name, already described with an example in the schema. The description adds no additional parameter-level meaning, so the baseline score of 3 applies.

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 first sentence names a specific verb and resource ('Get ... calibrated conformal risk forecast for a trading card') and the description goes on to contrast it with Monte Carlo simulation, distinguishing it from sibling simulate_price. This makes the tool's identity unambiguous.

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 positions this as 'the recommended, honest default forecast' and explicitly contrasts it with a Monte Carlo simulation, giving clear context for when it should be preferred. It stops short of explicitly naming the alternative tool or stating hard exclusion criteria, so it is not a full 5.

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