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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds substantial behavioral value beyond that: the score is a transparent weighted sum, each contributing fact is disclosed in evidence[] with its weight, coverage[] reports which inputs existed, and the score is a prioritization ranking, not a probability of sale. There is no contradiction with 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?

The description is front-loaded with the core purpose and every sentence earns its place: purpose, methodology, and caveat. It is, however, dense — the factor list runs long and the final clause 'when the internal predictor has scored this tail, its probability' is grammatically convoluted, slightly hurting readability. Well-structured but not maximally crisp.

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 one-parameter tool with 100% schema coverage, full annotations, and an output schema in place, the description carries the full interpretive burden — and it does: what the score means, how it is computed, which inputs feed it, how evidence and coverage are conveyed, and what it should not be used for. Nothing an agent needs in order to select and invoke this tool correctly 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 description coverage is 100% — 'Brazilian registration (PR-TBL)' fully documents the only parameter, so the baseline of 3 applies. The description contributes only the marginal note that the tool scores 'one registration,' implying single-aircraft granularity. No syntax, format, or domain detail is added beyond what the schema already provides.

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 verb-resource-output: 'Score 0-100 of how likely one registration is to reach the market.' It also sharpens the purpose with an explicit boundary — 'It is not a prediction of sale: it ranks who to contact first' — which distinguishes it from siblings like jt_market_listings and jt_fleet_search. An agent can tell what this tool uniquely adds without opening any other schema.

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 gives clear context: use the score to rank who to contact first, and do not treat it as a sale prediction. The 'not a prediction of sale' clause is an explicit when-not boundary, and the evidence[]/coverage[] exposition implies the agent can inspect the reasoning before acting. However, no alternative sibling is named to route an agent away from, so the guidance stops short of a full 5.

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