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

With no annotations at all, the description carries the behavioral load and does well: it discloses the unauthenticated rate limits (10/min, 100/day per network), that exceeding them surfaces API-key instructions, and that keyed calls run on the key's own quota. It does not describe the shape of the returned answers or latency, which keeps it from 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?

Three front-loaded sentences with no filler; the capability comes first and the quota/fallback mechanics follow. Slight redundancy in restating the API-key escalation twice, but every sentence carries operational value.

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 tool with a deeply nested schema, no output schema, and no annotations, the description covers auth and limits but says nothing about what a response looks like (per-question probabilities vs. labeled choices vs. expected level) or how 512-question batches behave. Adequate, not complete.

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%, so the schema already documents model, state, and the question-type union in detail. The description's 'typed questions about a state' echoes rather than extends that, so the baseline 3 is appropriate.

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 concrete verb and resource: ask typed questions about a state and receive calibrated probabilities. It is specific enough to distinguish from the only sibling (list_models, which enumerates model ids), but the term 'Drex' and 'typed questions' are left for the schema to define, so the purpose is clear rather than crisp.

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?

Explains the free tier and quota escalation, but never says when to reach for this tool versus alternatives or what kinds of tasks it suits (classification, scoring, boolean decisions). No exclusions or prerequisites are given beyond the media-type restriction which lives in the schema.

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