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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered; the description adds the non-obvious trait that the values are a heuristic model estimate rather than measured/hardware-derived output. That is exactly the kind of fidelity caveat annotations cannot express. It does not describe shape, number of scenarios, or pagination.

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?

Two short sentences, front-loaded with what is returned, followed by the usage condition. The 'not quantum hardware' clause is slightly oddly phrased but is a single compact caveat rather than filler.

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 zero-parameter, read-only tool with no output schema, the description conveys enough to call it correctly: what it returns, that it is a model estimate, and when to reach for it. The minor gap is that nothing hints at the magnitude or labelling of the returned weights.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly avoids inventing parameter guidance.

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 resource – heuristic scenario probabilities / scenario weights – with a parenthetical clarifying the source is a model estimate. It is clearly distinct from mutation-oriented siblings like simulate_scenario or submit_forecast, though it never explicitly names which sibling to prefer for forecast results.

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?

'Call this when you need scenario weights and accept they are a heuristic' gives an explicit triggering condition plus a caveat about acceptable fidelity. It stops short of naming an alternative (e.g. simulate_scenario or get_forecast_results) for cases where a non-heuristic answer is needed.

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