athena_gp_hyperqmc

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

With no annotations, the description carries the full burden. It explicitly discloses 'Read-only' and 'deterministic', which are key behavioral traits. The deterministic Halton QMC detail also hints at reproducibility. However, it does not mention what the returned output represents (e.g., particles, approximation object) or any edge-case behavior, so it is not fully transparent.

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 a single, front-loaded sentence that states the primary purpose and methodology, followed by a brief safety note ('Read-only'). Every word earns its place; no filler or redundancy.

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?

Given the complexity of nested bounds, a required context_key, and no output schema, the description is too terse. It does not specify the expected format for bounds, what the output is (e.g., posterior samples or a fitted object), or the purpose of context_key. An agent would struggle to invoke this tool correctly without additional external knowledge.

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 0% and the description does not compensate. It hints that 'bounds' is a positive box and that 'samples' corresponds to particles, but does not explain the structure of the bounds object, the role of seed in a deterministic method, or the meaning of context_key, which is the only required parameter. This leaves key parameters underspecified.

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 clearly identifies the tool's action: approximate a GP hyperparameter posterior using specific methodology (Halton QMC particles) within a defined scope (continuous log-uniform, positive box). This is a specific verb+resource combination that distinguishes it from sibling tools like athena_gp_hyperfit or athena_gp_hyperposterior by emphasizing approximation and deterministic QMC.

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?

No guidance is provided on when to choose this tool over alternatives such as athena_gp_hyperposterior or athena_gp_hyperfit. The description implies approximation via QMC but doesn't state criteria like 'when an exact posterior is too expensive' or contrast with exact methods. It only states what it does, not when to use it.

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