athena_diffusion_matrix

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

No annotations are present, so the description carries the full burden. The verb 'Return' implies a read-only operation, but the description does not explicitly confirm safety, clarify whether computation occurs, or explain side effects. It does add some context about reliability and causal-weight metadata, but this is more about output content than behavioral traits.

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, focused sentence that front-loads the action ('Return') and packs the key qualifiers without redundancy. Every word contributes to understanding the tool's output.

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 no output schema and a highly specialized domain, the description leaves gaps: it does not specify the structure of the returned matrix, the meaning of 'learned/shrunk', or how reliability and causal-weight metadata are presented. It is adequate for a surface understanding but not fully self-sufficient for an agent needing to interpret the result.

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 accepts zero parameters, so the 100% schema coverage is trivial. The description adds meaningful context by explaining what the returned data represents, which compensates for the empty input schema. A score of 4 reflects the baseline for zero-parameter tools with no param semantics needed.

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 uses a specific verb ('Return') and clearly identifies the resource ('learned/shrunk token-artifact-module-domain-system diffusion coefficients') with additional metadata qualifiers. It distinguishes from most siblings by focusing on a matrix of diffusion coefficients rather than observation or simulation, though it doesn't explicitly name an alternative.

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 about when to use this tool versus alternatives such as athena_diffusion_observe or athena_coordinate_matrix. The description only states what it returns, with no mention of scenario fit, prerequisites, or exclusions.

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