athena_belief_state

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

With no annotations provided, the description carries the disclosure burden. It explicitly states the operation is a read ('Read') and names the contents it returns ('belief distribution and entropy'). It does not cover failure modes, output format, or initialization requirements, but the core behavior is clearly disclosed.

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 11-word sentence that front-loads the verb and resource. It contains no filler or redundant phrasing, and every word adds meaning.

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?

The tool has no annotations, no output schema, and one undocumented parameter. While the description states the basic output, it omits crucial invocation details: the meaning of context_key, when to choose this over sibling belief-state tools, and any behavioral edge cases. These are important gaps for correct tool selection and use.

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 schema has a single required parameter, context_key, with no description, and schema description coverage is 0%. The description never mentions this parameter, so an agent cannot infer what context_key means, what values are valid, or how it affects the result.

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 ('Read') and clearly names the resource ('current finite model belief distribution and entropy'). The qualifier 'finite model' helps distinguish it from sibling tools like athena_gaussian_belief_state, and 'current' indicates a state query rather than an observe/register operation.

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 implies this tool is used to read the current belief state, but it gives no explicit guidance on when to use it versus alternatives, nor any exclusions. Without naming sibling tools or conditions, usage guidance remains only implied.

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