inspect_memory_state

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

The readOnlyHint annotation already establishes that this is a non-mutating operation. The description adds meaningful context by naming exactly what is returned, going beyond the annotation. However, it does not clarify the format or granularity of the health statistics, though this is a minor gap.

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 entire description is a single well-structured sentence. It leads with the action and immediately lists the key returned data, with no filler or redundant words.

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 parameterless read-only inspection tool, the description adequately covers purpose and key return values. It lacks an explicit output schema or detailed return format, but given the simplicity of the tool, the description is sufficiently complete for an agent to invoke it correctly.

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 has zero parameters, so there is nothing for the description to explain about parameter usage. The schema coverage is effectively complete, and the description focuses on outputs rather than inputs, which 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?

The description states a specific verb ('Returns') and identifies the resource ('Mushroom Body') along with concrete outputs: total active memories, synaptic weight distribution, and health statistics. This clearly distinguishes it from sibling tools that perform different actions like remembering or resetting.

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 query_associative_memory or check_code_reflex. The description implies a read-only inspection use case, but it does not explicitly state conditions or exclusions.

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