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

Annotations already declare readOnlyHint/idempotentHint, but the description adds real behavioral context: counting happens server-side, with no pagination and no memory bodies read. That tells the agent this is cheap and complete, not a sampling call.

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?

Front-loaded with the purpose, then a dense field enumeration. It is long, but with no output schema each listed field earns its place by describing the return shape.

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?

Because there is no output schema, the description takes on the burden of describing return values, and it does so field by field (memories, associations, bundleNodes, byProject, byTag). Muninn-specific terms are glossed well, so an agent understands what it will receive.

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?

Zero parameters, so the schema carries no semantics to be explained. Baseline is 4; there is nothing for the description to compensate for.

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 verb+resource ('Return aggregate corpus statistics') and scopes it to the current user, immediately distinguishing it from the many list/get siblings. An agent can tell this is a read-only aggregate snapshot, not a paginated listing.

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?

Gives three concrete use cases ('how big is my memory', live corpus snapshot, compare against another system). It does not explicitly name an alternative tool it should be preferred over (e.g. muninn_memory_list), but the intent is unambiguous.

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