mimir_stats

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

Annotations declare readOnlyHint=true, which is consistent with the description. The description adds value by detailing exactly what statistics are returned, which goes beyond the annotation's simple read-only indication. No contradictions.

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 sentence that efficiently enumerates all returned statistics without redundancy. It is front-loaded with the main verb and resource, and every phrase adds value.

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 tool has no parameters and an output schema exists (as per context signals), the description is complete. It covers all aspects of the output, and the agent can rely on the output schema for detailed structuring.

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 input schema has no parameters, so the description doesn't need to explain parameters. However, it compensates by describing the output, which is useful for an agent. Baseline for 0 params is 4, and this description meets that.

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 specific verbs ('Return') and clearly lists the types of statistics (entity counts by category, type, decay layer; journal count; state count; file size; date range). It distinguishes itself from sibling tools like 'mimir_health' which likely focuses on system status, whereas this focuses on database content statistics.

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 implicitly states its purpose (obtaining comprehensive stats), and given there are no parameters or configuration, the use case is clear. It doesn't explicitly state when not to use, but the context of sibling tools provides differentiation. A score of 4 is appropriate as it's clear but lacks explicit exclusions.

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