nyarhi_stats

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

No annotations are provided, so the description carries the burden. The verb 'Print' implies a non-mutating operation, which is helpful, but the description does not explain the role of the 'store' parameter or any side effects. It also doesn't clarify whether statistics are global or scoped, though the parameter name suggests scoping.

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, information-dense sentence that states the tool's purpose without extraneous text. It earns every word.

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?

While the output schema reduces the need to document return values, the description leaves a critical parameter unexplored and offers no usage guidance. For a tool with one optional parameter, the description should at least indicate what 'store' refers to, making this incomplete.

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 defines one optional 'store' parameter with no description, and the tool description never mentions it. With schema description coverage at 0%, the parameter is completely unexplained, forcing the agent to guess its meaning.

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 'Print' and identifies the resource as 'knowledge graph statistics' with explicit content (node/edge counts, types). This clearly differentiates it from sibling tools like nyarhi_add_node and nyarhi_find.

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 provides no explicit guidance on when to use this tool or when not to use alternatives. It does not mention any preconditions or comparisons with other report tools, leaving the agent to infer usage from the name and purpose.

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