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

With no annotations, the description carries the full burden, and it does disclose the kinds of data returned, including counts from prior agents. However, it does not explicitly state that the operation is read-only, whether it requires permissions, or how the stats are generated or scoped, leaving important behavioral traits implicit.

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 definition is compact and front-loaded with the core purpose, followed by a short usage sentence. The enumeration of stats is long but each item helps the agent understand what the tool returns, so little is wasted.

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 zero-parameter stats tool with no output schema and no annotations, the description provides sufficient context by listing the metrics returned and indicating its orienting role. It could be stronger if it clarified the return format or whether the stats are live or cached, but it is largely complete for an agent deciding whether to call it.

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 the baseline is 4 under the scoring rules. There are no parameter semantics to clarify, and the empty schema is fully consistent with the description.

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 clearly states the tool's purpose as returning graph-level statistics and enumerates the specific metrics available, such as piece count, connection count, and orphan count. It distinguishes itself from navigation-oriented siblings by framing the result as stats, but it does not explicitly differentiate from other graph-inspection siblings like graph_changes_since or active_frontier.

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?

It gives a clear usage context: 'Use this to orient before navigating,' which tells the agent when to invoke the tool relative to navigation tools. It does not, however, name specific alternatives or state when not to use this tool, so the guidance stops short of full when/when-not coverage.

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