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

Annotations already declare it read-only, idempotent and non-destructive. The description adds genuinely new behavioral context: counts are computed rather than stored, so they cannot go stale — a freshness guarantee that changes how an agent should trust the values.

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?

Two compact sentences with no filler, and the payload of returned figures is front-loaded. Efficient for the amount of information conveyed.

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?

With no output schema and no parameters, the description must convey what comes back, and it does enumerate the returned metrics. Missing only guidance on when to prefer it over sibling listing tools.

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 takes zero parameters, so there is no parameter semantics burden. Baseline of 4 applies; the description correctly implies no input is required.

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 exactly which figures are returned (years working, projects completed, built-from-scratch count, response times), a clear resource for a tool whose name 'get_facts' alone would be opaque. It does not explicitly distinguish itself from siblings like list_projects, which return project data rather than aggregate figures.

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?

There is no statement of when to call this versus the many sibling tools (list_projects, get_service, search_services, etc.). The use case of pulling aggregate stats is only implied by the enumerated figures.

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