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

With no annotations provided, the description carries the behavioral burden. It does so by stating the operation is read-only ('Return') and enumerating what is returned. It does not note caveats such as data freshness or scope, but for a no-parameter stats tool this is sufficient.

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?

One sentence with all critical information front-loaded; no filler or repetition. The list of metrics is compact and every word earns its place.

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?

The description covers the purpose, return type, and content for a simple no-parameter tool, and an output schema exists for return format. It does not discuss alternatives or caveats, but given the simplicity and sibling separation, nothing core is missing.

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?

There are no parameters, so the description does not need to elaborate on input semantics. The schema is empty and the description adds no parameter confusion. The zero-param baseline applies.

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 a clear verb ('Return') and a specific resource ('outreach funnel stats'), and lists the exact metrics ('counts per stage, reply rate, conversion rate'). This distinguishes it from the sibling tools, which are about recording touches and updating stages, not reading 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 implies the tool is the go-to for funnel statistics, but it doesn't explicitly state when to use it instead of record_touch or update_stage. It also doesn't mention any exclusions or alternative retrieval tools. The usage context is clear enough from the resource name, but it remains implied rather than stated.

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