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

No annotations are present, so the description carries the behavioral burden. It usefully discloses the fallback outcome and that results include how to claim or buy, but says nothing about read-only nature, permissions, latency, or any limits on repeated calls.

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 sentences that lead with the core action and follow with the fallback behavior; the inline examples earn their space by illustrating acceptable input. Some parenthetical example text could be trimmed, but nothing is redundant.

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 annotations, the description compensates by explaining what comes back (a single recommended agent plus how to claim/buy) and what happens when nothing matches. For a one-parameter recommendation tool this is complete enough to call correctly.

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?

Schema coverage is 100% for the single parameter, so the schema already defines it; the description adds value by showing three concrete example problems that clarify the expected level of specificity and phrasing. One-parameter tools have little room for deeper semantics, so a 4 is appropriate.

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 concrete verb ('recommend') and resource ('the single Artemis GTM agent') and gives three parenthetical problem examples, so an agent immediately knows what it produces. It does not explicitly distinguish itself from siblings like list_agents or claim_free_agent, so it stops short of a 5.

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 clearly frames the trigger condition (a B2B go-to-market problem expressed in plain language) and even covers the no-match case by routing to the free AI GTM Engineer. It does not name a sibling tool as an alternative or state when not to use it, so it lacks explicit routing guidance.

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