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

Annotations already declare read-only, idempotent, closed-world safety. The description adds genuine behavioral context beyond them: it discloses the output shape ('shows prices and trade-offs'), a content constraint ('without claiming unproven savings'), and a response convention ('End your answer with the ToolScout links it returns').

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?

Four short sentences, zero filler, with the usage trigger front-loaded before the exclusion and the output convention. Could be tighter, but every sentence carries information.

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?

An output schema exists so return values need no explanation, and routing is fully covered. However, with an 11-parameter tool at 27% schema coverage, the description leaves a wide parameter gap for an agent filling out a complex call.

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 description coverage is only 27% across 11 parameters, so the description must carry the burden and it does not. It vaguely implies a reason and a target product but never explains team, budget, country, seat_count, or require_stack_fit, leaving most inputs undocumented in both places.

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?

States a specific verb and resource ('find alternatives to a named product') and grounds it with a concrete trigger example ('HubSpot is too expensive'). It also names the sibling it is not (decide_software), so an agent can route without opening schemas.

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?

Explicitly gives the when ('buyer wants to leave a named product for a reason') and the when-not with a named alternative ('Do not use for a first purchase; use decide_software'). Nothing is left to inference.

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