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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so safety and scope are covered. The description adds the output breakdown (created/sent/accepted/rate), which is genuinely useful, but says nothing about permissions, aggregation semantics, or empty-range behavior.

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 tight clauses with zero filler; the computed metrics come first and the usage hint second. Every phrase 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?

With no output schema, the description usefully enumerates the returned funnel stages, which is what an agent needs to interpret results. Minor gaps remain around how 'accepted rate' is derived and whether results are aggregated or itemized.

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?

Both parameters are fully documented in the schema, including the YYYY-MM-DD inclusive format. The description only refers to 'a date range' and adds no syntax or boundary nuance beyond what the schema already states, so baseline 3 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?

States a specific computation (quote-to-close funnel) over a defined scope (date range) and enumerates the metrics produced: quotes created, sent/pending, accepted, accepted rate. This is far more specific than a name restatement, though it does not explicitly name a sibling it is distinct from.

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?

'Use for conversion rate / pipeline funnel' gives concrete user-intent triggers that map a request to this tool, which is useful routing guidance. It stops short of stating exclusions (e.g. when to prefer revenue_by_month or ar_aging instead).

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