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

Annotations already cover the safety profile (readOnly, non-destructive, closed world), yet the description still adds real behavior: your_size scales only the reading portion while fixed agent overhead is preserved, output includes a typical and a budget/worst-case figure, and price source defaults are stated. The caveat that the result is an estimate derived from small test jobs rather than a quote is exactly the kind of expectation-setting an agent needs.

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?

Purpose is front-loaded in the first sentence and every following sentence carries distinct information (scaling rule, return shape, price default, caveat) with no filler. It is dense but well-ordered; a slightly tighter phrasing of the scaling sentence would make it a 5.

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?

There is no output schema, so the description must describe returns, and it does: typical vs budget figure per run and per month when runs are given. Combined with the price-default rule and the estimate-vs-quote caveat, an agent has everything needed to call it and interpret the result.

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%, so the baseline is 3; the description earns above that by explaining the effect of your_size (proportional scaling of the reading component, fixed overhead retained) and the conditional meaning of runs_per_month (monthly figures only when supplied). It adds interpretive meaning rather than restating the schema.

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 first sentence gives a specific verb ('Estimates') plus resources ('tokens and dollar cost of an AI agent task') and the method ('from the measured benchmark job closest to it'). No sibling tool (list_benchmark_jobs, render_agent_map, check_agent_one_page, check_agent_one_page) does costing, so the agent can distinguish it immediately.

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 supplies clear situational guidance: pick the closest benchmark job, pass your_size only for jobs that scale with reading, and rely on benchmark-day prices unless current prices are supplied. It never names an alternative sibling or states an explicit 'do not use this for X' exclusion, so it stops short of the 5 bar.

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