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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds non-redundant context: it returns medians rather than averages, names the data source (Stratalize industry composite), discloses per-call cost, and provides a concrete consolidation-threshold example. No contradiction with annotations.

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 front-load the trigger and output, then use an example, source, and pricing to round out the picture. Every sentence earns its place, and the example is long enough to clarify the metric without bloating the description.

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's explicit return list—median total spend, category breakdown, productivity tool medians—is valuable and mostly sufficient. The main gap is the lack of parameter vocabulary, but the use case, example, source, and cost together give an agent enough context for a typical 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 0%, so the description must explain the parameters, but it only says 'by industry' and includes a 'Mid-market healthcare org' example. It never defines acceptable values for `industry` or `company_size`, nor does it enumerate supported industry or company-size tiers.

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 use case (validating total IT spend against peers, building a CFO budget baseline) and the returned data (median monthly total software stack spend, category breakdown, productivity tool medians by industry). This clearly identifies it as an industry-level spend benchmark and distinguishes it from category- or vendor-specific sibling tools.

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 opens with explicit 'Use when...' guidance covering two concrete scenarios and even names the presentation context. It does not mention alternatives or when not to use it, so it stops short of full routing guidance.

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