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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context beyond that: the data source (Carta State of Private Markets), the quarterly refresh cadence, and the per-call cost ($0.02 USDC). These are not present in any structured field.

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 sentences, each earning its place: value proposition, source/cadence, target users/use case, and price. The core subject is front-loaded in the first sentence. Slightly more than the minimum necessary, but there is no redundancy or filler.

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?

For a simple two-param enum-only lookup with annotations covering safety, the description is nearly complete. It conveys the return content via the listed metrics, the data provenance, and the cost. The main gap is that it doesn't state the exact response shape, but for a benchmark lookup with enum inputs that is a minor omission.

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 carries the parameter-semantics burden. It compensates well by naming both parameters in context — 'by stage and sector' — and explains what the output metrics (dilution, option pool, etc.) are measured against. It stops short of elaborating the enum value distinctions, but it meaningfully connects the two params to the tool's purpose.

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 clearly identifies the resource (venture capital round benchmarks) and the specific data fields it returns (pre-money valuation, round size, dilution, option pool standards). Among 150+ sibling benchmark tools, 'venture capital round' + 'by stage and sector' makes this uniquely distinguishable from peers like get_pe_return_benchmark or get_ma_multiples_benchmark.

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 gives a concrete use-case context — 'Used by founders, VC CFOs, and early-stage investors for round pricing and cap table modeling' — which implies when to reach for it. However, it names no alternatives and gives no exclusions, even though sibling tools like get_saas_metrics_benchmark or get_pe_return_benchmark overlap in the fundraising/valuation domain.

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