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

Annotations already declare this a safe read, but the description adds substantive behavioral context beyond them: the ≥3 comparable-member threshold gating headline medians/quartiles, the guarantee that monthly/per-seat/per-call prices are never blended, and the security rule that benchmark_id is a bearer secret passed as an argument rather than a URL. These are real operational constraints an agent would otherwise not know.

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?

Front-loads what is returned and packs thresholds, cohort types, and the token-handling rule efficiently into one sentence plus a short instruction. The enumeration is dense but every clause carries information; no 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?

With no output schema, the description takes on the burden of describing returns and does so thoroughly, including statistical gating rules. Only minor gaps remain, such as when to prefer this over sibling read tools and pagination/response-size behavior.

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 100%, so all four parameters are already documented in the schema, including the as_of reproducibility semantics and the response_mode enum. The description only re-emphasizes that benchmark_id is a cb_ token passed as an argument; it adds little parameter meaning beyond the schema, so the 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?

Names a specific verb (get) and resource (private custom benchmark's current report) and enumerates the exact payload returned: members, stats, cohorts, index, coverage. This is clearly distinguishable from siblings like get_price_index or compare_providers, which cover market-level data rather than a private 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?

Implies usage by scoping to a private custom benchmark (a cb_ token), but never states when to choose this over price_benchmark, get_price_index, or update_custom_benchmark, nor any prerequisites. The reader must infer the private-vs-market distinction from the word 'custom'.

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