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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real semantic context about how to interpret the output (index where 1.0 is exactly typical, values read against a cohort), but says nothing about permissions, data freshness, or pagination. Adequate value over annotations but not rich.

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 sentences, front-loaded with the core deliverable and followed by a justification of why the dimension view matters. The unexplained 'PRO' prefix is mild noise, but overall the text is efficient and well-ordered.

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 well, enumerating the cohort statistics and the 1.0-typical index. It still omits the set of available dimensions and any relationship to sibling insight tools, which an agent would need for confident selection.

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%, with slug and context both fully documented in the schema, so the baseline is 3. The description adds no syntax or usage detail for either parameter, leaving the schema to carry the full load.

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 names a concrete resource (a company's investment dimensions) and precisely the derived columns returned (cohort median, mean, max, rank, percentile, index). It is clear what the tool surfaces, but it never distinguishes itself from closely related siblings like insights_dimensions, get_company_insight, or company_peers, so an agent cannot route between them from this text alone.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named despite several dimension/insight siblings existing. The only implicit cue is that a raw score is 'unreadable on its own,' which hints at complementary use but stops short of routing.

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