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

With no annotations, the description carries the full behavioral burden and does disclose two useful traits: responses are capped near 12 KB and an unknown kind returns the kind list. It says nothing about auth, freshness, or read-only nature, so it is partial but not empty.

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?

The purpose is front-loaded in one sentence, followed by a compact per-kind list where every entry carries its own entity/window/limit semantics. It is dense but no line is redundant, given the 0% schema coverage.

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 17-mode dispatcher with no output schema and no parameter documentation, the description supplies the kind vocabulary, per-kind arguments, defaults, and the response-size cap. Return shapes per kind are not described, but the cap notice plus no output schema make that an acceptable 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 coverage is 0% and the kind parameter has no enum, so the description compensates heavily: it lists all 17 valid kinds, marks which need entity vs optional entity, states window defaults (90, 24) and limit defaults (20), and gives severity values (notable|alert|critical). Only detail's non-peg behavior is left implicit.

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 states a specific resource (market, governance and risk data) and enumerates the 17 kinds it returns, so an agent knows exactly what it fetches. It does not, however, distinguish this tool from siblings like basis_answer or entity_read, leaving overlap unexplained.

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 tells the agent to 'pick a kind' and annotates each kind with its expected entity window/limit, which implies when each is appropriate. But there is no explicit when-to-use vs basis_answer/entity_read guidance or any exclusion criteria, so routing among siblings is left to inference.

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