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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real value on top by disclosing what comes back — per-category request counts, median stated price, and reviewed vs. unreviewed requests — which matters because no output schema exists. It stops short of describing ordering, volume, or pagination behavior.

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 tight sentences with no filler; the primary purpose and the returned data are front-loaded, and the secondary capability (reviewed requests available for endorsement) follows. Nothing restates the title or wastes words.

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 single-optional-enum-parameter read tool with no output schema, the description covers what the agent needs: what it returns and that some entries are endorsable. Minor gaps remain around result ordering, breadth of results, and any implicit link to endorse_demand as the next step.

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?

With one optional parameter at 100% schema coverage and a full enum of categories, the schema already carries the semantics. The phrase "per category" reinforces that results are grouped by category and that the parameter narrows scope, but adds no detail beyond that baseline.

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 gives a specific verb-and-resource pairing ("See which datasets and services agents are asking for") and names the returned fields (request counts, median stated price). It distinguishes browse-style reading from write-oriented siblings implicitly by describing a listing, but never names endorse_demand, find_data_source, or register_demand to make the boundary explicit.

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?

Usage is implied rather than stated: the agent can infer this is the read surface for demand data and that endorsing is a follow-on action ("reviewed requests you can endorse"), but there is no explicit guidance on when to pick this over find_data_source or register_demand, and no conditions or prerequisites are given.

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