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

With no annotations, the description carries the full burden for behavioral disclosure. It mentions a distinguishing behavior ('distinguishes live supply from demand tests') but does not clarify whether the operation is read-only, how results are filtered, whether experiments are included by default, or what the response contains. The one behavioral hint is too vague to rely on.

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 description is a single efficient sentence with the main verb front-loaded and no filler. It earns high marks for brevity, though the compressed wording makes some parts cryptic.

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?

The tool is simple (2 params, no nested objects), but there are no annotations or output schema, so the description must cover return behavior, filtering semantics, and the role of include_experiments. It does none of this, and central terms like 'AIP intelligence shelves' are left undefined. The context is insufficient for confident invocation.

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 must compensate for explaining parameters, but it does not. 'Matching a need' loosely implies the query parameter, but include_experiments is entirely unexplained and its effect on live supply versus demand tests is unclear. The description adds minimal meaning beyond the parameter names.

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 action ('Find') and resource ('AIP intelligence shelves'), and adds a distinguishing trait by noting it separates 'live supply from demand tests.' However, the domain terms are opaque and it does not explicitly differentiate from sibling query_intelligence, so it is clear but not fully distinguishing.

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?

No explicit when-to-use guidance or alternatives are named. The phrase 'matching a need' implies a search-oriented use compared to list/describe/query siblings, but the description never states when to prefer this tool over query_intelligence or what scenarios it excludes. This leaves the agent to infer usage rather than be told.

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