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

With no annotations, the description carries the full burden and does useful work: it defines signals as observed changes, not purchase-intent claims, and states that every signal includes before/after state, evidence, and confidence. It could additionally disclose ordering or pagination behavior, but the core semantics are well covered.

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?

Three sentences deliver scope, filters, a concrete use case, result contents, and a caveat. It is front-loaded with the core purpose and every sentence adds value without repeating the title or schema verbatim.

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?

Given no output schema and no annotations, the description compensates by explaining what a signal is and what each result contains. The schema covers parameter limits. It stops just short of full completeness by not explicitly stating how filters combine or how results are ordered.

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 the baseline is 3. The description adds helpful technology examples like 'vue' and 'hubspot', and restates the event types and score range, but it does not materially extend the schema's meaning for limit, since, or offset.

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 opens with a specific verb and resource: 'Search Revnuvo's signal feed across all observed companies.' It enumerates filter dimensions and gives a concrete question the tool answers ('which companies recently adopted technology X?'), making it easy to distinguish from per-company siblings like revnuvo_get_company_changes.

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?

The description clearly frames when to use this tool: for cross-company signal search and technology adoption questions, and it cautions that signals are observed changes rather than purchase-intent claims. It does not explicitly name alternative tools or state when not to use it, so it falls just short of full routing guidance.

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