datasets_trustmrr_history

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

With no annotations, the description carries full burden. It discloses chronological order, daily accrual, and the behavior of returning a short/empty series for new startups rather than 404. It could mention rate limits or authentication, but covers key behavioral aspects.

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 with no fluff: first sentence states purpose and lists returned metrics, second sentence clarifies a key behavioral nuance (accrual and empty series). Every sentence adds value.

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, the description explains the return type (time-series), fields, and order. It lacks explicit structure (e.g., 'returns array of objects'), but the metric list and 'one point per day' give sufficient context. It does not cover error cases beyond empty series.

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 no additional meaning beyond the schema's parameter descriptions (e.g., inclusive dates, limit default/max). It does not provide context like format examples or parameter interactions.

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 clearly states the verb 'Get' and the resource 'a startup's daily history', listing specific metrics (MRR, revenue, traffic, etc.). It effectively distinguishes from siblings like datasets_trustmrr_item (current data) and datasets_trustmrr_search (search).

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 implicitly indicates usage for historical time-series data, contrasting with current-data tools. However, it does not explicitly state when not to use it or name alternatives like trustmrr_startup for a single point-in-time snapshot.

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