get_pilot_status

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

Beyond the readOnlyHint annotation, the description states the status is computed from raw observations and that the data is from a labeled synthetic pilot. This tells the agent the output is an aggregate view rather than raw data, which adds meaningful behavioral context without contradicting the annotation.

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 two short sentences with no wasted words. The first sentence names the resource and its key contents, and the second adds data provenance and synthetic labeling. It is well-structured and front-loaded.

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?

With no parameters, a readOnlyHint annotation, and an output schema present, the description provides the necessary context: data source, synthetic nature, and aggregate computation. Nothing essential is missing for an agent to call this tool correctly.

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?

There are zero parameters and the input schema has no properties, so there is no parameter burden for the description to carry. The baseline of 4 applies here.

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 uses a specific verb ('Get') and names a concrete resource ('pilot status overview'), then enumerates the contents: cohort size, observation count, date range, data quality, and active interventions. It clearly conveys what the tool returns, though it does not explicitly differentiate it from sibling tools like get_data_quality or get_intervention_status.

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 gives useful context—'Computed from raw observations' and '50-operator synthetic pilot'—which implies when this tool is appropriate. However, it does not explicitly state when to use it over alternatives or provide exclusions, so the guidance is implied rather than direct.

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