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

With no annotations present, the description carries the full disclosure burden. It transparently states the tool's read-only nature by saying it 'Returns' three specific pieces of information, and it adds a behavioral recommendation (call this first). It stops short of explicitly stating there are no side effects or describing error conditions, but for a zero-parameter getter the behavioral disclosure is largely adequate.

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 exactly two sentences: the first lists the concrete return values, the second tells the agent when to invoke the tool. Every word earns its place, and the most important behavioral detail is 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?

For a tool with no parameters, no input schema, and no output schema, the description is fully self-contained: it tells the agent what the tool returns and in which situation to use it. Nothing essential for correct invocation is missing.

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?

The tool has zero parameters, so the baseline is 4, and there is no parameter ambiguity. The description's mention of 'data' and 'segments' is enough to set context for what the tool reports, though it doesn't need to define parameter meanings.

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 ('Returns') and names the exact resource and output fields: last activated time, number of live segments, and last run state. This clearly distinguishes it from sibling tools like get_supplier_exposure or list_drug_recalls, which retrieve domain data rather than freshness metadata.

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?

It gives explicit situational guidance ('Call this first when you need to know whether the data is fresh'), establishing a clear trigger for use. It does not explicitly mention when not to use it or name alternative tools, but the context strongly implies this is the meta-data companion to the domain-data sibling tools.

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