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

With no annotations, the description must carry the behavioral burden. It clearly explains that this is a read-only operation returning three counters and defines each counter's meaning. It does not mention side effects, rate limits, or other behavioral traits, but for a simple getter with no parameters and no mutation, the return-value explanation is sufficient. The description adds value by explaining what each number represents.

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 compact and well-structured: a one-line hook, a one-line cautionary note, and a three-line bulleted return list. Every sentence earns its place. There is no fluff, and the format makes the return fields easy to parse. It is front-loaded with the most important context ('sample size behind everything').

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 zero-parameter getter with an output schema, the description is complete. It explains the purpose, the use case, and each returned field's meaning. There is no missing information about authentication, side effects, or prerequisites. The output schema likely provides the structured return types, so the description doesn't need to redisclose them. This is fully sufficient for an agent to invoke and interpret results.

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 schema is trivially complete (100% coverage). The description doesn't need to add parameter semantics. Per the rubric, a baseline of 4 is appropriate for zero-parameter tools. No additional information about inputs is needed.

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 what the tool does: it returns sample-size related counters (signals_fired, data_points, days_collecting). It distinguishes itself from siblings like get_system_health (health status) and get_signal_history (historical data) by focusing on the aggregate counts behind the system's data collection. The specific verb 'returns' plus the explicit output list makes the purpose unmistakable.

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 provides an implicit usage context: 'Small samples cannot prove an edge — this tells you exactly how small.' This tells the agent when to use this tool (when assessing data sufficiency). It does not explicitly name alternatives or exclusions, but the context is clear enough for a zero-parameter getter. It could have explicitly said 'use this to check sample size before making conclusions,' but the intent is embedded.

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