classify_users

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

With no annotations, the description carries the full burden, and it does disclose real behavioural detail: the exact segment definitions, that output keys remain English while labels are localised to en/ko/ja. It still omits where results go (returned vs written back), whether the CSV is modified, and any failure modes for a 3-param tool.

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 compact sentences with the purpose and segment definitions front-loaded, followed by the one parameter clarification. No filler; the parenthetical segment definitions are load-bearing rather than redundant.

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?

No annotations, no output schema, and 0% schema coverage mean the description is the only documentation, yet it leaves the two required inputs undefined and says nothing about the return shape (labelled rows? file? counts?). It is under-specified for a tool whose only other context is a bare JSON schema.

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 0%, so the description must compensate, and it only covers one of three parameters: `lang` is meaningfully enriched (en/ko/ja values, keys stay English). The two required parameters, `csv_path` and `value_event`, are never explained — notably `value_event`, whose semantics are not inferable from the name.

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?

Names a specific operation (classify users into behavioural segments) and defines each segment inline (churned, weekend_only, regular, casual), so the agent knows exactly what the output categories mean. It is distinguishable from reporting siblings like retention_curve or onboarding_funnel, though it never explicitly contrasts itself with them.

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?

There is no statement of when to reach for this tool versus siblings such as find_aha_moments or retention_curve, and no prerequisites (e.g. data freshness, required event coverage) are given. Usage must be inferred entirely from the one-line purpose.

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