Request Usage-By-User Report

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

Annotations already disclose non-read-only, non-idempotent, open-world behavior, and the description adds the key behavioral detail that the call is asynchronous and returns a job_id to poll. This adds context beyond the annotations — no contradiction; readOnlyHint=false is consistent with creating a background job resource.

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, front-loaded with the purpose and followed by the essential async follow-up. Every word earns its place; there is no padding and no repetition of schema content.

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 simple async job-request tool with no output schema, the description fully covers the return value (job_id) and next step (poll with lyzr_report_get_status). It could specify org scoping or conditional param requirements, but the schema handles parameter semantics and the core flow is completely explained.

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 all five parameters and their enums are already fully documented in the schema. The description adds no parameter-level detail, which matches the baseline-3 rule for high schema coverage.

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 ('Request') paired with a concrete resource ('async usage report broken down by user'), immediately communicating the tool's function. It clearly distinguishes from sibling report tools via the 'by user' dimension and orients the agent to the async pattern by naming the polling companion, lyzr_report_get_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 conveys the essential usage workflow: call this tool to request the report, receive a job_id, then poll with lyzr_report_get_status. It does not explicitly name alternatives like lyzr_report_usage_by_model or lyzr_report_usage_by_sub_account, but the by-user scope plus the async polling instruction give clear contextual guidance.

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