llm_team_report

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

No annotations are provided, so description carries full burden. It discloses the read-only nature (report) and that user/project are auto-detected. This adds context beyond typical assumptions for a report 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 sentences plus an inline parameter list. Every sentence adds value: the first states purpose and scope, the second lists metrics, and the parameter explanation is clear and compact. No fluff.

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 only one optional parameter and an output schema present, the description covers the key aspects: what the report shows, how user/project are determined, and the period values. It does not mention filtering by other dimensions, but for a simple report this is sufficient.

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 schema provides no description for the 'period' parameter (0% coverage). The description compensates by listing allowed values ('today', 'week', 'month', 'all') and explaining the default, which adds meaningful guidance.

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?

Description clearly states it shows a team savings report with specific metrics (call counts, cost savings, free-tier usage, top models) for the current user and project. However, it does not distinguish from sibling tools like llm_savings or llm_usage, which may have overlapping functionality.

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 implies when to use (when a team savings report is needed) but provides no explicit guidance on when not to use or alternatives to consider. No exclusions or best practices are mentioned.

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