llmtrim_stats

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

Describes a read-only report operation without side effects; no annotations provided, but description clearly indicates non-destructive behavior and references data source (local ledger).

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 efficient sentences, front-loaded, every word adds value.

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?

Adequately explains purpose and data source; lacks output format details but is sufficient for a simple reporting tool with no parameters.

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?

No parameters exist in schema; baseline 4 for zero parameters; description does not need to add parameter info.

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?

Clearly states it reports recent savings (tokens trimmed and dollars saved) from the local ledger, distinguishing it from compression tools like llmtrim_compress.

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?

Implies use for obtaining savings data, contrasts with siblings that perform compression; no explicit when-not or alternative guidance but context is clear.

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