get_usage_stats

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

No annotations are provided, so the description carries the full burden. The verb 'Menampilkan' (displays) indicates a read-only operation, and the description clearly lists the types of data returned. It does not mention side effects, auth requirements, or rate limits, but for a simple stats display tool, this is adequate.

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 a single, well-structured sentence that front-loads the main purpose and then lists specific statistics. It is concise with no unnecessary words, making it easy for an agent to parse quickly.

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 tool with no parameters and no output schema, the description fully specifies what the tool does and what data it returns. The sibling tool is clearly different, and the description is complete for its simplicity.

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 0 parameters, so the schema is non-informative. The description adds no parameter details because there are none to add. Baseline for 0 parameters is 4, and the description does not need to compensate for any missing 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 clearly states the tool's function: displaying usage statistics for the Gemini Vision API, listing specific metrics such as today's calls, total calls, remaining daily limit, per-model breakdown, and daily history. This distinguishes it from the sibling tool analyze_image, which is for image analysis.

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 usage context is implied by the description: use when needing API usage stats. It does not explicitly exclude other tools or provide alternatives, but the clear focus on usage statistics makes the use case obvious. No explicit 'when not to use' is given, but it is not necessary given the simplicity.

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