api_analytics

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

With no annotations, the description carries full burden. It implies a read-only operation ('View') and lists data provided. It does not mention side effects, auth, or rate limits, but for a simple query tool, it is fairly transparent.

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 two concise sentences plus a bullet list, front-loaded with key information. Every part adds value with no redundancy or 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?

Given no output schema, the description specifies the metrics returned (call counts, success rates, latency, etc.), which is adequate for tool selection. It does not detail output format but covers expectations well.

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 coverage is 100%, with all parameters already described. The description adds context for scope values and project identifier but does not significantly enhance understanding beyond the schema. Baseline score of 3 is appropriate.

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 explicitly states 'View API usage analytics per project or system-wide' and lists the specific metrics (call counts, success rates, latency, token usage, top tools, daily trends). It distinguishes between project and system scopes, making the purpose clear and differentiating from siblings.

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 details two scopes ('project' and 'system') with clear distinctions, guiding when to use each. However, it does not explicitly mention when not to use the tool or provide alternatives, though no direct siblings exist for analytics.

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