Get Analytics

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions what the tool generates but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns data in a specific format, or involves any side effects. For a reporting tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, efficient sentence that front-loads the core purpose and lists key components. It avoids unnecessary words and gets straight to the point, though it could be slightly more structured by separating usage context from functionality.

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 the tool's complexity (analytics generation with multiple report types) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects, return values, or detailed usage scenarios. The description alone is insufficient for an agent to fully understand how to invoke and interpret results from this tool.

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 description lists report components (summary statistics, purpose breakdown, daily trends, recent activity patterns) that partially map to the 'report_type' enum values, adding some meaning beyond the schema. However, with 100% schema description coverage, the schema already documents all parameters thoroughly. The description doesn't explain parameter interactions (e.g., that 'custom_period' requires date_from/date_to) or add significant semantic depth, so it meets the baseline.

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 purpose: 'Generate analytics reports on contact submissions' with specific components listed (summary statistics, purpose breakdown, daily trends, recent activity patterns). It uses a specific verb ('Generate') and identifies the resource ('analytics reports on contact submissions'). However, it doesn't distinguish this tool from sibling tools, which are unrelated (blog posts, GitHub activity, hiring, messaging, web operations).

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or exclusions. While sibling tools are unrelated, there's no explicit comparison or usage context provided beyond the basic function.

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