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

No annotations are provided, so the description carries the transparency burden. It discloses that it wraps a GET endpoint, implying a read-only operation, and lists the returned data fields. However, it does not mention authentication, rate limits, or any side effects, though for a simple analytics overview this may be sufficient.

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 concise, front-loaded with 'Dashboard overview', and clearly lists the included metrics in a compact manner. It conveys necessary information without unnecessary words.

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 simplicity (no parameters, no output schema), the description is complete: it lists the key data points provided. The sibling tool names reinforce that this is the analytics-specific tool. It could be slightly more explicit about the intended use case, but it is adequate.

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 zero parameters, so the description need not explain parameter meaning. The schema is trivially complete with 100% coverage. Baseline for 0 params is 4, and the description adds no conflicting or missing param 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?

The description clearly states the tool provides a dashboard overview with specific metrics (total guests, stage breakdown, average fit score, conversion rates, etc.). The mention of the underlying GET endpoint reinforces its purpose. It is distinct from sibling tools like list_guests or draft_outreach_email.

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 usage for high-level analytics summaries but does not explicitly state when to use it over alternatives or provide exclusion criteria. It is clear context but lacks explicit guidance on when not to use it.

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