get_dashboard_stats

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

With no annotations, the description should disclose behavioral traits. It clarifies the tool is read-only (get) and provides a summary, but it doesn't mention whether responses are aggregated across all users or scoped to a context, or whether the metrics are computed in real-time. The description is adequate but not rich.

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, clear sentence, front-loading the verb and resource, then listing the specific metrics. No wasted words, and it is appropriately structured for a parameter-less tool.

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 has no parameters, no output schema, and no annotations, the description does a good job of explaining what it returns. It lacks a note on the response format (e.g., JSON structure) and whether it supports date filtering, but for a simple stats snapshot it is sufficient.

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 description doesn't need to explain parameters. It does explain that it returns aggregate statistics, adding meaning beyond the empty schema, which fully covers the parameters.

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 it retrieves dashboard statistics and enumerates the specific metrics (total applications, active applications, interviews, offers, AI match score), using a specific verb 'Get'. It distinguishes itself from siblings like list_applications (which likely returns detailed records) by focusing on aggregate stats, though it doesn't explicitly name a sibling.

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 a quick overview of key metrics, distinct from detailed tooling, but it does not explicitly state when to prefer this over get_analytics_overview or list_applications. It lacks exclusions or alternative guidance.

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