get_active_users

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. It mentions the data source ('anonymous activity pings'), which adds some context, but does not cover critical aspects such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output looks like (e.g., numeric count or structured data). For a tool with no annotations, this leaves significant behavioral gaps.

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 ('Get active user count') and includes all necessary details (metrics, app specificity, data source) without any redundant or extraneous information. Every word earns its place, making it highly concise and well-structured.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and data source but lacks details on behavioral traits, output format, and usage guidelines. Without annotations or output schema, the description should do more to compensate, but it provides a minimal viable explanation, leaving room for improvement in context.

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 description coverage is 100%, so the schema already documents both parameters ('app_id' and 'period') with descriptions. The description adds marginal value by implying the parameters relate to querying user counts for an app over time periods, but it does not provide additional syntax, format details, or constraints beyond what the schema states. This meets the baseline for high 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 specific action ('Get active user count') and resource ('for a specific app'), distinguishing it from sibling tools like 'get_active_users_all_apps' by specifying 'for a specific app' and from 'get_app' by focusing on user metrics rather than app details. It includes precise metrics (DAU/WAU/MAU) and data source ('anonymous activity pings'), making the purpose highly specific and differentiated.

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 context by specifying 'for a specific app based on anonymous activity pings,' which suggests it's for analytics purposes. However, it does not explicitly state when to use this tool versus alternatives like 'get_active_users_all_apps' (which might cover multiple apps) or other analytics tools, nor does it mention exclusions or prerequisites. The guidance is clear but lacks explicit alternatives or when-not-to-use details.

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