user_activity

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

With no annotations, the description carries full responsibility. It discloses the data source (materialized view), date semantics (inclusive/exclusive), return shape (one row per host+date), and filter behavior. It does not mention limit behavior or potential data staleness explicitly, but the materialized view hint and detailed row semantics cover most important behavioral aspects for a query tool.

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 compact single paragraph that front-loads the core purpose, uses clear punctuation (em dashes) to separate concerns, and includes illustrative examples without becoming verbose. Every sentence adds value.

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?

The description covers the data source, filtering options, date boundaries, and output granularity, which is largely sufficient for an agent to select and invoke it. The availability of an output schema likely covers column details, but the unexplained limit parameter leaves a small completeness gap for correct invocation in scenarios needing large result sets.

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 0%, so the description must fully explain parameters. It explains host_email (single user vs team), and since/until with ISO-8601 and inclusive/exclusive formatting. However, it does not describe the limit parameter at all, which is a gap given the absence of schema descriptions.

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 identifies the tool as providing per-user daily call activity from the mv_user_daily materialized view, with specific examples of questions it answers. It distinguishes itself from generic query and search sibling tools by focusing on user-centric call metrics.

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 gives clear context for when to use the tool (e.g., 'how many calls did X have this week'), and explains the host_email filter for single-user vs team view. However, it does not name alternative sibling tools or explicitly state when not to use this tool, so it lacks exclusions but has strong usage context.

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