statsfm_streams_stats

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

The description conveys the core behavior—aggregating user listening stats—and mentions optional windowing. But with no annotations provided, it does not disclose details like default time range, handling of unknown user IDs, or whether the operation is read-only, leaving some behavioral context to inference.

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?

A single front-loaded sentence with no filler. It communicates the action, resource, output categories, and an optional modifier while remaining compact and scannable.

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 essential action and scope, and the schema covers all parameters. However, with no annotations and no output schema, the agent is left without explicit detail on return structure, default behavior when no window is provided, or how this tool relates to the many sibling statsfm statistics tools.

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 explains user_id, after, before, and response_format. The description adds a high-level framing around aggregation and windowing but does not materially deepen parameter-level understanding.

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 uses a specific verb ('Aggregate') and resource ('listening stats') and lists concrete output categories: totals, percentiles, catalog cardinality. It is clear about the user-level scope and optional windowing, though it does not explicitly differentiate itself from sibling stats tools like statsfm_track_stats or statsfm_artist_stats.

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 when to use it: when you need aggregated listening statistics for a user, optionally over a time window. However, it names no alternatives and gives no exclusion criteria, leaving the agent to infer the distinction from sibling names.

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