topic_data

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

With no annotations provided, the description carries the full behavioral burden. It is clearly a read/compute operation and it discloses the two output modes (stats vs. downsampled table), but it says nothing about whether log source selection or large windows affect cost, nor about any pagination or truncation behavior.

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 compact sentence, front-loaded with the computed outputs followed by the scope and optional mode. No filler, though 'optionally with a downsampled table' is slightly ambiguous about what 'table' means.

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?

An output schema exists, so return-value explanation is not required, and the 100%-covered input schema documents all six parameters including the log source. The description is therefore adequate for the core call but leaves usage routing and cost/permission behavior unstated for a tool with several siblings.

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 baseline is 3. The description maps roughly to t_from/t_to ('over a time window') and to the points parameter ('downsampled table'), adding marginal meaning beyond the schema but no syntax or format detail the schema lacks.

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 names a specific computation (min/mean/max/first/last) applied to a specific resource (a topic's fields) over a defined scope (a time window), which is far more informative than a tautology. It doesn't explicitly differentiate itself from siblings like plot_series or list_topics, so it stops short of a 5.

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?

There is no when-to-use or when-not-to-use guidance. An agent must infer that this tool is for statistics while plot_series is for visualization, and the 'optionally with a downsampled table' phrase hints at an alternative output mode without stating when to prefer it.

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