malcolm_field_values

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

Despite no annotations, the description explains that the tool returns distinct values with document counts, and provides examples of output format. It doesn't disclose potential performance implications or destructive behavior (not applicable), but the transparency is adequate.

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 concise yet comprehensive: a one-line purpose, a usage guideline, multiple examples, and a parameter list. Every sentence adds value, and the structure is easy to parse.

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 presence of an output schema (not shown) and the examples, the description sufficiently covers return formats. It lacks details on nested filter structure but overall provides a complete picture for agent usage.

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?

With 0% schema description coverage, the description compensates fully by explaining all five parameters in an 'Args' section, including the meaning of 'field', 'limit', 'filters' (optional JSON), and time range parameters. Examples illustrate typical field values.

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 ('List') and resource ('distinct values for a field with document counts'), clearly stating the tool's purpose. Examples further clarify and distinguish it from siblings like malcolm_field_search (which searches for field presence) and arkime_unique (which returns unique values without counts).

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?

Explicitly advises using this tool BEFORE filtering to prevent value hallucination. While it doesn't name alternative tools for when not to use it, the guidance is clear and actionable.

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