system_df

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

No annotations are provided, so the description carries the burden. It adds that the output is 'already compact — shipped raw,' hinting at minimal formatting. However, it does not disclose whether the operation is read-only, requires any special permissions, or has any side effects.

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 two short sentences with no wasted words. The purpose is front-loaded, and the additional note about output compactness adds value without redundancy.

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?

For a zero-parameter tool with no output schema, the description adequately explains what the tool returns. It mentions the categories (containers, images, volumes, build cache) and the output nature. However, it could be slightly more complete by explicitly stating it provides read-only information about disk 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?

The input schema is empty (0 parameters, 100% coverage). With no parameters, the description does not need to add parameter semantics. The baseline of 4 applies because the schema already covers all parameter information.

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 it returns Docker disk usage with a breakdown by containers, images, volumes, and build cache. The verb 'return' and specific resource 'Docker disk usage' make the purpose unambiguous, and it distinguishes from sibling tools like system_prune.

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?

No guidance on when to use this tool vs alternatives. While the purpose is clear, there is no discussion of appropriate contexts, prerequisites, or comparisons to sibling tools such as system_prune or volume_query.

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