pool_df

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

With no annotations, the description carries the full behavioral disclosure burden and does well by labeling the tool as [READ] and explaining the error semantics in detail. The warning that a non-null error means query failure rather than 'no pools' is valuable because it prevents a common misinterpretation. It stops short of mentioning permissions or other operational constraints, but for a read-only query this is largely sufficient.

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 compact and front-loaded: a one-line purpose, then return format, then a crucial error-handling note, then the single parameter. Every sentence earns its place, and the error clarification is high-value rather than filler.

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 simple one-parameter read tool with no output schema and no annotations, the description covers the return structure, error behavior, and parameter meaning. It could elaborate on what 'returned' represents or what the pool objects contain, but the essentials for correct invocation and interpretation are present.

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 schema only provides the parameter title 'Target' with 0% description coverage, so the description must add meaning. The line 'Ceph target name from config; omit for the default' explains the source and optionality of the parameter, which is helpful. It still leaves the actual default target unspecified, but this is enough for correct invocation in most contexts.

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 the tool reads per-pool usage metrics (bytes, percent, objects, capacity), which is a specific and useful purpose. It does not explicitly name siblings like osd_df or pool_ls to differentiate them, though 'per-pool usage' is distinct enough to be reasonably clear.

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 provides no explicit guidance on when to choose this tool over alternatives such as osd_df or pool_ls. There is no mention of use cases, exclusions, or sibling routing, so an agent must infer when this tool is appropriate solely from the stated purpose.

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