capacity_forecast

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

In the absence of annotations, the description fully discloses behavior: it is a pure arithmetic read projection, no clock read, no side effects. The [READ] prefix and explicit mention of deterministic arithmetic ensure transparency.

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, with a clear first sentence summarizing purpose, followed by usage conditions and an Args section. Every sentence 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?

Although there is no output schema, the description hints at the output: capacity usage and daysToNearfull, with insufficient-data when growth is missing. It could be more explicit about the response format, but it is sufficient for a simple tool with two optional parameters.

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. It explains the effect of each parameter: daily_growth_bytes for projection vs. usage-only, target for Ceph config. This adds significant meaning beyond the schema's null defaults.

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 explicitly states it is a READ tool for capacity usage and a deterministic days-to-nearfull projection. It clearly distinguishes itself from sibling tools like osd_df (current usage) and cluster_health (overall health) by focusing on forecast and threshold definition.

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 explains when to use the daily_growth_bytes parameter: pass it for projection, omit for usage-only view. It defines nearfull as 85% and notes that without growth data, the forecast returns insufficient-data. However, it does not explicitly compare to alternatives like pool_df or osd_df, but the unique functionality makes the usage clear enough.

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