io.github.AIops-tools/ceph-aiops

pool_df

Read-only

Retrieve per-pool usage metrics from a Ceph cluster, including used/available bytes, percentage, object counts, and usable capacity.

Instructions

[READ] Per-pool usage: used/avail bytes, percent, objects, usable capacity.

Returns {"pools": [...], "returned": N, "error": str | None}. A non-null "error" means the query failed — that is NOT the same as a cluster with no pools, so do not report it as "nothing to worry about".

Args: target: Ceph target name from config; omit for the default.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pool_df"
  }
}

Input Schema

Name	Required	Description	Default
`target`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 12, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=true), but the description goes further by disclosing the return shape ({"pools", "returned", "error"}) with no output schema present, and by warning that a non-null error is a failed query rather than an empty cluster. That interpretation caveat is exactly the kind of context an agent cannot get from structured fields. Auth requirements and result limits implied by "returned" are not explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the [READ] tag and the payload summary, then the return contract, then the caveat, then the arg. Every sentence carries information; no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-param read tool with no output schema, the description supplies the return shape, the error semantics, and the parameter meaning, which is close to sufficient. The one loose end is that "returned": N implies a cap or truncation that is never explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% – the property is only titled "Target" with a null default – so the description must compensate, and it does: it explains target is a Ceph target name from config and that omitting it selects the default. That is a meaningful addition over the schema, though it doesn't say where the name comes from or how to discover valid values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and the exact data returned (used/avail bytes, percent, objects, usable capacity), so an agent can tell this is a capacity/usage report rather than a listing. It never names sibling pool_ls or capacity_forecast, so differentiation must be inferred from the field list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the purpose (reach for this when you need per-pool capacity numbers), but there is no explicit when-to-use statement, no exclusion, and no routing to pool_ls or capacity_forecast. The only guidance given is on the parameter default.

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