graph_query

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

Beyond the annotations (readOnlyHint, idempotentHint), it specifies that KQL write/external access operators are blocked and that scope is validated against Azure format. It also confirms read-only behavior, adding useful behavioral constraints not present in the schema. No contradiction with annotations.

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?

Three short sentences, front-loaded with the main purpose, followed by the two most important behavioral constraints. Every sentence adds value and there is no verbose 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 tool with four parameters, no output schema, and a required capability_id, the description leaves the central parameter undefined and provides no usage scenario or relationship to sibling graph_* tools. The safety and scope details are good, but a caller cannot confidently construct a valid call.

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 carries the burden but only explains scope validation. It does not clarify the meaning of capability_id, which is required, nor query and limit behavior. This is insufficient for an agent to correctly populate parameters.

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 states a clear action ('Executa consulta parametrizada') and a target ('fontes que aceitam query, ex.: Azure Resource Graph'), establishing what the tool does. It does not fully differentiate it from the many graph_* siblings, but conveys that it runs a KQL query rather than a fixed list/get operation.

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?

It implies use for query-capable sources like Azure Resource Graph and notes read-only constraints, but it never explicitly states when to prefer graph_query over graph_list, graph_get, or other siblings. There are no exclusion conditions or alternatives named.

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