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

Adds real context beyond annotations: an internal permission-filtered tool loop, answers that cite the tools used, a prerequisite (configured AI provider), and a side effect the annotations don't capture (consumes provider credits). The notable gap is that destructiveHint=true is never explained – nothing warns the agent that the internal loop may perform writes or that repeated calls are non-idempotent and billed.

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 dense sentences (~50 words) with zero filler, leading with the action and following with mechanism, return shape, and cost prerequisites. Every clause carries information an agent cannot get from the schema.

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?

With no output schema, the description does the necessary work by stating the return value (a written answer citing tools used). Missing pieces for a destructive, open-world, credit-consuming tool are the failure mode when no AI provider is configured and any warning about mutating internal calls.

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?

Schema coverage is 67% and the schema already documents both `app` (id or orgSlug/appSlug) and `conversationId`. The description only adds the single-application scoping constraint on the question; it says nothing about question length, phrasing, or what happens if conversationId refers to a different app.

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?

Specific verb+resource: asks a natural-language question to a SaaS Pro assistant, scoped to one application. It implicitly distinguishes itself from the structured-data siblings (get_metric_series, list_events, etc.) by describing an agentic NL layer, though it never names an alternative explicitly.

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?

Usage is only implied: an agent can infer this is for open-ended NL questions rather than precise data lookups, and the 'about one application' clue implies multi-app questions need multiple calls. There is no explicit when-to-use/when-not guidance relative to the many sibling query tools.

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