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

Annotations already provide the safety profile (readOnly, idempotent, non-destructive). The description adds valuable context about the live catalog source, category-bucketed output, and the ability to call with no arguments or a topic focus. 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?

The description is longer than average but front-loaded with common user phrasings and well-organized into purpose, output details, and usage. Every clause adds useful context; the only minor issue is a slightly dense list of categories and meta-tools that could be trimmed.

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?

Even without an output schema, the description explains what is returned (category-bucketed example questions with exact tool + argument shape), how to invoke it, and when to use it. This is complete for an onboarding/discovery tool.

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 single optional `topic` parameter is fully described in the schema with an enum-like list and the default 'omit for cross-category spread'. The description adds examples and clarifies the focus behavior, but largely mirrors the schema, so it does not significantly exceed the baseline for high schema coverage.

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 identifies this as the onboarding entry point for discovering what to ask Pipeworx, and explicitly states it returns category-bucketed example questions with the exact tool and argument shape. It distinguishes itself from sibling research/execution tools by focusing on 'what can I ask' rather than performing a task.

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 gives explicit usage direction: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and explains how to use it for learning meta-tools. It also mentions alternatives by name (ask_pipeworx, entity_profile, compare_entities) and provides a clear fallback scenario.

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