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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds behavioral context beyond these: it returns live catalog data with example questions and tool shapes, and that topic filters the output. It does not contradict annotations and provides useful operational detail (what the response contains, how arguments affect it).

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 long but packed with useful information: sample user queries, return format, parameter behavior, and usage positioning. It is front-loaded with user intents and remains structured. It could trim the redundant example queries slightly, but every sentence adds clarity.

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?

The tool is simple (one optional parameter, no output schema), and the description covers its purpose, usage, parameter semantics, and relationship to sibling meta-tools. It explains what the user gets (category-bucketed questions with tool shapes) and when to use it, making the tool fully understandable without external references.

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 input schema already documents the `topic` parameter with allowed values (100% coverage). The description adds semantic value by explaining that omitting `topic` gives a cross-category spread, while passing it focuses results, and gives concrete examples like 'finance', 'pharma', 'betting'. This goes beyond the schema's value list.

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 states the tool's purpose: it's the onboarding entry point for an agent that wants to know what to ask Pipeworx, returning category-bucketed example questions with the exact tool and argument shape for each. It distinguishes itself from siblings by mentioning the meta-tools (ask_pipeworx, entity_profile, compare_entities) and positioning itself as the 'FIRST' step.

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 gives explicit usage guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' It also explains the optional `topic` parameter, telling the user to omit it for a full spread or pass a specific focus area.

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