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

Annotations already declare readOnly=true and openWorld=true, so the bar is lower. The description adds behavioral context by explaining what is returned (category-bucketed examples, live catalog, tool+argument shapes) and how to vary output via topic. It does not mention potential response size or rate limits, but these are not critical for a read-only informational tool.

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 moderately long but front-loaded with example user queries that make the purpose instantly understandable. Every sentence adds relevant detail (categories, tool shape, usage). It could be slightly tightened, but the structure is effective and not verbose.

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?

Given no output schema, the description adequately explains the return value: category-bucketed example questions with tool and argument shapes. It covers when to use, how to use, and what to expect. For a simple read-only tool with one optional parameter, this is complete enough. It does not go into exact response structure, but that is not necessary for onboarding context.

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 100% for the only parameter (topic), so baseline is 3. The description adds 'to focus' and examples like 'finance', 'pharma', 'betting', but these mostly repeat the schema's enum list. The only extra semantic is the 'Omit for a cross-category spread' guidance, which is already implied by the parameter being optional. No significant meaning beyond the schema.

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 returns category-bucketed example questions with exact tool and argument shapes for onboarding. It uses specific verbs ('Returns', 'Call') and distinguishes itself from siblings by positioning as the 'entry point' for learning what Pipeworx can do. It also lists concrete categories, making the scope unambiguous.

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?

Provides explicit when-to-use guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you'. It also differentiates from meta-tools (ask_pipeworx, entity_profile, compare_entities) and explains how to adjust the call (no args vs. topic). This is clear context beyond the schema.

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