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

Annotations indicate readOnly, openWorld, idempotent, and non-destructive hints. The description adds value by specifying that calling with no arguments gives a full spread and that the topic parameter focuses results. It also describes the return format, which is not present in 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 somewhat lengthy but well-structured with example queries upfront. Every sentence provides useful information, such as the list of categories and the guidance on tool usage. Minor redundancy could be trimmed, but overall it is efficient.

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 the tool's simplicity (one optional param, no output schema), the description covers all necessary aspects: purpose, usage context, parameter behavior, and return format. It is sufficiently complete for an agent to correctly select and invoke the 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?

Schema coverage is 100% with one optional parameter. The description adds meaning beyond the schema by listing example values ('finance', 'pharma', etc.) and explaining the effect of omitting the parameter. This helps the agent understand usage better than the schema alone.

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 that the tool returns category-bucketed example questions with associated tools and argument shapes. It uses specific verbs ('returns') and resources ('example questions'). It distinguishes itself from siblings like ask_pipeworx and discover_tools by being the onboarding entry point.

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 explicitly advises 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' This provides clear guidance on when to use the tool, though it does not explicitly state when not to use it.

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