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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds that it returns 'category-bucketed example questions (company financials, drugs & clinical trials, etc.) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools.' This provides detailed behavioral context beyond 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 slightly long but front-loaded with natural language queries, then clearly explains the tool's function and output. Each sentence adds value, though a minor trim could improve conciseness without losing content.

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 fully explains what the tool returns (categorized example questions with tool calls) and mentions its role in learning meta-tools. It covers all necessary context 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?

Schema coverage is 100% with one parameter (topic) described. The description adds example values (finance, pharma, etc.) and clarifies that omitting the parameter gives a cross-category spread, enhancing the schema's meaning.

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 starts with common user queries and clearly states it is the onboarding entry point that returns category-bucketed example questions. It distinguishes itself from siblings like ask_pipeworx and entity_profile by specifying its role in helping users discover capabilities and tool usage.

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 says '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 strong when-to-use guidance. It also mentions optional topic filtering but does not explicitly state when not to use it or list alternatives, though the context is clear.

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