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

Even though annotations already declare readOnly/hints, the description adds valuable context: results are 'drawn from the live catalog of thousands of tools' and include 'the exact tool + argument shape.' This reveals the dynamic output structure and source, going beyond the 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 long but every sentence earns its place—it lists example user queries, explains the output, names categories, and gives call variants. It is well-structured and front-loaded with the user's perspective, making it easy to scan.

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?

With a single optional parameter and no output schema, the description fully covers behavior: what it returns, when to use it, how to focus, and which meta-tools to learn. It is complete for an onboarding 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 schema already documents `topic` with the full list of valid areas and the omit behavior (100% coverage). The description merely repeats the same examples ('finance', 'pharma', 'betting') without adding new meaning, so it stays at the baseline 3.

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 it is 'the onboarding entry point for an agent that just connected and wants to know what is worth asking.' It specifies the exact output (category-bucketed example questions with tool + argument shape) and differentiates itself from siblings like discover_tools by positioning itself as the FIRST tool to use.

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 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.' It also explains the two calling modes (no args vs topic) and references sibling tools, providing clear when-to-use and how-to-use guidance.

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