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

Annotations already declare read-only, idempotent, and non-destructive. The description adds context about what the tool actually does: it returns category-bucketed example questions sourced from a live catalog, and that each example includes the exact tool and argument shape. This is valuable behavioral detail 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 a single dense paragraph that front-loads example queries and efficiently packs in the tool's purpose, output format, call patterns, and when to use it. Every sentence contributes value; no filler or redundancy.

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?

For a tool with one optional parameter and no output schema, the description fully explains the return value (category-bucketed examples with tool+argument shapes), the calling convention (no args or with topic), and the recommended usage scenario. It also lists the categories. This makes the tool self-sufficient.

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% (the `topic` parameter has a description), but the tool description adds meaningful context: it lists concrete examples ('finance', 'pharma', 'betting') and explains that omitting the argument yields a full spread. This enriches the schema's enum-like 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: 'the onboarding entry point' that 'Returns category-bucketed example questions' with each tool and argument shape. It lists specific categories (company financials, drugs, etc.) and distinguishes itself from siblings like ask_pipeworx by explaining it teaches how to call those meta-tools.

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?

Explicit usage guidance is provided: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and 'to learn how to call the meta-tools'. It also explains call variations (no arguments vs. with topic) and gives examples of topic values. This clearly positions it relative to alternatives.

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