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

Annotations already declare read-only, open-world, and idempotent hints. The description adds valuable context about the response content (category-bucketed examples, exact tool and argument shape, live catalog) and how the topic parameter changes behavior. This goes beyond the annotations without contradicting them.

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 longer than typical but every segment earns its place: example queries, category list, tool-shape detail, and usage instructions. It is front-loaded with example queries and structured with em-dashes. Slightly verbose but not wasteful.

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 format and purpose. It covers both invocation modes (no args vs topic) and the tool's role in onboarding, making it complete for an agent to use correctly.

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 a clear description of the topic parameter including allowed values and default behavior. The description adds example values ('finance', 'pharma', 'betting') and explains the focus effect, providing marginal extra value.

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 that returns category-bucketed example questions with exact tool and argument shapes. It is distinct from siblings like discover_tools or ask_pipeworx, and uses specific verbs like 'returns example questions'.

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?

Explicitly instructs 'Use this FIRST when you do not yet know what Pipeworx can do for you' and provides context for both no-argument and topic-filtered calls. It also names meta-tools to learn about, giving clear cross-references.

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