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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context: it returns category-bucketed example questions from a live catalog, each with tool and argument shape, and explains how the optional topic parameter changes the result (full spread vs. focused). No contradiction with 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 front-loads the core purpose with example queries, then details return format, parameter behavior, and usage guidance. The structure uses em-dashes and lists effectively, making it scannable and complete without 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?

With no output schema, the description carries the burden of explaining return values, which it does (category-bucketed example questions with tool + argument shape). It also covers no-argument vs. topic usage and ties into the broader tool ecosystem. For a simple 1-parameter tool, this is complete.

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% and the optional 'topic' parameter already includes a description listing valid values and the omit behavior ('Omit for a cross-category spread'). The description adds example values (finance, pharma, betting) and reinforces the focus effect, but does not provide substantial meaning beyond the schema. Baseline 3 applies.

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 is the onboarding entry point for an agent that just connected, returning category-bucketed example questions with exact tool and argument shapes. It distinguishes itself from siblings like discover_tools and ask_pipeworx by explicitly positioning itself as the 'FIRST' step to learn what Pipeworx can do.

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' and mentions it helps learn how to call meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.). This provides clear when-to-use context and names alternatives, satisfying the usage guidance dimension fully.

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