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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds meaningful context beyond these: it returns category-bucketed example questions with tool+argument shapes drawn from a live catalog of thousands of tools. It also explains that calling with no arguments yields the full spread while passing a topic focuses results, which is behavioral detail not covered by 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 efficiently structured with a clear lead-in of example user queries, followed by the tool's purpose, return value structure, calling convention, and explicit usage priority. Every sentence carries essential information, and the front-loaded examples make it immediately apparent what the tool does. No wasted words.

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 the tool has only one optional parameter and no output schema, the description is fully complete. It explains the output content (category-bucketed example questions with tool+argument shapes), the source (live catalog), the no-argument versus topic-focused modes, and when to use it first. It also proactively references meta-tools that the agent should learn, covering the full context an agent needs for onboarding.

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 covers the `topic` parameter with a description and valid values, so baseline is 3. The description adds value by giving concrete examples ('finance', 'pharma', 'betting') and explaining the contrast between full spread (no arguments) and focused results (with topic), which helps the agent decide how to invoke the tool. It doesn't reach 5 because the schema already lists all valid topics and the description doesn't introduce additional parameter-related semantics.

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 this is the onboarding entry point for agents wanting to know what they can ask Pipeworx, returning category-bucketed example questions with exact tool and argument shapes. It distinguishes itself from siblings by explicitly saying 'Use this FIRST' and by referencing meta-tools like ask_pipeworx, entity_profile, and compare_entities, making its unique role clear.

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 gives explicit when-to-use guidance: '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 clarifies when to omit or pass the `topic` parameter, and contrasts with alternatives by naming the meta-tools it teaches.

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