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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds behavioral context by explaining the output format (category-bucketed examples with exact tool+argument shapes from the live catalog) and the optional `topic` filter, which is useful beyond what annotations convey.

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?

While longer than typical descriptions, every sentence earns its place: it lists example queries, enumerates categories, explains the tool+argument mapping, and gives usage guidance. The structure is front-loaded with the most common phrases, making it scannable and information-dense.

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 and a single optional parameter, the description fully covers what the tool returns (category-bucketed examples with tool+argument shapes), how to focus via `topic`, and when it should be called first. It also mentions the source (live catalog of tools), leaving no critical gaps for the agent.

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%, so the baseline is 3. The description goes beyond the schema by explaining the effect of passing `topic` (e.g., 'finance', 'pharma', 'betting') to focus and omitting it for a full spread. This practical guidance adds meaning to the parameter without redundancy.

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 uses a specific verb ('returns') and resource ('category-bucketed example questions') while also detailing that each example includes the exact tool and argument shape. It clearly differentiates from sibling tools like ask_pipeworx or discover_tools by positioning itself as the onboarding entry point for 'what can I ask'.

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 states 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' This provides clear when-to-use guidance and names the meta-tools (ask_pipeworx, entity_profile, compare_entities) as the next steps, covering both usage and alternatives.

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