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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds context by noting results are 'drawn from the live catalog of thousands of tools' (consistent with openWorldHint) and describes the return structure (category-bucketed questions with tool + argument shape). It does not contradict annotations and provides useful behavioral context beyond the structured data.

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 front-loaded with example queries, then a concise explanation of purpose and output. Despite being long, every sentence contributes: the query examples, the category list, the tool/argument detail, and the usage guidance. It is well-organized and not redundant with the schema or annotations.

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 read-only onboarding tool with no output schema, the description covers what it returns (category-bucketed example questions with tool/argument shapes), the optional topic parameter, and when to use it. It is complete for an agent to understand the tool's purpose, usage, and output without additional documentation.

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% for the single parameter, providing baseline 3. The description adds value by elaborating that omitting topic gives a 'cross-category spread' and listing example focus areas (finance, pharma, betting, etc.), which helps understand the parameter's effect on the output. This goes beyond the schema's terse description.

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 for an agent wanting to know what Pipeworx can do, listing example queries like 'What can I ask Pipeworx?' and describing the return of category-bucketed example questions. It distinguishes from siblings by explicitly saying to use this FIRST before other 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?

Explicitly says 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).' It also explains how to use the optional topic parameter to focus, and that omitting it gives a full spread, covering both when and how to use it.

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