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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds valuable context: it is an onboarding entry point, returns examples with exact tool+argument shape drawn from live catalog, and explains topic filtering. 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 relatively long but front-loaded with key phrases and organized with lists. It could be slightly more concise, but every sentence contributes useful information 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?

Despite lacking an output schema, the description adequately explains the return format (category-bucketed example questions with tool+argument shape). It covers purpose, usage, parameter behavior, and context, making it complete for the tool's role as an onboarding guide.

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 description coverage is 100% with a basic description for the `topic` parameter. The tool description adds meaningful detail: lists example topic values (finance, pharma, etc.) and explains behavior when omitted (full spread) or provided (focus). This adds semantic value beyond the schema.

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 explicitly states the tool returns category-bucketed example questions for onboarding and discovery. It distinguishes itself from siblings by specifying it should be used first when the agent doesn't know what Pipeworx can do, and mentions meta-tools like ask_pipeworx.

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 clear when-to-use instructions: '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 describes calling with no arguments for full spread or with a topic to focus.

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