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

Annotations already disclose read-only, open-world, idempotent, and non-destructive nature. Description adds that the tool returns exact tool+argument shapes and is the onboarding entry point, which provides useful behavioral context 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?

Description is appropriately sized for a meta-tool, with key phrases front-loaded in quotes. It lists example queries, describes output structure, and provides usage guidance without unnecessary words. Slightly verbose but every sentence earns its place.

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 fully explains what the tool returns: category-bucketed example questions with exact tool+argument shapes. This is sufficient for an onboarding tool, leaving no ambiguity about its function.

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 already describes the optional 'topic' parameter with allowed values. Description reinforces this with examples like 'finance', 'pharma', and explains the behavioral difference: omitting gives a full spread, specifying a topic focuses results. This adds meaningful 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?

Description uses specific verbs ('returns', 'call') and clearly states the resource: category-bucketed example questions for onboarding. It distinguishes from siblings like ask_pipeworx and discover_tools by framing it as the first step for a new agent.

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 when to use: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' Also provides context for optional topic filtering and implies when not to use (if already familiar with tool capabilities).

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