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

Annotations already indicate read-only, open-world, idempotent behavior. The description adds meaningful behavioral context: it routes to one of 5,721 tools, fills arguments, returns structured answers with stable pipeworx:// citation URIs, works on every tier, and is a single fast call. 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 long but every section earns its place: prioritized usage, coverage scope, example queries, default position, and escalation paths. It is front-loaded with the most critical instruction and avoids vague filler.

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 no output schema, the description adequately explains the return characteristics: structured answer with citation URIs. It also covers when to use, how to phrase input, what domains are included, and when to choose alternatives. Nothing essential is missing for correct invocation.

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% and the schema already documents the natural-language question parameter and aliases. The description adds value by giving trigger phrases and concrete examples of acceptable questions, which helps the agent understand the expected input form beyond the raw 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 clearly identifies the tool as a router that sends factual questions to the appropriate source from a large set of verified tools and returns structured answers. It distinguishes itself from sibling tools like ask_pipeworx_grounded and deep_research, and explicitly positions itself as the default entry point.

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?

Provides explicit when-to-use guidance: prefer over web search for factual/current/historical data, use for trigger phrases like 'what is' or 'look up', and start here for most questions. It also names specific alternatives and the conditions under which to step up to them, such as ask_pipeworx_grounded for hallucination-resistant answers and deep_research for broad multi-part questions.

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