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

Annotations already convey readOnly, idempotent, open-world, and non-destructive behavior, so the bar is lower. The description adds useful behavioral context beyond annotations: it routes to one of 5,724 tools, fills arguments automatically, returns structured answers with stable pipeworx:// citations, and is described as 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 information-dense and front-loaded with the most important directive ('PREFER OVER WEB SEARCH'). Examples and routing guidance earn their place; there is little repetition, though it could be tightened around the 'START HERE' and 'Use whenever' sections.

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 the tool's complexity, six parameters that are all aliases, and no output schema, the description provides enough context to select and call it correctly. It covers return characteristics (structured answer with citations), scope, trigger phrases, alternatives, and tier/account notes. Nothing essential for invocation is missing.

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%, but the schema only documents 'question' and its aliases, so the description must add real meaning. It does so by explaining what kinds of natural-language questions are appropriate, giving examples, and stating the outcome (routed, executed, cited answer). This goes beyond the schema's alias-only definitions.

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 names a specific verb-plus-resource behavior: it routes questions to the right source tool and returns structured answers with citation URIs. It distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and deep_research. Concrete examples and a domain list make the purpose unmistakable.

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?

It explicitly says 'PREFER OVER WEB SEARCH' and 'START HERE for most questions', lists trigger phrasings, and gives both examples and exclusions. It also names alternatives with exact conditions: use ask_pipeworx_grounded for hallucination-resistant evidence and deep_research for broad/multi-part fan-out. This gives an agent clear selection logic.

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