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

Annotations already flag read-only/idempotent behavior; the description adds substantial context: account and paid-tier requirements, parallel routing to 5,798 tools, findings packet contents, gap handling with never-invented findings, citation fetchability, latency expectations, and semantic excerpting of large records. There is no contradiction with the 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, front-loading the account requirement and core scope before process details. Some repetition exists, but every major behavioral fact earns its place and the structure flows logically from scope to process to output to latency.

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 complex research tool with no output schema, the description covers auth, pricing, scope, process, return packet, gaps, citations, latency, depth behavior, and limits. An agent has enough information to select and invoke this tool correctly without needing external 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?

The input schema already documents both parameters at 100% coverage, including detailed enum semantics for depth. The description adds meaningful layer: 'thorough' requires a paid plan, depth controls gap-recovery and contradiction passes, and the question parameter is explicitly natural-language and multi-part friendly.

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 names a specific operation—decomposing multi-part questions and running parallel grounded research across Pipeworx's 1517 structured data sources—and explicitly contrasts it with open-web search and single-lookup tools. It is clearly distinguishable from sibling 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?

It states the best-use case (broad/multi-part questions over structured data) and gives explicit exclusions: for single lookups use ask_pipeworx, and if not signed in use ask_pipeworx. This tells the agent both when to select this tool and when to prefer an alternative.

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