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

The annotations already mark the tool as read-only, idempotent, open-world, and non-destructive. The description goes far beyond by adding account requirements, paid-tier constraints, latency expectations, citation/gap behavior, contradiction scanning, semantic excerpting of large records, and an explicit promise that findings are never invented. 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 every clause contributes either usage guidance, behavioral transparency, or output details. It front-loads the critical account requirement and alternative tool selection before diving into mechanics. A slight lack of paragraph separation and one run-on sentence prevent it from being perfectly scannable, but it is still effective.

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 having no output schema, the description thoroughly explains what the agent will receive: findings packets, verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[] for deeper modes, and excerpting behavior. Combined with the detailed schema and annotations, the agent has enough context to call and interpret the result correctly.

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?

Input schema coverage is 100%, so the schema already documents both parameters, including the depth enum values and their behavioral differences. The description adds some context like the need to sign in and the paid plan requirement for thorough, but this substantially overlaps with what the schema already states about depth being paid and about broad natural-language questions. It meets the baseline but adds little parameter-level meaning 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 clearly identifies the tool as a grounded multi-source research engine over Pipeworx's structured data sources, with a specific mechanism (decomposes into facets, routes to tools in parallel) and output shape (evidence, confidence, source, citation, gaps). It also distinguishes itself from open-web search and from single-lookup tools, so an agent can tell it apart from siblings.

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 states when to use deep_research (broad/multi-part questions over structured data) and when not to (single lookups use ask_pipeworx; unsigned users should use ask_pipeworx because it works on every tier). This gives clear selection criteria and an explicit alternative without leaving inference to the agent.

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