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

The description goes well beyond annotations, detailing the internal behavior: question decomposition, routing to 5,743 tools in parallel, a findings packet with evidence/confidence/source/fetched_at citations, explicit gaps[] for unanswered facets, never-invented answers, contradictions[] for deeper tiers, semantic excerpting, and expected latency. No annotation contradiction is present.

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 and dense, but it is information-rich rather than padded, with the key routing advice front-loaded. Some parenthetical chains could be tightened, but each clause adds a distinct operational detail.

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 covers auth requirements, alternative tool routing, input suitability, output shape, gap handling, citation resolvability, result reliability, and timing. For a complex research tool, this is complete enough for an agent to select and invoke it 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?

Schema coverage is 100% and both parameters are already described in the schema. The description adds meaningful context on top: the 'thorough' depth requires a paid plan, what each depth tier costs in time, and which tiers include the contradictions[] scan. This is more than the schema alone provides.

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 states a specific verb and resource: grounded multi-source research across Pipeworx's 1500 structured data sources in one call, with parallel decomposition and routing. It explicitly contrasts with open-web search and names ask_pipeworx for single lookups, so it is clearly distinguished 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 gives explicit when-to-use guidance: use deep_research for broad/multi-part structured-data questions, and use ask_pipeworx for a single lookup. It also provides a catch-condition: if not signed in, use ask_pipeworx instead because it works on every tier.

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