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

Despite annotations already marking this as read-only, idempotent, non-destructive, and open-world, the description adds substantial behavioral context: account/paid-plan requirements, parallel decomposition across 5,798 tools, the findings-packet format with gaps[] and contradictions[], citation fetchability guarantees, semantic excerpting, and expected latency. This tells the agent exactly what will happen and what to rely on in the result.

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 contains a large repeated block — the 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... For a single lookup use ask_pipeworx instead' segment appears multiple times verbatim. While the content is informative, the duplication substantially harms conciseness and structure; a well-organized description would state this material once.

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 tool with no output schema, the description is remarkably complete: it covers auth requirements, sibling alternatives, depth-mode behavior, return-packet contents, citation resolvability, contradiction handling, gap reporting, excerpting behavior, and timing. An agent has everything it needs to determine whether to call the tool, how to set parameters, and what to expect in the response.

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 schema already covers both parameters thoroughly (100% schema description coverage), so the baseline is 3. The description adds value by explaining that 'thorough' requires a paid plan, that 'standard' is the default, and that multi-part/broad questions are appropriate for the 'question' parameter. It doesn't deeply expand on types or formats, but the cost constraint is genuinely decision-relevant and not present in 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 names a specific verb and resource — 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' — and immediately differentiates the tool from open-web search and from ask_pipeworx. It clearly communicates the tool's unique decomposition-and-parallel-routing behavior, so an agent can tell what the tool does and how it differs 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?

The description gives explicit routing guidance: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup use ask_pipeworx instead.' It also states when deep_research is best ('broad/multi-part questions over structured data') and provides examples. It even distinguishes depth tiers by cost and iteration behavior, leaving little ambiguity about when this tool should be selected.

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