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

Annotations already declare readOnly/openWorld/idempotent behavior, and the description adds much more: account and paid-plan requirements, the findings packet shape, explicit gaps[] when data is unavailable, never-invented evidence, contradictions[] for deeper depths, citation URI semantics, semantic excerpting, and expected latency. None of this contradicts 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 almost every sentence carries essential behavioral or routing information, and it is front-loaded with the account requirement and alternative tool. It loses a point for mild redundancy — ask_pipeworx is mentioned twice for the same routing guidance — and for dense run-on sentences that make parsing harder than necessary.

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 prerequisites, return format, evidence fields, citation fetchability, gap behavior, contradiction scanning, handling of large records, and latency. An agent can decide when to call it, invoke it, and interpret its results 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, so the baseline is 3. The description adds value beyond the schema by noting that the "thorough" depth requires a paid plan, that "standard" and "thorough" add gap-recovery and contradiction passes, and that the question can be broad or multi-part natural language.

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 1540 structured data sources in one call. It explains the mechanism (decomposes into facets, routes to 5,908 tools in parallel) and explicitly distinguishes itself from open-web search and from the single-lookup sibling 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 gives explicit selection rules: use deep_research for broad/multi-part questions over structured data, use ask_pipeworx instead for a single lookup or when not signed in. It names the alternative and the exact conditions that route to it, leaving little to inference.

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