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

Beyond the readOnly/idempotent annotations, the description discloses account requirements, output packet structure (verbatim evidence, confidence, source, fetched_at, pipeworx:// citations), explicit gaps[], 'never invented' behavior, contradictions[] on standard/thorough, semantic excerpting, and latency expectations. This is rich, non-contradictory behavioral detail.

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 dense and front-loaded with critical access information and the key differentiation from ask_pipeworx. There is minor redundancy with schema depth descriptions, but overall each sentence earns its place and the structure flows from usage constraints to behavior to timing.

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 inputs, expected latency, return packet contents, gap behavior, citation stability, contradictions, and account constraints. It is sufficiently complete for an agent to understand what will happen and what it will receive.

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%, so the baseline is 3, but the description adds meaning beyond the schema by explaining depth tiers in practical terms (quick=3 single hop, standard=3 default, thorough=6 paid), reiterating that question can be multi-part natural language, and tying depth choices to paid-plan constraints. This goes beyond the schema's field descriptions.

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' and explains the internal mechanism of decomposition and parallel routing. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can clearly differentiate it from sibling tools.

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: 'Best for broad/multi-part questions over structured data' with concrete examples. It also provides exclusions and alternatives: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup use ask_pipeworx instead.' This fully routes the agent between deep_research and ask_pipeworx.

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