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

The description goes well beyond the readOnly/openWorld/idempotent annotations: it discloses account/payment requirements, parallel decomposition behavior, the findings packet structure, explicit gaps[] for unanswered facets, the guarantee not to invent findings, contradictions[] for standard/thorough depths, semantic excerpting, and expected latency ranges. This is a rich, honest behavioral profile.

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 every sentence adds non-redundant information such as auth constraints, output shape, limitations, and latency. It would be improved by starting with the core purpose before the account gate, but it is structured enough that an agent can extract the essential usage guidance without difficulty.

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 tool with no output schema, the description thoroughly covers return values, evidence attributes, citations, gaps handling, contradiction detection, and time expectations. It also addresses prerequisites and alternatives. Nothing an agent needs to decide whether and how to call this tool is missing.

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 schema already documents both parameters clearly. The description adds meaningful extras not in the schema: thorough depth requires a paid plan, standard and thorough depths include contradictions[], and the overall behavioral meaning of depth levels is contextualized. This goes beyond a baseline schema-only score.

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 precise action ('Grounded multi-source research across Pipeworx's 1540 STRUCTURED data sources') and distinguishes it clearly from generic web search and from sibling tools. It also names what it is not ('NOT open-web search') and provides representative query examples, leaving no ambiguity about its function.

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?

Usage conditions are explicit: if not signed in, use ask_pipeworx instead; for a single lookup, use ask_pipeworx; best for broad/multi-part questions over structured data. It clearly names the alternative and the condition that selects it, which is exactly what an agent needs to route correctly.

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