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

Beyond the readOnly/openWorld/idempotent annotations, it discloses the output shape (findings packet with evidence, confidence, source, fetched_at, citation), the gaps[] and contradictions[] behavior, no-fabrication policy, graceful failure, latency ranges, and paid-tier restrictions. This is rich behavioral context that annotations did not provide, and it does not contradict them.

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 significantly bloated and repetitive: the account/paid-plan warning and 'use ask_pipeworx instead' appear multiple times, and the findings-packet description is stated more than once. It is front-loaded and useful, but it would benefit from trimming to a single non-redundant statement.

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?

With no output schema present, the description compensates by detailing the return packet, gaps and contradictions, failure behavior, latency, prerequisites, and alternatives. An agent has enough information to select and invoke the tool correctly across account states, depths, and question types.

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?

Although the schema already covers both parameters at 100%, the description adds substantial meaning: it says standard is the default, explains the tradeoffs of quick versus thorough, flags the paid requirement for thorough, and gives concrete question-formulation advice such as including tickers/CIKs, date context, source names, and chain/trace language. This materially improves correct invocation.

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-resource: grounded multi-source research across Pipeworx's 1,506 structured data sources in one call, decomposing questions into facets and routing them to tools in parallel. It also explicitly distinguishes itself from open-web search and names the tool it is not (ask_pipeworx), making sibling differentiation clear.

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 criteria (broad/multi-part questions over structured data) and when-not-to-use criteria (single lookups), and names alternatives: ask_pipeworx, entity_profile, compare_entities, and search_within. It even handles the signed-out case by routing the agent to ask_pipeworx.

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