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

Annotations already mark it readOnly, openWorld, idempotent, and non-destructive. The description adds substantial behavioral detail beyond that: account and paid-plan requirements, parallel decomposition, gap reporting (never invented findings), fetchable citations, contradiction scanning, semantic excerpting, and expected latency. No contradiction with 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 information-dense and front-loaded with the most critical usage constraint (account required; fallback to ask_pipeworx). Each section adds operational value, though some depth-enum detail overlaps with the schema and could be trimmed slightly.

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, the description carries the full burden of explaining return values, and it does: findings packet contents, verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], hop field, and timing. It also covers prerequisites, exclusions, alternatives, and multi-step behavior. Nothing critical 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% and the schema already documents both parameters, so the baseline is 3. The description adds value by giving concrete user-facing examples, clarifying that natural-language broad questions are valid, and elaborating the depth values with behavioral consequences like gap recovery and time expectations.

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 clearly states a specific verb and resource: grounded multi-source research across Pipeworx's 1,517 structured data sources in one call. It explicitly distinguishes itself from open-web search and names a sibling alternative (ask_pipeworx) for single lookups, so an agent can select it accurately.

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 when-to-use guidance: best for broad, multi-part questions over structured data, and tells the agent to use ask_pipeworx for single lookups or when not signed in. It also clarifies that it is NOT open-web search, which prevents misrouting.

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