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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses account requirements, a paid plan for thorough, gaps[] with no invented answers, contradictions[] scans, resolvable citation URIs, semantic excerpting, and expected latency. These details materially shape invocation and result interpretation.

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; almost every sentence adds a distinct operational fact. It is front-loaded with the account requirement and routing to ask_pipeworx before the core mechanism. Slight redundancy around ask_pipeworx mentions keeps it from a 5.

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?

Despite having no output schema, the description fully explains the return packet: evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], and hop field. It also covers authentication, latency, facet decomposition, and multi-hop behavior, making the tool safely and correctly invocable.

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 schema covers both parameters fully, so the baseline is 3. The description adds value beyond the schema by explaining depth behavior in practice — standard adds gap recovery, thorough chases leads, contradiction scans occur, and thorough requires payment — and by giving concrete example questions for the question parameter.

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 action and resource: 'grounded multi-source research across Pipeworx's 1540 STRUCTURED data sources' in one call. It clearly distinguishes this from open-web search and from ask_pipeworx, explicitly naming the sibling alternative it is not.

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 guidance is explicit and actionable: use ask_pipeworx when not signed in, for single lookups, and for breaking/news topics; use deep_research for broad/multi-part structured-data questions. It also explains when to choose different depth levels, including the paid threshold for thorough.

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