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

The description goes far beyond the annotations: it discloses the decomposition behavior, parallel tool routing, gaps[] semantics with a 'never invented' guarantee, contradictions[], citation_uri fetchability conditions, semantic excerpting instead of head-truncation, and expected latency. This is rich behavioral context that the readOnly/openWorld/idempotent annotations do not convey.

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; every clause conveys a meaningful distinction or behavior. It front-loads the critical auth constraint and sibling routing, then moves through scope, output packet, depth semantics, and latency. It is structured enough that no sentence feels wasted, though some repetition exists around the structured-vs-open-web distinction.

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?

Given the tool's complexity and the absence of an output schema, the description fully covers return packet shape, citation semantics, gaps/contradictions behavior, auth requirements, tier differences, timing expectations, and sibling alternatives. An agent has everything needed to select and correctly invoke this tool.

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. The description adds practical meaning beyond the schema by explaining 'thorough' requires a paid plan, clarifying that 'standard' re-angles unanswered gaps, and detailing how each depth tier affects iteration and contradiction scanning. It reinforces and expands on the enum values, so it earns a 4.

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 also clearly distinguishes itself from open-web search and from the ask_pipeworx sibling by explaining what it is NOT ('this is NOT open-web search') and what it is best for (broad/multi-part structured-data questions).

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 deep_research for broad multi-part structured questions, use ask_pipeworx for single lookups or trending/news topics, and use ask_pipeworx if not signed in. It also describes when depth tiers apply and how 'standard' vs 'thorough' behave in follow-up hops.

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