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

Beyond the readOnly/idempotent annotations, the description discloses significant access limitations (account required, paid tier for 'thorough'), latency expectations (15-60s, up to ~90s), output structure (findings packet with gaps[], contradictions[], hop, citation_uri), and important guarantees like 'never invented' and semantically excerpted records. This is rich behavioral context that annotations alone could 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 dense and long, but every sentence adds meaningful information—access requirements, alternatives, output packet, depth semantics, latency. It opens with the critical account caveat and alternative, which is good front-loading. A bit more visual structure (bullet points or short paragraphs) would improve scannability, but there is little redundancy.

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 fully compensates by detailing the findings packet fields, gap behavior, contradiction detection, hop field, citation_uri resolvability, and latency. For a tool of this complexity, nothing essential is missing: the agent knows what to expect, how long it takes, and how to route around it when inappropriate.

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 already documents all parameters with 100% coverage, so baseline is 3. The description adds value by explaining how depth values behave in practice: 'standard' re-angles gaps, 'thorough' chases leads, and both return contradictions[]—details beyond the schema's enum descriptions. It also clarifies that 'question' is meant to be broad and multi-part.

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—'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources'—and distinguishes itself from open-web search. It also differentiates from ask_pipeworx by scope and use case, making the tool's role in the sibling set unmistakable.

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 routing guidance: use ask_pipeworx when unsigned in, for single lookups, or for breaking/current news; prefer deep_research for broad/multi-part structured-data questions. It names exact alternatives and the conditions that select each, leaving no ambiguity about when to invoke this tool.

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