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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses account tiers, paid depth requirements, parallel decomposition, gap handling with gaps[], contradiction detection, citation_uri fetchability guarantees, semantic excerpting of large records, and expected latency. This richly characterizes behavior without contradicting the 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 dense and long, but every sentence carries operational value, and key constraints (account requirement, free tier, alternative tool) are front-loaded. The heavy use of parentheticals and nested clauses makes it slightly harder to parse, but the organization is logical and all content earns its place.

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?

For a complex tool with no output schema, the description is remarkably complete: it explains the findings packet fields, citation behavior, gap handling, contradiction reporting, deep-dive mechanics, and expected latency. It also tells the agent when not to use the tool and what to use instead, leaving little ambiguity about how and when to invoke it.

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 input schema already documents both parameters thoroughly, including depth semantics and the fact that broad/multi-part questions are acceptable. The description adds useful operational context like the paid requirement for 'thorough', but it mostly restates the schema's parameter meaning rather than introducing new parameter-level semantics.

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 (multi-source structured research), a clear resource (Pipeworx's 1,517 structured data sources), and a distinct deliverable (findings packet with evidence, confidence, source, and citations). It also explicitly separates itself from open-web search and from sibling tools like ask_pipeworx, so an agent can tell what deep_research is for.

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: sign-in is required, unpaid users are routed to ask_pipeworx, and single lookups should use ask_pipeworx. It further states the tool is best for broad/multi-part questions over structured data, which gives clear selection criteria against sibling tools.

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