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

The description goes well beyond the readOnly/idempotent annotations, disclosing account and plan requirements, expected latency (15-60s, ~90s for thorough), parallel routing to 5,714 tools, gap[] and contradictions[] return behavior, semantic excerpting, and citation_uri fetchability guarantees. All of this is valuable behavioral context not implied by 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 densely informative and front-loaded with the account requirement and core purpose. Every sentence adds operational detail; the structure is organized enough that an agent can parse it. Slightly verbose for pure conciseness, but each part earns its place for such a complex tool.

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 explains the return packet (verbatim evidence, confidence, source, fetched_at, citation, gaps[], contradictions[]), behavioral differences across depth values, latency, authentication, and the tool's applicability. An agent has everything needed to select and invoke this tool correctly.

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 the depth enum. The description adds meaningful context above that by linking depth tiers to behaviors (gap recovery, iterative chases, contradiction scans), tying thorough to the paid plan, and affirming that broad/multi-part questions are acceptable. This is more than baseline, though not a major semantic expansion.

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?

States a precise verb and resource: 'Grounded multi-source research across Pipeworx's 1495 STRUCTURED data sources' that 'decomposes your question into focused facets' and 'returns a findings packet'. It explicitly distinguishes itself from ask_pipeworx and emphasizes 'this is NOT open-web search', making its role unambiguous among siblings.

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?

Offers explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data', with concrete examples. It also states exclusions and alternatives: 'For a single lookup use ask_pipeworx' and 'For BREAKING or colloquial CURRENT-NEWS... prefer ask_pipeworx', plus a note about account requirements and the ask_pipeworx fallback when signed out.

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