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

The description goes far beyond what annotations (readOnlyHint, openWorldHint, idempotentHint) provide: account gating with tier requirements, parallel decomposition across 5,798 tools, findings packet shape, gaps[] for unanswered facets ('never invented'), contradictions[] scan, semantic excerpting of large records, expected latency, and the conditional presence of citation_uri. Nothing in the description contradicts the annotations — readOnly/openWorld/idempotent are fully consistent with a multi-source research read.

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 (~320 words) but almost every sentence carries essential operational information, and the critical blocker (account required) plus fallback routing is front-loaded. It loses a point for its stream-of-consciousness parenthetical structure and minor redundancy (fetchable citations are asserted twice: 'stable pipeworx:// citation per finding' and later 'a citation you get back is always fetchable').

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 must carry the return-value burden, and it does: it enumerates the finding fields (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), the gaps[] array, contradictions[], the hop field, and citation_uri semantics. It also covers auth prerequisites, expected latency, and pricing constraints. Nothing an agent needs to invoke and interpret this tool correctly is missing.

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 baseline is 3. The description adds genuine value beyond the schema by explaining what the depth enum means operationally (hop counts per value, gap-recovery behavior, contradictions[] scan, and the paid requirement for 'thorough'), and clarifies that the question parameter is meant to be broad and decomposed. This elevates it above the schema-only baseline.

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 specific verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call'. It explicitly differentiates itself from open-web search ('this is NOT open-web search') and positions itself against siblings by noting single lookups should use ask_pipeworx. An agent can determine exactly what this tool does and how it differs from nearby tools.

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?

Gives explicit routing conditions: 'If you are not signed in, use ask_pipeworx instead — it works on every tier' and 'For a single lookup use ask_pipeworx', plus the positive case 'Best for broad/multi-part questions over structured data'. It names the alternative tool and the exact condition that selects it, leaving nothing to inference.

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