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

Adds substantial context beyond the readOnlyHint/openWorldHint/idempotentHint annotations: account sign-in requirement, paid thorough tier, 15-90s latency, gaps[] that are never invented, contradictions[] for standard/thorough, resolvable citation_uri, semantic excerpting rather than head-truncation, and hop behavior. 'NOT open-web search' refines the openWorldHint rather than contradicting it.

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 same full block — from 'ACCOUNT REQUIRED' through 'Best for broad/multi-part questions over structured data' — is repeated at least three times, making the description grossly oversized. It is not front-loaded in any disciplined sense; the repeated passages waste agent context and obscure the genuinely unique second-hop/citation-uri content.

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 carries full responsibility for explaining return values and does so thoroughly: findings packet contents (verbatim evidence, confidence, source, fetched_at, citation_uri), gaps[], contradictions[], and hop field. Auth, pricing, latency, scope limits, and data sources are all covered, leaving no call-critical gap for an agent.

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 description coverage is 100%, so baseline is 3; the description adds value by linking depth values to latency, paid access, gap-recovery hops, and contradiction scans, and by noting that broad/multi-part questions are the intended input for the question param. It doesn't duplicate the schema's per-value facet counts, so it earns a 4 rather than a 5.

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 deliverable: grounded multi-source research that decomposes a question into facets, routes each to one of 5,798 tools in parallel, and returns a findings packet with citations. Explicitly distinguishes itself from open-web search and from the ask_pipeworx sibling for single lookups, so an agent can tell it apart from the 30+ sibling 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 when-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete example questions, and two named exclusions — 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead'. Also flags the paid-plan gate for the thorough depth, which is selection-relevant.

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