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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses detailed behavioral traits: never invents gaps, returns verbatim evidence with confidence/source/fetched_at/citations, semantically excerpts long records, runs iterative hop/recovery passes by depth, and cites expected latencies. It also explains citation_uri's condition ('present only when source emits one that resources/read can actually serve'), adding real execution semantics.

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 information-dense, with the critical account gate front-loaded before the core mechanics. Parenthetical asides pack complementary details (paid tier, hop behavior, citation fetchability) without bloating the main clauses, and every sentence contributes unique operational guidance.

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 the full burden of explaining return semantics — and it does: findings packet with evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[] for unanswered facets, contradictions[] for standard/thorough, hop field, and citation_uri behavior. Combined with annotations and 100% schema coverage for the two parameters, an agent has enough context to invoke this tool correctly and interpret its result.

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 the baseline is 3. The description adds value beyond the schema by flagging that 'thorough' requires a paid plan, clarifying that quick/standard/thorough differ by facet count and iterative hops, and giving latency expectations that depend on the chosen depth. The schema already explains the enum values, but the paid-plan and timing context are not repeated in the schema.

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 verb-resource ('Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources') and explicitly differentiates it from open-web search and from ask_pipeworx. It also explains the decomposition-and-parallel-routing mechanism and the findings-packet output, so an agent knows exactly what the tool accomplishes and how it differs from 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?

The description gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete examples, and clear when-not-to-use guidance: 'For a single lookup use ask_pipeworx instead.' It also names the alternative (ask_pipeworx) and adds an account/tier prerequisite, so selection and preconditions are unambiguous.

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