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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description goes well beyond these by disclosing account/paid-tier requirements, parallel decomposition, `gaps[]` for unanswered facets, a never-invented guarantee, fetchable citation URIs, semantic excerpting, contradiction scanning, and latency expectations. There is no contradiction with 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 critical account caveat, then the value proposition, then return semantics, then latency. A few details repeat what the schema's `depth` description already states, but overall every sentence adds meaningful operational context.

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?

Despite no output schema, the description fully covers what the agent will receive: findings packet, evidence, confidence, source, fetched_at, citation URIs, gaps, contradictions, and excerpting behavior. Auth requirements, latency, and alternatives are all addressed, making the tool safe and practical to invoke.

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 the baseline is 3. The description adds practical nuance beyond the schema: question accepts natural-language broad/multi-part queries, depth behaviors are tied to paid tiers, and the trade-offs between quick/standard/thorough are reinforced with concrete operational meaning.

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 uses a specific verb and resource: "Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources" in ONE call. It also explicitly distinguishes itself from open-web search and from ask_pipeworx, making its scope unambiguous.

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: "If you are not signed in, use ask_pipeworx instead," "Best for broad/multi-part questions," and "For a single lookup use ask_pipeworx instead." This clearly tells an agent when to select this tool versus its sibling alternatives.

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