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

Beyond the annotations, the description discloses account requirements, structured-data scope, parallel facet decomposition, gaps[] for unanswered facets, contradictions[] for standard/thorough, stable citation URIs only when resolvable, semantic excerpting of large records, and expected latency. None of this contradicts the readOnly/openWorld/idempotent 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 information-dense: account requirements and the alternative tool are front-loaded, and every sentence contributes a distinct behavioral fact. There is no filler or tautology, and the length is appropriate for the tool's complexity.

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 covers the return contract: findings packet with verbatim evidence, confidence, source, fetched_at, hop, citation_uri, gaps[], and contradictions[]. It also explains edge behavior like unfetchable citations, deep-record excerpting, and timing, so an agent can invoke and interpret results confidently.

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 useful context beyond the schema: account/plan gating, latency expectations, and how depth levels map to follow-up hops and contradiction scans. However, much of the depth-enum semantics is already documented in the schema, so the increment is modest.

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 clearly states what deep_research does: grounded multi-source research over Pipeworx's 1517 structured data sources, decomposing questions into facets and routing them across tools in parallel. It explicitly contrasts itself with open-web search and names ask_pipeworx as the sibling for simpler lookups. This leaves no ambiguity about the tool's core function.

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 and when-not-to-use guidance: use ask_pipeworx if not signed in, use ask_pipeworx for single lookups, and use deep_research for broad/multi-part questions over structured data. It also flags the paid-tier requirement for the 'thorough' depth. This is strong alternative routing.

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