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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description goes well beyond them: it discloses that findings are verbatim evidence with confidence/source/fetched_at and pipeworx:// citations, that gaps[] are explicit when data can't answer, that it never invents, and that thorough/standard include contradictions[]. It also discloses latency ranges and the paid requirement for thorough. 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?

Dense and front-loaded with the most operationally critical constraint (account required, paid tier for thorough) before the core capability. Every sentence adds value, though the sentence structure with parentheticals and semicolons makes it a bit heavy; it could be broken into cleaner sentences without losing 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?

Despite no output schema, the description fully describes the return shape: findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri, hop field, gaps[], contradictions[], and excerpting behavior. It also covers expected latency, prerequisites, and alternatives. An agent has everything it needs to decide and call this tool correctly.

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 schema already describes both parameters. The description adds semantic value by explaining depth levels in plain terms (quick=3 single hop, standard=3 with gap recovery plus contradictions, thorough=6 paid with iterative hop), which enriches the enum semantics beyond the schema's wording. It could have also mapped depth to latency more explicitly, but it already mentions timing in the text.

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 and resource: multi-source research over Pipeworx's 1517 structured data sources, explicitly contrasting itself with open-web search. It distinguishes itself from ask_pipeworx and mentions decomposition across 5,798 tools in parallel, so an agent can tell it apart 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?

Explicitly says when to use it (broad/multi-part questions over structured data) and when not to (single lookup -> ask_pipeworx; not signed in -> ask_pipeworx). It also names the alternative and the condition that selects it, plus tier/plan guidance. This is exceptionally actionable.

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