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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds substantial context: account/plan requirements, parallel routing to 5,743 tools, findings-packet structure (verbatim evidence + confidence + source + fetched_at + citation), explicit gaps[], contradictions[], hop fields, citation resolvability, semantic excerpting, and latency expectations. These behaviors are not inferable from annotations alone and are critical for trust and correct invocation.

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 it front-loads the account requirement, core function, and sibling differentiation before diving into depth semantics, guarantees, and timing. Every sentence earns its place for a tool this complex, though the density approaches a wall of text and could benefit from slight formatting.

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 correctly carries the burden of explaining return values — it enumerates the findings packet, evidence confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], hop field, and citation_uri resolvability. It also covers failure modes (empty gaps for news topics), account/plan prerequisites, and approximate latency. Nothing an agent needs to invoke this tool correctly is missing.

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 schema already documents both parameters clearly. The description adds meaningful nuance beyond the schema for depth (explaining quick/standard/thorough in terms of facet counts, gap recovery, lead chasing, and the contradictions scan) and clarifies that question is natural-language and may be broad or multi-part. The added value is real but modest because the schema already does a solid job.

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 1500 STRUCTURED data sources' and explicitly contrasts with open-web search. It names sibling alternatives (ask_pipeworx) and tells when each is appropriate, making the tool's scope unmistakable.

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 ('Best for broad/multi-part questions over structured data') and when-not-to-use guidance ('For a single lookup use ask_pipeworx', 'For BREAKING or colloquial CURRENT-NEWS ... prefer ask_pipeworx'). Also handles the account prerequisite and fallback for unsigned-in users, leaving no ambiguity about selection.

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