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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false), the description discloses the account prerequisite, paid plan for 'thorough', parallel routing across 5,961 tools, output packet structure (verbatim evidence, confidence, source, fetched_at, citation_uri, gaps, contradictions), semantic excerpting, and expected latency (15-60s, up to ~90s). This is rich, non-obvious behavioral context.

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 dense with high-value information and is front-loaded with the most critical routing guidance (account required, use ask_pipeworx if not signed in). Some minor redundancy exists (e.g., 'thorough' paid plan mentioned twice), but every sentence largely earns its place for a complex tool.

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?

Given the high complexity and absence of an output schema, the description thoroughly explains the return format (findings packet, gaps, contradictions, hop, citation_uri), prerequisites, limitations (not open-web search, empty gaps for news topics), and latency. An agent has everything needed to call it 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 description coverage is 100%, so the schema already documents both parameters and the depth enum. However, the description adds helpful meaning beyond the schema: it explains the facet counts, hop behavior, gap recovery, contradiction scanning, and paid requirement for 'thorough'. This is useful extra context, though not exhaustive.

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 ('Grounded multi-source research') and resource ('1552 STRUCTURED data sources'), and explicitly distinguishes itself from open-web search and from the sibling ask_pipeworx. An agent can immediately tell what this tool does and when it is different from alternatives.

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?

It gives explicit conditions for use: signed-in required, use ask_pipeworx if not signed in, best for broad/multi-part questions over structured data, use ask_pipeworx for single lookups, and prefer ask_pipeworx for breaking current-news topics. Nothing is left to inference.

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