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

Even with readOnlyHint, openWorldHint, and idempotentHint annotations present, the description adds substantial behavioral context: account requirements, paid depth tier, decomposition and parallel routing, gaps[] that are never invented, contradictions[] on standard and thorough depths, resolvable citation_uri guarantees, semantic excerpting, and expected latency. This goes far beyond what annotations alone convey.

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 it is front-loaded with the account constraint and the sibling alternative. It is organized by topic, though a few details like the exact count of 5,798 tools and repeated one-call emphasis could be trimmed without losing meaning.

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 carries the full burden of explaining return values, and it does: findings packet fields, gaps[], contradictions[], hop field, and citation_uri. It also covers prerequisites, latency, depth behavior, and data scope, so an agent has enough context to invoke the 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 description coverage is 100%, so the input schema already explains the question and depth parameters in detail. The description still adds meaningful value by noting that thorough requires a paid plan and by tying latency expectations to depth (15-60s, up to ~90s for thorough). That extra semantic context lifts it above the high-coverage baseline.

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: grounded multi-source research across Pipeworx structured data sources, decomposing questions into facets and returning a findings packet. It clearly distinguishes itself from siblings by saying this is NOT open-web search and by naming ask_pipeworx for single lookups. The tool's purpose is 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?

The description explicitly says it is best for broad/multi-part questions over structured data and directs single lookups to ask_pipeworx instead. It also provides an auth-based routing rule: if not signed in, use ask_pipeworx because it works on every tier. This gives clear when-to-use and when-not-to-use guidance.

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