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

Beyond the read-only/open-world/idempotent annotations, the description discloses the account requirement, paid tier for thorough depth, parallel decomposition across 5,743 tools, output structure with confidence/source/fetched_at/citation, explicit gaps[] with never-invented behavior, contradictions[] for standard/thorough, semantic excerpting, and expected latency. This is extensive and valuable 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 dense and front-loaded with the account requirement and fallback routing, which is good. However, it is quite long and partially redundant with the schema's depth descriptions, repeating details about 'gap recovery,' 'chases leads,' 'contradictions[]', and the paid thorough tier. It earns its length for the most part, but could be tightened.

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 tool's complexity, no output schema, and only 2 parameters, the description is remarkably complete. It covers authentication, fallbacks, scope, method, output format, citation resolvability, failure-mode behavior, contradictions, semantic excerpting, and latency. An agent has nearly everything needed to decide whether and how to invoke this tool.

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% and the depth enum is already well-documented, so the baseline is 3. The description adds meaningful context beyond the schema: it explains the practical consequence of depth choices (multi-step questions resolving in one call, gap recovery, contradiction scans), latency expectations, and the paid-plan gate for thorough. This helps an agent choose a depth value with fuller understanding.

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 the tool performs grounded multi-source research across Pipeworx's 1500 structured data sources, decomposing a question into facets and returning a findings packet. It also distinguishes itself from ask_pipeworx by emphasizing it is not open-web search and is for broad/multi-part questions. This makes the tool's purpose and scope explicit.

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 guidance: best for broad/multi-part structured-data questions, and explicitly says to use ask_pipeworx instead for signed-out users, single lookups, and breaking/current-news topics. Naming alternatives and the conditions that route to them is exactly the clarity an agent needs.

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