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

Even with annotations covering read-only, open-world, and idempotent behavior, the description adds substantial context: account and paid-tier requirements, latency expectations, the findings-packet format, gaps[] and contradictions[] semantics, never-invented behavior, and semantic excerpting of large records. There is no contradiction with the 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?

The description is dense and information-rich, and the most critical constraints are front-loaded: account requirement, alternative tool, and core scope. However, it is one long unbroken paragraph with many parentheticals and semicolons, which reduces scannability compared to a structured or list-based layout.

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 fully takes on the responsibility of explaining return values: findings packet fields, citation_uri fetchability, gaps[], contradictions[], and processing time. Combined with rich annotations and complete parameter schemas, an agent has everything needed to invoke 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 description coverage is 100%, and the schema already thoroughly documents both parameters, including depth enum behavior and the fact that broad/multi-part questions are supported. The description mostly restates this context rather than adding new parameter-level meaning, so it stays at the 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 names a specific operation, grounded multi-source research, and a specific resource, Pipeworx's 1,500 structured data sources. It also distinguishes itself from open-web search and from the ask_pipeworx sibling by explaining its parallel decomposition across 5,743 tools.

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 when to use this tool, broad or multi-part questions over structured data, and when not to use it, single lookups and breaking/current news, naming ask_pipeworx as the alternative in both cases. It also adds an auth-based exclusion: unsigned-in users should use ask_pipeworx instead.

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