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

Even though annotations already declare readOnlyHint and openWorldHint, the description adds substantial behavior: parallel decomposition, routing across 5,798 tools, findings packet fields, gaps handling, never-invented guarantee, contradictions for standard/thorugh, semantic excerpting, latency expectations, and account/paid gating. This goes well beyond the annotation envelope.

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 front-loaded with the most critical operational gate (account/paid requirement) and the alternative tool. Almost every sentence carries a distinct fact, but the dense parenthetical style and flow-of-consciousness ordering make it slightly harder to parse than necessary.

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 only two scalar parameters and no output schema, the description carries the full burden of explaining the output contract (verbatim evidence, confidence, source, fetched_at, citation_uri, gaps, contradictions) and invocation constraints (account, paid tier, latency, depth behavior). Nothing critical is missing for an agent to call 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 coverage is 100%, so the baseline is 3. The description adds useful parameter-level meaning: thorough requires a paid plan, quick/standard/thorugh have different follow-up and contradiction behavior, and question scope can be broad/multi-part. This is more than the schema alone provides, though not by a huge margin.

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 behavior: grounded multi-source research across Pipeworx's 1517 structured data sources in one call. It explicitly distinguishes itself from open-web search and names ask_pipeworx as the tool for single lookups, so an agent can clearly separate it from siblings.

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 routing rules: if not signed in, use ask_pipeworx instead; use deep_research for broad/multi-part structured-data questions; use ask_pipeworx for a single lookup. It also differentiates depth levels and when thorugh is appropriate, so an agent knows when to invoke this tool versus alternatives.

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