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

Annotations already mark the tool read-only, open-world, idempotent, and non-destructive, and the description adds substantial behavioral depth beyond that: it discloses the account/tier requirement, parallel decomposition across 5,798 tools, the findings packet structure, explicit gaps[] for unanswered facets, contradictions[] in standard/thorough modes, semantic excerpting rather than head truncation, and expected latency. No contradiction exists between the description and 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 long but information-dense, with key routing information front-loaded at the top ('ACCOUNT REQUIRED... use ask_pipeworx instead'). Some sentences are run-on and dense, but every major clause contributes a distinct behavioral fact, so the length is justified for a tool this complex.

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 carries the burden of explaining return behavior: findings packet fields, confidence, source, fetched_at, citation_uri, gaps[], contradictions[], hop field, and citation resolution guarantees. It also covers prerequisites, fallback routing, depth differences, and latency. An agent has everything needed to invoke and interpret 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% for both parameters, so the schema already documents question and depth. The description adds real value by explaining depth behavior in more operational terms ('gap-recovery hop', 'chases leads + recovers gaps', 'contradictions[] scan') and by clarifying that question can be broad/multi-part because decomposition is the point. This goes beyond the schema descriptions without redundant repetition.

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 verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in one call, and explicitly contrasts itself with 'open-web search'. It also identifies its niche ('Best for broad/multi-part questions over structured data') and distinguishes itself from the sibling ask_pipeworx by telling the agent when to use that tool instead.

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 routing guidance: 'If you are not signed in, use ask_pipeworx instead', and 'For a single lookup use ask_pipeworx'. It also explains which depth level is appropriate (quick/standard/thorough) and what each does, so the agent can select both the tool and its parameter reliably.

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