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

The description goes far beyond the readOnly/openWorld/idempotent annotations: it discloses the account/paywall requirement, the parallel decomposition execution model, the exact return packet contents (verbatim evidence, confidence, source, fetched_at, citation URI, gaps[]), the contradictions[] scans for deeper depths, semantic excerpting behavior, and expected latency. No annotation contradictions.

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 and dense, which is justified by the tool's complexity, but it is not as tightly written as the best examples. It front-loads the account requirement and primary purpose, and organizes details coherently, though some phrasing is convoluted and could be trimmed without loss of 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?

There is no output schema, so the description carries the full burden of explaining return values—it does, in detail: findings packet, confidence, source, citations, gaps[], contradictions[], hop field. It also covers prerequisites, errors/fallback (ask_pipeworx), and timing, making the tool fully understandable for correct invocation.

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 schema already documents question and depth well. The description adds some operational context (deep research is paid, standard default, multi-step resolution in one call) but does not materially expand on what each parameter means beyond what the schema provides. Baseline 3 is appropriate.

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's 1517 STRUCTURED data sources' in one call. It explicitly contrasts with open-web search and distinguishes from ask_pipeworx ('For a single lookup use ask_pipeworx instead'), making its unique niche 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?

Gives clear when-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete example questions. It also provides a specific exclusion: 'If you are not signed in, use ask_pipeworx instead' and 'For a single lookup 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.