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

Annotations already establish readOnly, openWorld, idempotent, and non-destructive hints. The description goes well beyond that by disclosing the findings packet structure, verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citations, explicit gaps[], contradictions[], semantic excerpting behavior, and latency expectations. This is exactly the kind of post-execution behavior an agent cannot infer from 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 front-loaded with account requirements and core purpose, which is good. However, the sentence 'For a single lookup use ask_pipeworx instead — it works on every tier.' is repeated verbatim many times, bloating the description significantly. Not every sentence earns its place, so the structure is weakened despite the rich content.

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?

This is a complex tool with only two parameters and no output schema, but the description covers input style, depth semantics, return packet shape, citation resolvability, gap handling, contradiction behavior, latency, and auth requirements. An agent has enough context to select the tool and interpret results correctly without needing additional documentation.

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 value on top of the schema by tying depth to concrete latency expectations (15-60s, thorough up to ~90s), reiterating the paid-tier constraint, and giving natural-language example questions that clarify what the question parameter should contain. That is genuine enrichment beyond the schema.

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 action: grounded multi-source research across Pipeworx's structured data sources, with decomposition and parallel routing. It also explicitly says this is NOT open-web search, which distinguishes it from generic search tools. It names ask_pipeworx as the alternative for simpler use cases, so an agent can tell them apart.

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: broad/multi-part questions over structured data, with concrete examples. It also gives when-not-to-use guidance: use ask_pipeworx for a single lookup or when not signed in. Account requirements and paid-tier depth limits are stated up front.

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