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

Beyond annotations (readOnly, openWorld, idempotent, non-destructive), the description adds substantial behavioral context: account/paywall requirements, parallel tool routing, evidence-and-citation return format, explicit gaps[] for unanswered facets, contradiction scanning, hop fields, fetchable citation URIs, semantic excerpting, and latency expectations. No contradiction with annotations is present.

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, and the most decision-critical facts (account requirement, fallback tool, not-open-web positioning) appear early. Every sentence contributes functional guidance, though the density and length could be slightly compressed without losing value.

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 compensates by explaining what the findings packet includes: verbatim evidence, confidence, source, fetched_at, pipeworx:// citations, gaps[], contradictions[], hop field, and citation_uri resolvability. It also covers auth, cost tiers, latency, and fallback behavior, making the tool actionable for an agent.

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 for both parameters is 100%, so the schema already documents question and depth. The description adds meaningful context beyond it: how depth affects hops and contradiction scans, that 'thorough' requires a paid plan, that broad questions are acceptable, and how facets are decomposed. Not a full 5 because the schema already carries the core parameter semantics.

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 clearly states the tool performs grounded multi-source research across Pipeworx's structured data sources, decomposing questions into facets and routing them in parallel. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can differentiate it from siblings without opening schemas.

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: best for broad/multi-part questions over structured data, while single lookups and breaking/colloquial current-news topics should go to ask_pipeworx. It also names the fallback for unsigned-in users and explains depth-level tradeoffs, leaving little to inference.

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