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

The description goes well beyond the annotations (readOnlyHint, openWorldHint, idempotentHint). It details the parallel routing to 5,767 tools, the findings packet structure (verbatim evidence, confidence, source, fetched_at, stable citation), the gaps[] behavior (never invented), contradictions[] scan, hop field, semantic excerpting, and expected latency ranges for different depths. It also discloses the account requirement and the paid tier for thorough depth. This is comprehensive disclosure of behavioral traits.

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 dense but long; it packs a lot of operational detail. It front-loads the account requirement and the alternative (ask_pipeworx), which is the most critical information for call eligibility. The later sentences about hop fields, citation URIs, and semantic excerpting are valuable but somewhat encyclopedic. Every sentence earns its place, though a tighter edit would improve scannability.

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?

The description fully covers eligibility (account, paid plan), alternatives, output format (findings packet, gaps[], contradictions[], hop, citation_uri), latency expectations, depth semantics, and the type of input desired. Given there is no output schema, the description must explain return values — and it does. Nothing necessary for an agent to correctly select and call this tool is missing.

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 both parameters are documented in the schema. The description adds extra semantic value by explaining what 'depth' means in terms of facet counts, hops, gap recovery, and contradictions scan — richer than the schema's enum descriptions. It also clarifies that 'question' should be broad/multi-part natural language and offers example question formats. The description significantly enriches both parameters beyond schema baseline.

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 that this tool performs grounded multi-source research across 1,506 structured data sources in one call. It uses a specific verb ('research'), identifies the resource ('Pipeworx's structured data sources'), and explicitly distinguishes itself from open-web search. It also differentiates from sibling tools by naming ask_pipeworx and search_within as alternatives for different use cases.

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 explicitly states when to use this tool: 'Best for broad/multi-part questions over structured data.' It also provides concrete exclusion guidance: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' It also notes that quick depth is single-hop and not suitable for multi-step questions. This is explicit when/when-not guidance that names alternatives.

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