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

Beyond readOnlyHint/openWorldHint/idempotentHint, the description adds rich behavioral context: account and paid-tier requirements, parallel decomposition across 5,798 tools, gap recovery and lead-chasing behavior per depth, contradictions[] for standard/thorough, guaranteed fetchable citations, semantic excerpting, and latency expectations. Every finding is described with its fields, and the 'never invented' gap behavior is explicitly stated.

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 for a tool this complex the density is justified. It front-loads the account requirement and the sibling alternative before diving into mechanics. Some phrasing is convoluted (the 'across... IN PARALLEL' sentence packs many clauses), but each sentence adds distinct information: sourcing, decomposition, output format, depth behavior, citation guarantees, latency.

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 carries full responsibility for explaining return values, and it does: findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri, hop, gaps[], contradictions[]. It also covers auth prerequisites, latency, depth semantics, and when not to use the tool. Nothing needed for correct invocation 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?

The schema already covers both parameters at 100%, so the baseline is 3. The description adds value beyond the schema: it maps depth values to facet counts (quick=3, standard=3, thorough=6), states that 'thorough' requires a paid plan, and explains the latency implications. It also clarifies that the question parameter accepts broad/multi-part natural language, which complements 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 verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call — this is NOT open-web search.' It clearly distinguishes from ask_pipeworx and open-web search, and provides concrete example questions. The resource scope (structured data sources, 5,798 tools) leaves no doubt about what the tool does.

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 says when to use this tool versus alternatives: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx instead.' It also gives a critical exclusion: 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' Depth tiers are mapped to use cases, so an agent can route correctly.

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