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

Annotations already declare readOnly/openWorld/idempotent, and the description adds rich behavioral context: account/plan requirements, 15-90s latency, explicit gaps[] instead of inventing answers, contradictions[] for standard/thorough, semantic excerpting, and resolvable citation_uri. It also clarifies that results depend on the structured catalog and may be empty for current-news topics. No contradiction with 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 long, but the tool is complex and the extra length mostly earns its place: account gating, scope restrictions, alternatives, depth semantics, return format, and latency are all meaningful for correct invocation. Some depth details repeat what the input schema already states, so it is not maximally tight, but it is well organized and front-loaded with the most decision-relevant information.

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 must carry the burden of explaining return values — and it does: findings packet with verbatim evidence, confidence, source, fetched_at, stable citation, gaps[], contradictions[], and hop field. Combined with usage alternatives, auth/plan requirements, latency, and parameter semantics, an agent has enough to select and invoke this tool correctly.

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 beyond the schema by tying depth levels to concrete behaviors (quick=3 facets, standard adds gap-recovery, thorough is paid and chases leads) and emphasizing that the question can be broad/multi-part because decomposition is the point. It reinforces and slightly extends the schema's parameter documentation.

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 names a specific verb and resource: grounded multi-source research across Pipeworx's structured data sources, with decomposition into facets, parallel routing, and a findings-packet return. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can tell them apart without guessing.

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 structured-data questions, with concrete examples. It also names the alternative and its condition: single lookup or breaking/current-news topics → use ask_pipeworx; not signed in → use ask_pipeworx. This is exactly the kind of routing clarity an agent needs.

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