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

Annotations already declare readOnly/openWorld/idempotent, and the description goes well beyond them: latency (15-60s, thorough up to ~90s), gap-recovery and contradiction-scan behavior per depth tier, semantic excerpting rather than head-truncation, the guarantee that gaps[] are never invented, and citation_uri being present only when actually fetchable. This is rich behavioral disclosure that meaningfully shapes the agent's expectations.

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?

Front-loaded with the account/tier constraint before anything else, and every sentence carries real payload — no filler. It is dense and somewhat run-on as a single paragraph with heavy parentheticals, so scannability suffers, but for a tool this complex the length is justified and nothing is wasted.

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 correctly carries the burden of explaining the return shape: findings packet with verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], and hop field. It also covers auth requirements, latency, alternatives, and edge-case behavior (unanswerable facets, unfetchable citations). Nothing an agent needs to invoke this correctly 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 coverage is 100%, setting baseline at 3. The description adds value beyond the schema by mapping depth values to concrete behavioral consequences (single hop vs. gap-recovery hop vs. iterative lead-chasing), the paid-plan requirement for 'thorough', and the contradictions[] scan availability — none of which appear in the schema's depth description. The question parameter is adequately covered by the schema plus the description's natural-language emphasis.

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?

States a specific verb+resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in ONE call, with a concrete output packet. Explicitly distinguishes from siblings by saying 'this is NOT open-web search' and routing single lookups to ask_pipeworx. An agent can immediately tell what this does and how it differs from nearby tools.

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?

Gives explicit when-to-use ('Best for broad/multi-part questions over structured data'), an explicit alternative with a condition ('If you are not signed in, use ask_pipeworx instead — it works on every tier'), and an exclusion ('For a single lookup use ask_pipeworx instead'). Depth tiers and their behavioral implications are also spelled out.

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