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

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds substantial behavioral context beyond those: it returns a findings packet with verbatim evidence, confidence, source, fetched_at, and citations; it explicitly reports gaps[] and 'never invented' findings; it describes contradiction detection, semantic excerpting, and expected latency (15–60s, up to ~90s). This goes far beyond the annotation hints.

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 and contains a lot of valuable information, but it is structured as one long paragraph with many phrases crammed together (e.g., 'ACCOUNT REQUIRED...' plus depth variants and timing). Most sentences earn their place, but formatting with separators or bullet-like structure would improve scanability. It is not wasteful, just packed.

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?

Given the tool's complexity (2 params, no output schema), the description is remarkably complete: it covers auth requirements, fallback behavior, data source scope, parallelism, output contents, gap handling, contradiction detection, citation semantics, excerpting behavior, and latency expectations. An agent has nearly everything needed to invoke it correctly and interpret its results.

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 the schema already documents both parameters. The description adds meaningful detail beyond the schema, particularly for the depth parameter: it explains quick=3 (single hop), standard=3 (gap-recovery hop + contradictions scan), and thorough=6 (paid, full iterative hop), plus timing implications. This enriches agent understanding of trade-offs.

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 1,517 structured data sources in one call. It explicitly differentiates from siblings by noting 'this is NOT open-web search' and directing single lookups to ask_pipeworx, so an agent can select it correctly.

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 conditions: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx instead'. It also names an alternative for unsigned-in users ('use ask_pipeworx instead'), making routing decisions explicit rather than implied.

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