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

Annotations already provide readOnlyHint/openWorldHint/idempotentHint; the description adds substantial context beyond them: auth requirements (free GitHub sign-in, paid plan for 'thorough'), latency bounds (15-60s, up to ~90s), the findings-packet envelope (gaps[], contradictions[], hop, citation_uri), the 'never invented' honesty guarantee, and semantic excerpting behavior. No claim contradicts the read-only 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?

Front-loaded with the account gate and fallback tool before the purpose. The length is justified by the tool's complexity — auth tiers, three depth levels, sibling routing, rich return envelope, latency — and nearly every clause earns its place. Falls short of 5 because the single-paragraph wall with nested parentheticals and dash-chains is harder to parse than needed.

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?

For a complex tool with no output schema, the description must define the return contract — and it does, in detail: verbatim evidence + confidence + source + fetched_at + citation_uri, gaps[] for unanswered facets, contradictions[] at standard/thorough depths, hop fields, and resolvability guarantees. Also covers latency, auth prerequisites, failure behavior (empty gaps[] when topic isn't in the catalog), and excerpting. Nothing required to invoke or interpret the result 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% with a detailed enum description for depth, so the baseline is 3. The description adds genuine value beyond the schema: the paid-plan gate on 'thorough', per-depth hop/contradiction behavior, and latency expectations — decision-relevant facts an agent needs before choosing a depth. Not a 5 because the schema already carries the core depth semantics.

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 and resource: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources... in ONE call.' Explicitly differentiates from siblings — 'this is NOT open-web search', contrasts with ask_pipeworx for single lookups and breaking news. Worked examples ('compare X and Y's regulatory + financial exposure') pin down the intended use.

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?

Provides explicit when-to-use ('Best for broad/multi-part questions over structured data'), when-not-to-use ('For a single lookup use ask_pipeworx', breaking news → ask_pipeworx), and an auth-based fallback ('If you are not signed in, use ask_pipeworx instead'). Names alternatives and the exact conditions that select them — nothing left to inference.

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