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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint, and the description adds substantial behavior beyond them: auth/tier requirements, parallel decomposition across 5,798 tools, the gaps[] 'never invented' guarantee, hop semantics per depth level, resolvable citation_uri condition, contradictions[] behavior, semantic excerpting, and latency bounds (15-60s, ~90s for thorough). No contradiction with the 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?

Long (~300 words) but information-dense, and the most decision-critical facts are front-loaded: account requirement, sign-in URL, and the ask_pipeworx fallback. Every sentence earns its place given the tool's complexity. Minor deductions for redundancy with the schema's depth descriptions and the unescaped inner quotes (depth:"thorough", depth:"standard") that read as formatting artifacts.

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 carries the full burden of explaining the return packet — verbatim evidence, confidence, source, fetched_at, citation per finding, gaps[], contradictions[] — and it does so thoroughly. Prerequisites (account tiers), alternatives, mechanics, guarantees, and timing are all covered; an agent can safely decide whether to invoke and what to expect.

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 schema already documents both parameters; baseline is 3. The description adds meaning beyond the schema by tying depth levels to behavior ('depth:standard re-angles unanswered gaps', 'thorough additionally chases the best leads'), gating 'thorough' behind a paid plan, and attaching latency expectations to each mode. This is valuable context, though the enum descriptions in the schema already carry the core 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 action and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... in ONE call'. It explicitly distinguishes itself from alternatives — 'this is NOT open-web search' — and from ask_pipeworx, which is the single-lookup sibling. The examples ('compare X and Y's regulatory + financial exposure') make the tool's niche unmistakable.

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 and when-not-to-use guidance: 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx instead'. It even routes based on auth state: 'If you are not signed in, use ask_pipeworx instead — it works on every tier'. No inference is left to the agent.

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