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

Annotations already establish read-only/idempotent/non-destructive behavior, and the description adds substantial detail: it returns evidence as a verbatim quote, can refuse with structured reasons such as not_in_source or data_truncated, and never fabricates facts outside the tool result. It also discloses the cost tradeoff. 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 dense but front-loaded with the core promise ('hallucination-resistant') and each remaining sentence adds a distinct fact: routing, output shape, refusal reasons, use cases, and cost comparison. The output-shape listing is justified because there is no output schema.

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 routing tool with no output schema, the description fully covers success and failure responses, evidence semantics, refusal reasons, when to use it, and how it differs from ask_pipeworx. The only missing detail is exact confidence semantics, which is minor.

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%: all six parameters are documented as aliases for 'question' and as natural-language input. The description adds no specific parameter syntax or format detail, but the schema already carries that burden, so baseline 3 is appropriate.

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 behavior: a grounded answer mode that routes through Pipeworx, fetches data, and extracts an answer using only the tool result. It distinguishes itself from ask_pipeworx by emphasizing verbatim evidence and explicit refusals rather than free-form answers.

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?

It tells the agent exactly when to choose grounded mode — when the answer will be quoted, cited, or acted on, especially for financial, legal, medical, or public-statement contexts. It also gives an explicit exclusion: prefer ask_pipeworx for casual lookups because grounded mode costs one extra LLM call.

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