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

Annotations only convey readOnly, idempotent, and non-destructive hints. The description adds substantial behavioral detail: exact success return shape, explicit refusal reasons such as 'not_in_source' and 'data_truncated', the guarantee of evidence as a verbatim quote, and the extra LLM call cost. It discloses more than the annotations provide.

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 every sentence earns its place: core behavior, routing mechanism, success contract, failure contract, usage context, and cost trade-off. The key differentiator ('Hallucination-resistant answer mode') is front-loaded, and the alternative is named for comparison.

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?

With no output schema, the description fully supplies the return contract and all failure modes. Since the tool takes only one question parameter and annotations already establish safety and idempotency, nothing needed to invoke or interpret the tool 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 description coverage is 100% and the input schema fully documents 'question' and its aliases. The description adds no additional parameter-level meaning, so the baseline score of 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 states a specific verb and resource: 'Hallucination-resistant answer mode' that routes, fetches, and 'EXTRACTS the answer using ONLY what the tool result contains.' It clearly distinguishes itself from ask_pipeworx by labeling itself as the grounded variant with evidence and refusal handling.

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 gives explicit guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements).' It also names the alternative and the trade-off: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.'

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