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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds meaningful context beyond that: it details the success response shape, the explicit refusal format, the five refusal reasons, and the routing-to-fetch-to-extract pipeline. 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 every sentence earns its place: it front-loads the tool's core value and routing, then explains return contracts, refusal conditions, use cases, and cost trade-off. It is appropriately sized for a high-stakes tool with 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?

There is no output schema, so the description fully carries the burden of explaining return values and failure modes. It covers success shape, refusal shape, every refusal reason, and the primary use case. For a tool of this complexity, an agent has what it needs to call, interpret, and decide whether to use it.

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 all six parameters and their aliases. The description reaffirms that the question is in natural language but does not add meaning beyond what the schema provides, matching the baseline of 3.

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: it is a 'hallucination-resistant answer mode for high-stakes reads' that routes to the right tool, fetches data, and extracts answers only from tool results. It explicitly distinguishes itself from ask_pipeworx by name and by behavior, so an agent can identify it without ambiguity.

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 guidance: use whenever an answer will be quoted, cited, or acted on and the agent must not invent facts, with concrete examples. It also names the alternative ask_pipeworx and says to prefer it for casual lookups, along with the cost trade-off of 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.