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

Beyond the readOnlyHint, openWorldHint, and idempotentHint annotations, the description discloses exactly what happens under the hood: it routes, fetches data, and extracts only from the tool result. It also details the return contract including refusal_reason values and success/refusal shapes. This gives the agent a precise behavioral model without contradicting any annotation.

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 information-dense with no filler. It front-loads the core purpose in the first phrase, then methodically covers behavior, return shape, refusal handling, use cases, and cost trade-off. Every sentence earns its place and the structure aids quick comprehension.

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?

Given there is no output schema, the description fully compensates by specifying the exact success and refusal return shapes, including refusal_reason enum values. It also covers when to use the tool versus the sibling and the cost difference. This is complete enough for an agent to select and invoke the tool correctly.

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?

The input schema already documents all parameters at 100% coverage, including alias explanations, so the description does not need to add much. The description explains the high-level behavior but adds no parameter-level semantics beyond what the schema provides. Baseline 3 is appropriate given the schema's thorough coverage.

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 clearly identifies a specific verb and resource: it is a 'hallucination-resistant answer mode' that routes through ask_pipeworx but extracts answers only from tool results. It explicitly distinguishes itself from ask_pipeworx by framing the use case as high-stakes reads where facts must not be invented. This makes its purpose unambiguous and differentiates it from siblings.

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 provides explicit when-to-use guidance: use whenever the answer 'will be quoted, cited, or acted on' and the agent must not invent facts. It also gives a clear when-not-to-use rule by stating it costs 'one extra LLM call vs ask_pipeworx' and instructs to 'prefer ask_pipeworx for casual lookups.' This is exemplary usage routing.

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