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

With no annotations, the description carries the burden of explaining behavior. It usefully discloses that the tool contains warnings and data caveats rather than raw query results, and provides concrete examples of what it states. It does not explicitly say whether it is a static read-only document or describe its return format, but 'read_first' and 'read this' make the read-only nature reasonably clear.

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 compact and front-loaded with the core purpose: it tells the agent to read before computing, then gives specific, high-value examples of the warnings inside. No sentence is wasted, and the most important directive appears early.

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 no-parameter informational tool, the description provides enough context for an agent to decide to call it first and to understand the kind of content it will receive. It does not specify the output format or size, but the absence of parameters and the explicitly informational nature make that gap 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?

The input schema has zero parameters, so there is nothing for the description to clarify beyond what the schema already shows. The baseline score of 4 applies because no parameter documentation is needed.

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 the tool as a prerequisite reading resource that explains table grain and common analytical traps, and explicitly says to read it before computing anything. It is not a tautology and it is clearly distinct from query tools, though it does not explicitly name or compare against sibling tools like document or worked_examples.

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 an explicit usage trigger: 'Read this before computing anything.' This tells the agent when the tool should be called relative to other data operations. However, it does not explain when not to use it or mention alternatives among the sibling tools.

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