read_email

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool reads email content, which implies no modification, but it does not explicitly confirm that it is non-destructive or mention any side effects (e.g., marking as read). It also does not describe behavior for invalid UIDs, missing folders, or rate limits. The description provides a useful fact about UID persistence but does not cover the tool's operational behavior.

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 exactly two sentences with no wasted words. It front-loads the core purpose ('Read email content using UIDs') and then adds a practical note about UID persistence and sourcing. This is concise and well-organized, earning a high score.

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 simple two-parameter tool with no output schema, the description covers the essential usage: it explains the input (UIDs), the source of that input, and the purpose. However, it does not mention error handling (e.g., invalid UIDs, non-existent folder) or the structure of returned content. Given the lack of annotations and output schema, a bit more detail about expected outcomes or failure modes would improve completeness, but the core usage is adequately covered.

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 both parameters, giving a baseline of 3. The description adds value by explaining what UIDs are (permanent identifiers) and how to obtain them, which clarifies the semantic meaning beyond the schema's basic 'Array of UIDs' description. However, it does not add details on format (e.g., integer range, array length constraints) or edge cases, so it meets the baseline without exceeding it.

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 states the tool reads email content using UIDs and differentiates from siblings by mentioning that UIDs are permanent and obtained from list_emails or search_emails. It specifies the resource (email content) and the action (read), which distinguishes it from listing, searching, or mutating tools.

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 a direct usage hint ('Get UIDs from list_emails or search_emails') which establishes the source of the required input. It implies the tool is for reading full content rather than listing metadata, but it does not explicitly state when to avoid using it or compare with alternative tools beyond the UID sourcing. The context is clear enough for an agent to infer the intended use case.

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