analyze_email

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

Without annotations, the description carries the full burden. It discloses the output (forensic verdict with SPF/DKIM/DMARC, IP reputation, etc.) and input format, but does not mention side effects, storage, auth requirements, or statelessness. This leaves some behavioral gaps.

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?

Description is concise (two sentences), front-loads the purpose, and every sentence adds value. No wasted words.

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 one parameter, no output schema, and no annotations, the description covers input, process, and output adequately. It lacks prerequisites or error conditions but is complete enough for the tool's complexity.

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 coverage is 100% with one parameter fully described. The description adds meaning by clarifying that the 'email' parameter accepts raw headers or full RFC 2822 email, which goes beyond the schema's minimal description.

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?

Description clearly states the tool's purpose: analyzing emails for phishing, spoofing, and authentication failures. It specifies acceptable input formats (raw headers or full RFC 2822) and distinguishes from sibling tools (get_analysis, list_analyses) by focusing on performing a new analysis rather than retrieving existing ones.

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 implies using this tool when you have an email to analyze, but it does not explicitly state when to use it versus alternatives. No exclusions or when-not-to-use guidance is provided, leaving the agent to infer from sibling names.

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