analyze_raw_email

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

The annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond that: the request body is processed in-memory and not stored, no authentication is required, and the analysis includes external checks such as IP reputation. This fully supports and reinforces the annotation hints.

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 tightly written. The opening sentence immediately communicates purpose and scope, the second sentence defines the parameter, and the final sentence gives usage guidance and a safety guarantee. No sentence is wasted.

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 carries the full burden of explaining what the tool returns. It does so clearly: parsed verdicts, reputation checks, spam triggers, a 0-100 score, and AI-assisted suggestions. It also includes relevant caveats like max size, in-memory processing, no auth, and when to prefer the sibling tool.

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 rawEmail thoroughly, including type, required flag, and max length, so the schema coverage is 100%. The description adds mild reinforcement by stating that rawEmail must contain full headers and body and by repeating the 500KB limit, but it does not add substantive meaning beyond the schema.

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 specifies a clear verb and resource: read-only analysis of a pasted raw RFC-5322 MIME email source. It enumerates concrete parsed elements and outputs (verdicts, reputation/blacklist status, spam score, fix suggestions). It also distinguishes itself from create_email_test by naming when each should be used.

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?

Explicitly states when to use this tool: debug a specific failing email when the user can paste raw source. It also names the alternative: use create_email_test when the user can resend the email. This is clear and directly actionable.

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