parse_dmarc_report

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

The description goes beyond annotations by explaining that reports are parsed in-memory and not stored, and that no auth is needed. It details the output structure (metadata, policy, per-source rows) which is valuable for understanding 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 concise yet comprehensive, covering purpose, output, input, and use case in a logical flow. Every sentence adds value without redundancy.

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 the absence of an output schema, the description provides sufficient detail about the output structure. It also covers input options, side-effect profile, and use case, making it complete for an agent to decide when and how to use the 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?

Both parameters are fully described in the schema, and the description clarifies that they are alternative ways to provide the report (raw XML vs. base64 gzip). It adds practical guidance on usage and limits, making the parameters unambiguous.

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 that the tool parses DMARC aggregate XML reports into structured JSON. It distinguishes itself from sibling tools that perform scans or tests by explicitly focusing on reading and parsing reports.

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?

It explicitly states when to use the tool: to programmatically read DMARC reports fetched from the rua@ mailbox. It also provides practical notes like parsing in-memory, no authentication required, and no side effects, giving clear guidance on context and constraints.

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