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Totally-Harmless

DingusMail

parse_eml

Parse .eml files to extract email metadata, content, and attachment info for preview. Keeps attachment bytes unread and works offline to avoid trackers.

Instructions

Parse an .eml file and return metadata, content, and attachment info.

Does NOT extract attachment bytes - use extract_eml_attachments for that. Perfect for previewing what's in an email without bloat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYesPath to the .eml file

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait—that attachment bytes are not extracted—and clarifies the return scope (metadata, content, attachment info). While it doesn't mention error conditions or file access details, it sufficiently explains what the tool does and does not do for a read-only parsing operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise: two sentences that front-load the core purpose, then add the critical caveat and a use-case recommendation. Every word earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no nested objects) and the presence of an output schema, the description provides complete context: what it returns, what it excludes, and when to use it. The sibling tool is also clearly differentiated, making the description sufficient for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers the single parameter with 100% coverage, providing a clear description ('Path to the .eml file'). The tool description does not add further parameter-specific semantics, but the schema already does the heavy lifting, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Parse an .eml file and return metadata, content, and attachment info.' It also distinguishes itself from the sibling tool by explicitly noting it does NOT extract attachment bytes, making its scope unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage direction: 'Perfect for previewing what's in an email without bloat.' It also tells the user when not to use it and points to the alternative tool: 'Does NOT extract attachment bytes - use extract_eml_attachments for that.'

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

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