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Totally-Harmless

DingusMail

extract_eml_attachments

Extract attachments from .eml email files and organize them into folders by type: small files, documents, images, and other attachments. Supports custom output directory and zip creation.

Instructions

Extract attachments from .eml file with smart organization.

Organizes files into folders:

  • small_files/: Files <10KB (icons, signatures, etc.)

  • documents/: PDFs, Word docs, spreadsheets, presentations

  • images/: All image files (inline + regular)

  • attachments/: Everything else

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filepathYesPath to the .eml file
organizeNoWhether to organize into subfolders (default: True)
create_zipNoCreate a zip file of all extracted content (default: False)
output_dirNoDirectory to extract to (default: "eml_extracted")eml_extracted

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 clearly discloses the side effect of creating folders and categorizing files (e.g., small_files/, documents/). It also specifies size thresholds and that inline images are included, providing useful behavioral context beyond the name.

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 concise and well-structured: a single lead sentence followed by a bulleted list. Every sentence provides unique value, and the formatting improves scannability without redundancy.

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

Completeness4/5

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

The description adequately covers the core extraction and organization behavior, especially given an output schema exists to document return values. It lacks some edge-case context (e.g., overwrite behavior, permissions) but is sufficient for a straightforward extraction tool.

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

Parameters4/5

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

Input schema covers 100% of parameters, but the description adds meaningful semantics for the `organize` parameter by detailing the exact folder structure and file categories. This enriches the schema's generic 'organize into subfolders' description, raising the score above the baseline 3.

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: "Extract attachments from .eml file" with a specific verb and resource. It further distinguishes itself from the sibling tool parse_eml by focusing on attachments and providing a unique "smart organization" feature.

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

Usage Guidelines3/5

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

The description implies usage for extracting attachments from .eml files but provides no explicit guidance on when to prefer this tool over parse_eml. There are no exclusions or alternative tool comparisons, so the context is only implied.

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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