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Get Email Folder Tree

emailfolders_get_tree
Read-onlyIdempotent

Recursively build a tree of mail folders to understand the mailbox folder structure and organization.

Instructions

📖 Recursively build a tree of mail folders (read-only, safe for unsupervised use)

Returns a hierarchical tree structure showing all folders and their nested children. Useful for understanding mailbox folder organization.

Args: account_id: Microsoft account ID parent_folder_id: Root folder to start from (None = root) max_depth: Maximum recursion depth to prevent infinite loops (1-25, default: 10) include_hidden: Whether to include hidden folders (default: False)

Returns: Nested tree structure with folders and their children

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idYes
parent_folder_idNo
max_depthNo
include_hiddenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

The description explicitly confirms read-only behavior ('safe for unsupervised use'), matching annotations. It adds valuable behavioral context: recursion with depth control (max_depth 1-25), handling of parent folder as root, and hidden folder inclusion. This goes beyond what annotations (readOnlyHint, idempotentHint) convey.

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 well-structured with an emoji for quick scanning, a one-line summary, then clearly labeled Args and Returns sections. Every sentence adds value, with no unnecessary repetition. It is front-loaded with the key purpose and safety note.

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 presence of an output schema (not shown but confirmed), the description sufficiently explains what the tool does, its parameters, and the hierarchical return. It addresses safety (read-only), recursion limits, and hidden folder control, making it complete for an AI agent to use correctly.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by detailing each parameter: account_id, parent_folder_id (None=root), max_depth (1-25, default 10), include_hidden (default False). This adds critical meaning beyond the bare schema types and defaults.

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 verb ('Recursively build'), resource ('tree of mail folders'), and scope ('read-only, safe for unsupervised use'). It effectively distinguishes the tree-building functionality from sibling tools like emailfolders_list (likely flat) and emailfolders_get (single folder).

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

Usage Guidelines4/5

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

The description notes the tool is 'useful for understanding mailbox folder organization,' which implies a hierarchical exploration use case. However, it does not explicitly specify when to avoid this tool in favor of alternatives (e.g., emailfolders_list for flat listing or emailfolders_get for a single folder). The guidance is clear but lacks exclusion criteria.

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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