Dutify

pm_list_automations_for_folder

Read-onlyIdempotent

List automations scoped to a folder. Automations attached at folder level cascade to every list inside that folder unless overridden at the list level. API-key scope: automations:read.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "folderIdentifier": "<folderIdentifier>"
    },
    "name": "pm_list_automations_for_folder"
  }
}

Input Schema

Name	Required	Description
`account`	No	Multi-account auth only: name of the account from X-Dutify-Accounts to use for this call. Ignored in single-account mode (X-API-Key header). When multiple accounts are configured and this is omitted, the call fails with ACCOUNT_REQUIRED listing the available names. list_accounts never requires a selection.
`workspace`	No	Workspace identifier or exact name for this call. Overrides the configured workspace. For personal keys, discover candidates with list_workspaces and select explicitly. Does not change other calls or expand a workspace key's access.
`folderIdentifier`	Yes	Folder identifier (fld_…)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 24, 2026

TDQS

A4.4/5.0

Behavior4/5

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

The description adds specific behavioral details about API access control (API-key scope: `automations:read`), which is valuable context for a client agent. Since annotations are already provided (e.g., `readOnlyHint: true`), the description adds significant, non-redundant value regarding access rights.

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 two sentences are highly efficient. They front-load the core function and immediately follow with a crucial, advanced behavior (cascading logic), maximizing the information density without unnecessary padding.

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 covers the functional logic (listing automations) and the behavioral logic (cascading scope). While it doesn't mention return format or pagination, the annotations and schema fully cover the necessary operational details for invoking the tool correctly, making it nearly complete.

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?

Schema description coverage is 100%, meaning all parameter details are covered in the schema. The description adds no additional meaning beyond what the structured data already provides for parameters, thus meeting the baseline score.

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 purpose: to list automations scoped specifically to a folder. The phrasing 'scoped to a folder' distinguishes it immediately from sibling tools like `pm_list_automations_for_list` and `pm_list_automations_for_space`.

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 includes critical usage context by explaining the 'cascading' behavior of folder-level automations. This tells the AI exactly *when* it will see certain automations (and thus, when it won't) based on where it is operating relative to the list level.

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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