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create_list

Creates a named list of items to enable parallel processing across multiple files, URLs, or strings. Returns a list ID for use with batch shell commands or AI agents.

Instructions

Creates a named list of items for parallel processing. Use this tool when you need to perform the same operation across multiple files, URLs, or any collection of items.

WHEN TO USE:

  • Before running shell commands or AI agents across multiple items

  • When you have a collection of file paths, URLs, identifiers, or any strings to process in parallel

WORKFLOW:

  1. Call create_list with your array of items

  2. Use the returned list_id with run_shell_across_list or run_agent_across_list

  3. The list persists for the duration of the session

EXAMPLE: To process files ["src/a.ts", "src/b.ts", "src/c.ts"], first create a list, then use run_shell_across_list or run_agent_across_list with the returned id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesArray of items to store in the list. Each item can be a file path, URL, identifier, or any string that will be substituted into commands or prompts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description bears the full burden. It states that the list persists for the session duration and returns a list_id, but does not disclose potential side effects, idempotency, maximum list size, or error conditions. This is adequate but not comprehensive.

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 with clear sections (WHEN TO USE, WORKFLOW, EXAMPLE). Every sentence contributes meaningful information, and the most important purpose is front-loaded.

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?

Given the tool's simplicity (1 param, no output schema, no annotations), the description covers the purpose, usage guidelines, and workflow with an example. However, it does not explicitly describe the return value structure (e.g., list_id), though it is implied in the workflow. Slightly incomplete.

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?

The input schema has 100% coverage with a description for the 'items' parameter. The description adds value by explaining that each item can be a file path, URL, identifier, or any string for substitution in commands, which goes beyond the schema description. Could be more precise about constraints.

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

Purpose4/5

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

The description clearly states 'Creates a named list of items for parallel processing', indicating the verb and resource. However, it mentions a 'named list' but the input schema only has an 'items' parameter, not a name. It distinguishes from siblings like create_list_from_shell by stating it takes an array of items, but could be more explicit.

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 a 'WHEN TO USE' section specifying usage before running shell commands or AI agents across multiple items, and a 'WORKFLOW' with clear steps. It references sibling tools (run_shell_across_list, run_agent_across_list) as subsequent steps, providing excellent guidance.

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