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create_list_from_shell

Run any shell command and generate a list from its newline-delimited output, enabling parallel batch processing of files or command results.

Instructions

Creates a list by running a shell command and parsing its newline-delimited output.

WHEN TO USE:

  • When you need to create a list from command output (e.g., find, ls, grep, git ls-files)

  • When the list of items to process is determined by a shell command

  • As an alternative to manually specifying items in create_list

EXAMPLES:

  • "find src -name '*.ts'" to get all TypeScript files

  • "git ls-files '*.tsx'" to get all tracked TSX files

  • "ls *.json" to get all JSON files in current directory

  • "grep -l 'TODO' src/**/*.ts" to get files containing TODO

WORKFLOW:

  1. Call create_list_from_shell with your command

  2. The command's stdout is split by newlines to create list items

  3. Empty lines are filtered out

  4. Use the returned list_id with run_shell_across_list or run_agent_across_list

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commandYesShell command to run. Its stdout will be split by newlines to create list items. Example: 'find src -name "*.ts"' or 'git ls-files'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Despite no annotations, the description details behavior: runs command, splits stdout by newlines, filters empty lines, returns list_id. Lacks mention of error handling or permissions, but covers key aspects well.

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?

Description is well-organized with sections, examples, and a workflow. Every sentence adds value; no fluff or repetition.

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 no output schema and no annotations, the description fully explains the tool's purpose, usage, behavior, and return value. Complete for a single-parameter 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?

Schema has 100% coverage with description for the single parameter. Description adds context through examples and explanation of its role in creating list items, exceeding baseline.

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 it creates a list by running a shell command and parsing newline-delimited output. It distinguishes from sibling 'create_list' by specifying the method (shell command vs manual specification).

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?

Explicit 'WHEN TO USE' section lists appropriate scenarios and directly contrasts with 'create_list' as an alternative. Provides examples and a workflow, giving clear guidance.

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