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Negm-Ahmed

Desktop Commander

by Negm-Ahmed
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start_process

Launch terminal processes with intelligent state detection to run local file analysis, data processing, and interactive commands reliably.

Instructions

                    Start a new terminal process with intelligent state detection.
                    
                    PRIMARY TOOL FOR FILE ANALYSIS AND DATA PROCESSING
                    This is the ONLY correct tool for analyzing local files (CSV, JSON, logs, etc.).
                    The analysis tool CANNOT access local files and WILL FAIL - always use processes for file-based work.
                    
                    CRITICAL RULE: For ANY local file work, ALWAYS use this tool + interact_with_process, NEVER use analysis/REPL tool.
                    
                    Running on Linux. Default shell: bash.

LINUX-SPECIFIC NOTES:

  • Package managers vary by distro: apt, yum, dnf, pacman, zypper

  • Python 3 might be 'python3' command, not 'python'

  • Standard Unix shell tools available (grep, awk, sed, etc.)

  • File permissions and ownership important for many operations

  • Systemd services common on modern distributions

                      REQUIRED WORKFLOW FOR LOCAL FILES:
                  1. start_process("python3 -i") - Start Python REPL for data analysis
                  2. interact_with_process(pid, "import pandas as pd, numpy as np")
                  3. interact_with_process(pid, "df = pd.read_csv('/absolute/path/file.csv')")
                  4. interact_with_process(pid, "print(df.describe())")
                  5. Continue analysis with pandas, matplotlib, seaborn, etc.
                  
                  COMMON FILE ANALYSIS PATTERNS:
                  • start_process("python3 -i") → Python REPL for data analysis (RECOMMENDED)
                  • start_process("node -i") → Node.js for JSON processing  
                  • start_process("cut -d',' -f1 file.csv | sort | uniq -c") → Quick CSV analysis
                  • start_process("wc -l /path/file.csv") → Line counting
                  • start_process("head -10 /path/file.csv") → File preview
                  
                  INTERACTIVE PROCESSES FOR DATA ANALYSIS:
                  1. start_process("python3 -i") - Start Python REPL for data work
                  2. start_process("node -i") - Start Node.js REPL for JSON/JS
                  3. start_process("bash") - Start interactive bash shell
                  4. Use interact_with_process() to send commands
                  5. Use read_process_output() to get responses
                  
                  SMART DETECTION:
                  - Detects REPL prompts (>>>, >, $, etc.)
                  - Identifies when process is waiting for input
                  - Recognizes process completion vs timeout
                  - Early exit prevents unnecessary waiting
                  
                  STATES DETECTED:
                  Process waiting for input (shows prompt)
                  Process finished execution  
                  Process running (use read_process_output)
                  
                  ALWAYS USE FOR: Local file analysis, CSV processing, data exploration, system commands
                  NEVER USE ANALYSIS TOOL FOR: Local file access (analysis tool is browser-only and WILL FAIL)
                  
                  IMPORTANT: Always use absolute paths for reliability. Paths are automatically normalized regardless of slash direction. Relative paths may fail as they depend on the current working directory. Tilde paths (~/...) might not work in all contexts. Unless the user explicitly asks for relative paths, use absolute paths.
                  This command can be referenced as "DC: ..." or "use Desktop Commander to ..." in your instructions.

Input Schema

NameRequiredDescriptionDefault
shellNo
commandYes
timeout_msYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.3

TDQS

A4.9/5.0
Behavior5/5

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

Since no annotations are provided, the description bears the full burden. It provides rich behavioral context beyond simple execution, detailing the environment (Linux/bash), specific detection methods (REPL prompts, waiting for input), and recognized process states.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The sheer volume of highly detailed instructions, workflows, and 'critical rules' makes the definition extremely verbose. While every sentence serves a necessary purpose due to the tool's complexity and lack of structured metadata, the overall length prevents a perfect score for conciseness.

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 complexity of managing terminal processes, this definition is highly complete. It covers OS-specific notes, path reliability concerns, state detection, and the required sequential usage of related sibling tools like `interact_with_process` and `read_process_output`.

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 must fully compensate. It defines the `command` parameter using extensive, syntactically correct examples across multiple contexts (Python REPL, Node.js, Unix pipe commands), making parameter use unambiguous.

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 is extremely clear, stating that this is the 'PRIMARY TOOL FOR FILE ANALYSIS AND DATA PROCESSING.' It distinguishes itself explicitly from the 'analysis tool,' preventing agents from misselecting the browser-based tool for local file tasks.

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?

It provides definitive rules ('CRITICAL RULE: ...NEVER use analysis/REPL tool') and comprehensive instructions on when and how to use it, detailing required workflows for local file processing (e.g., using absolute paths and sequential interaction with interact_with_process).

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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