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Npcsh

the composable multi-agent shell

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Install / Use

/learn @NPC-Worldwide/Npcsh
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<p align="center"> <a href="https://github.com/npc-worldwide/npcsh/blob/main/docs/npcsh.md"> <img src="https://raw.githubusercontent.com/NPC-Worldwide/npcsh/main/npcsh/npcsh.png" alt="npcsh logo" width=600></a> </p> <h1 align="center">npcsh</h1> <p align="center"> <strong>The agentic shell for building and running AI teams from the command line.</strong> </p> <p align="center"> <a href="https://github.com/npc-worldwide/npcsh/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a> <a href="https://pypi.org/project/npcsh/"><img src="https://img.shields.io/pypi/v/npcsh.svg" alt="PyPI"></a> <a href="https://pypi.org/project/npcsh/"><img src="https://img.shields.io/pypi/pyversions/npcsh.svg" alt="Python"></a> <a href="https://npc-shell.readthedocs.io/"><img src="https://img.shields.io/badge/docs-readthedocs-brightgreen.svg" alt="Docs"></a> </p>

npcsh makes the most of multi-modal LLMs and agents through slash commands and interactive modes, all from the command line. Build teams of agents, schedule them on jobs, engineer context, and design custom Jinja Execution templates (Jinxes) for you and your agents to invoke.

pip install 'npcsh[lite]'

Once installed, run npcsh to enter the NPC shell. Also provides the CLI tools npc, wander, spool, yap, and nql.

.npc and .jinx files are directly executable with shebangs (#!/usr/bin/env npc):

npc ./myagent.npc "summarize this repo"     # run an NPC with a prompt
npc ./script.jinx bash_command="ls -la"     # run a jinx directly
./myagent.npc "hello"                       # or just execute it (with shebang)

Benchmark Results

How well can a model drive npcsh as an agentic shell? 125 tasks across 15 categories — from basic shell commands to multi-step workflows, code debugging, and tool chaining — scored pass/fail. Comparisons with other agent coders coming soon. For a more comprehensive view of npcsh's capabilities and the advantages of the NPC Context-Agent-Tool data layer, check out ALARA for Agents: Least-Privilege Context Engineering Through Portable Composable Multi-Agent Teams

<table> <tr><th>Family</th><th>Model</th><th>Score</th></tr> <tr><td rowspan="5"><b>Qwen3.5</b></td><td>0.8b</td><td>31/125 (24%)</td></tr> <tr><td>2b</td><td>81/125 (65%)</td></tr> <tr><td>4b</td><td>77/125 (62%)</td></tr> <tr><td>9b</td><td><b>100/125 (80%)</b></td></tr> <tr><td>35b</td><td><b>111/125 (88%)</b></td></tr> <tr><td rowspan="5"><b>Qwen3</b></td><td>0.6b</td><td>—</td></tr> <tr><td>1.7b</td><td>42/125 (34%)</td></tr> <tr><td>4b</td><td><b>94/125 (75%)</b></td></tr> <tr><td>8b</td><td>85/125 (68%)</td></tr> <tr><td>30b</td><td><b>103/125 (82%)</b></td></tr> <tr><td rowspan="4"><b>Gemma3</b></td><td>1b</td><td>—</td></tr> <tr><td>4b</td><td>37/125 (30%)</td></tr> <tr><td>12b</td><td>77/125 (62%)</td></tr> <tr><td>27b</td><td>73/125 (58%)</td></tr> <tr><td rowspan="3"><b>Llama</b></td><td>3.2:1b</td><td>—</td></tr> <tr><td>3.2:3b</td><td>26/125 (20%)</td></tr> <tr><td>3.1:8b</td><td>60/125 (48%)</td></tr> <tr><td rowspan="2"><b>Mistral</b></td><td>small3.2</td><td>72/125 (57%)</td></tr> <tr><td>ministral-3</td><td>51/125 (40%)</td></tr> <tr><td><b>Phi</b></td><td>phi4</td><td>58/125 (46%)</td></tr> <tr><td><b>GPT-OSS</b></td><td>20b</td><td>94/125 (75%)</td></tr> <tr><td rowspan="2"><b>OLMo2</b></td><td>7b</td><td>13/125 (10%)</td></tr> <tr><td>13b</td><td>47/125 (38%)</td></tr> <tr><td><b>Cogito</b></td><td>3b</td><td>10/125 (8%)</td></tr> <tr><td><b>GLM</b></td><td>4.7-flash</td><td><b>102/125 (82%)</b></td></tr> <tr><td rowspan="3"><b>Gemini</b></td><td>2.5-flash</td><td>—</td></tr> <tr><td>3.1-flash</td><td>—</td></tr> <tr><td>3.1-pro</td><td>—</td></tr> <tr><td rowspan="2"><b>Claude</b></td><td>4.6-sonnet</td><td>—</td></tr> <tr><td>4.5-haiku</td><td>—</td></tr> <tr><td><b>GPT</b></td><td>5-mini</td><td>—</td></tr> <tr><td rowspan="2"><b>DeepSeek</b></td><td>chat</td><td>—</td></tr> <tr><td>reasoner</td><td>—</td></tr> </table> <details><summary><b>Category breakdown (completed models)</b></summary> <table> <tr> <th rowspan="2">Category</th> <th colspan="4">Qwen3.5</th> <th colspan="5">Qwen3</th> <th colspan="3">Gemma3</th> <th>Llama</th> <th colspan="2">Mistral</th> <th>Phi</th> <th>GPT-OSS</th> <th>Cogito</th> <th>GLM</th> </tr> <tr> <th>0.8b</th><th>2b</th><th>9b</th><th>35b</th> <th>1.7b</th><th>4b</th><th>8b</th><th>30b</th><th>0.6b</th> <th>4b</th><th>12b</th><th>27b</th> <th>3.2:3b</th> <th>small3.2</th><th>ministral-3</th> <th>phi4</th> <th>20b</th> <th>3b</th> <th>4.7-flash</th> </tr> <tr><td>shell (10)</td><td>5</td><td>6</td><td>10</td><td>10</td><td>8</td><td>8</td><td>9</td><td>9</td><td>—</td><td>6</td><td>6</td><td>9</td><td>6</td><td>10</td><td>7</td><td>9</td><td>10</td><td>0</td><td>10</td></tr> <tr><td>file-ops (10)</td><td>8</td><td>9</td><td>10</td><td>10</td><td>8</td><td>10</td><td>9</td><td>10</td><td>—</td><td>6</td><td>9</td><td>10</td><td>2</td><td>6</td><td>10</td><td>10</td><td>10</td><td>0</td><td>10</td></tr> <tr><td>python (10)</td><td>0</td><td>3</td><td>9</td><td>10</td><td>0</td><td>5</td><td>6</td><td>6</td><td>—</td><td>0</td><td>3</td><td>1</td><td>0</td><td>3</td><td>6</td><td>4</td><td>10</td><td>0</td><td>10</td></tr> <tr><td>data (10)</td><td>0</td><td>2</td><td>4</td><td>6</td><td>2</td><td>4</td><td>5</td><td>6</td><td>—</td><td>1</td><td>5</td><td>7</td><td>0</td><td>5</td><td>9</td><td>4</td><td>6</td><td>0</td><td>5</td></tr> <tr><td>system (10)</td><td>2</td><td>8</td><td>9</td><td>10</td><td>7</td><td>9</td><td>7</td><td>10</td><td>—</td><td>5</td><td>9</td><td>7</td><td>2</td><td>9</td><td>6</td><td>6</td><td>9</td><td>0</td><td>10</td></tr> <tr><td>text (10)</td><td>1</td><td>7</td><td>6</td><td>8</td><td>2</td><td>10</td><td>6</td><td>7</td><td>—</td><td>3</td><td>9</td><td>8</td><td>1</td><td>7</td><td>0</td><td>4</td><td>8</td><td>0</td><td>7</td></tr> <tr><td>debug (10)</td><td>2</td><td>6</td><td>10</td><td>10</td><td>0</td><td>4</td><td>2</td><td>10</td><td>—</td><td>0</td><td>3</td><td>0</td><td>0</td><td>4</td><td>0</td><td>0</td><td>9</td><td>0</td><td>9</td></tr> <tr><td>git (10)</td><td>0</td><td>8</td><td>6</td><td>9</td><td>2</td><td>9</td><td>9</td><td>8</td><td>—</td><td>4</td><td>6</td><td>9</td><td>4</td><td>8</td><td>4</td><td>6</td><td>8</td><td>0</td><td>5</td></tr> <tr><td>multi-step (10)</td><td>0</td><td>6</td><td>7</td><td>6</td><td>0</td><td>6</td><td>3</td><td>7</td><td>—</td><td>3</td><td>5</td><td>5</td><td>2</td><td>3</td><td>0</td><td>5</td><td>4</td><td>0</td><td>5</td></tr> <tr><td>scripting (10)</td><td>1</td><td>5</td><td>8</td><td>10</td><td>0</td><td>7</td><td>2</td><td>6</td><td>—</td><td>0</td><td>2</td><td>1</td><td>0</td><td>3</td><td>1</td><td>3</td><td>7</td><td>0</td><td>8</td></tr> <tr><td>image-gen (5)</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>—</td><td>3</td><td>5</td><td>3</td><td>5</td><td>5</td><td>1</td><td>2</td><td>5</td><td>5</td><td>5</td></tr> <tr><td>audio-gen (5)</td><td>5</td><td>4</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>5</td><td>—</td><td>4</td><td>5</td><td>5</td><td>4</td><td>5</td><td>1</td><td>5</td><td>5</td><td>5</td><td>5</td></tr> <tr><td>web-search (5)</td><td>1</td><td>5</td><td>4</td><td>5</td><td>1</td><td>5</td><td>4</td><td>5</td><td>—</td><td>1</td><td>5</td><td>5</td><td>0</td><td>4</td><td>5</td><td>0</td><td>3</td><td>0</td><td>5</td></tr> <tr><td>delegation (5)</td><td>0</td><td>2</td><td>3</td><td>3</td><td>0</td><td>2</td><td>2</td><td>4</td><td>—</td><td>0</td><td>2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3</td></tr> <tr><td>tool-chain (5)</td><td>1</td><td>5</td><td>4</td><td>4</td><td>2</td><td>5</td><td>2</td><td>5</td><td>—</td><td>1</td><td>3</td><td>3</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>5</td></tr> <tr><td><b>Total (125)</b></td><td><b>31</b></td><td><b>81</b></td><td><b>100</b></td><td><b>111</b></td><td><b>42</b></td><td><b>94</b></td><td><b>76</b></td><td><b>103</b></td><td>—</td><td><b>37</b></td><td><b>77</b></td><td><b>73</b></td><td><b>26</b></td><td><b>72</b></td><td><b>51</b></td><td><b>58</b></td><td><b>94</b></td><td><b>10</b></td><td><b>102</b></td></tr> </table> </details> 
python -m npcsh.benchmark.local_runner --model qwen3:4b --provider ollama

Usage

  • Get help with a task:

    npcsh>can you help me identify what process is listening on port 5337?

  • Edit files:

    npcsh>please read through the markdown files in the docs folder and suggest changes

  • Search & Knowledge

    /web_search "cerulean city"            # Web search
/db_search "query"                     # Database search
/file_search "pattern"                 # File search
/memories                              # Interactive memory browser TUI
/kg                                    # Interactive knowledge graph TUI
/nql                                   # Database query TUI
    <p align="center"> <img src="gh_images/Screenshot%20from%202026-01-29%2015-02-52.png" alt="Web search results", width=600> </p>

  • Computer Use

    /computer_use
    <p align="center"> <img src="gh_images/plonk.png" alt="Plonk GUI automation TUI" width=500> <img src="gh_images/plonk_task.png" alt="Plonk GUI automation — completed task" width=500> </p>

  • Generate Images

    /vixynt 'generate an image of a rabbit eating ham in the brink of dawn' model='gpt-image-1' provider='openai'
    <p align="center"> <img src="https://raw.githubusercontent.com/npc-worldwide/npcsh/main/test_data/rabbit.PNG" alt="a rabbit eating ham in the brink of dawn", width=350> </p>

  • Generate Videos

    /roll 'generate a video of a hat riding a dog' veo-3.1-fast-generate-pre

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NPC-Worldwide

View profile

View on GitHub
GitHub Stars266
CategoryDevelopment
Updated1d ago
Forks16
NPC-Worldwide/npcsh

Languages

Python

Security Score

95/100

Audited on Mar 29, 2026

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