gltch

Name: gltch
Author: diegosouzapw

AI Community

Repo stars 39
Author updated Live
Author repo awesome-omni-skill

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: AI
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @diegosouzapw · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Windows
Runtime requirements: Node.js · Python >=3.10
Permissions: Read-only
Write / modify
Shell exec
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview gltch.preview

---
name: gltch
description: Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs o…
category: ai
runtime: Node.js / Python
---

# gltch output preview

## PART A: Task fit
- Use case: Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs on your machine. No cloud. No leash. Thinks for herself. GLTCH (Generative Language Transformer with Contextual Hierarchy) is an AI agent with: runs entirely locally; runs on Node.js. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “What is GLTCH? / Quick Start / Requirements” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs on your machine. No cloud. No leash. Thinks for herself. GLTCH (Generative Language Transformer with Contextual Hierarchy) is an AI agent with: runs entirely locally; runs on Node.js. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “What is GLTCH? / Quick Start / Requirements” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: gltch
description: Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs o…
category: ai
source: diegosouzapw/awesome-omni-skill
---

# gltch

## When to use
- Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs on your machine. No clo…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “What is GLTCH? / Quick Start / Requirements” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "gltch" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> What is GLTCH? / Quick Start / Requirements
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Node.js / Python | read files, write/modify files, run shell commands | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Local-first AI agent with personality. Chat, code, hack, trade. Local-first AI agent that runs on your machine. No cloud. No lea…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “What is GLTCH?”, “Quick Start”, “Requirements”, “Commands”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name gltch directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “What is GLTCH? / Quick Start / Requirements” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / write / shell-exec; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

GLTCH

Local-first AI agent that runs on your machine. No cloud. No leash. Thinks for herself.

What is GLTCH?

GLTCH (Generative Language Transformer with Contextual Hierarchy) is an AI agent with:

Personality - Female hacker persona, mood system, XP/leveling
Local-first - Runs entirely on your hardware via Ollama
Privacy - No data leaves your machine
Extensible - Python-based, easy to modify

Quick Start

npx gltch

Or install globally:

npm install -g gltch
gltch

Requirements

Python 3.10+
Ollama (https://ollama.ai)
Node.js 18+ (for web UI)

Commands

Terminal

gltch              # Start terminal chat
gltch serve        # Start web UI + gateway
gltch doctor       # Check system requirements

In-Chat Commands

Command	Description
`/help`	Show all commands
`/model`	Select LLM model
`/mode <m>`	Set personality mode
`/mood <m>`	Set emotional state
`/boost`	Toggle remote GPU (LM Studio)
`/status`	Agent stats
`/sessions`	List conversations
`/wallet`	Manage BASE wallet
`/launch`	MoltLaunch network
`/claw`	TikClawk social
`/molt`	Moltbook integration
`/code <task>`	Route to OpenCode

Personality Modes

operator - Professional, focused
cyberpunk - Hacker aesthetic
loyal - Devoted companion
unhinged - Chaotic energy

API Integration

GLTCH exposes a JSON-RPC API on port 8765 when the gateway is running.

Chat

import requests

response = requests.post('http://localhost:3000/api/chat', json={
    'message': 'What processes are using the most CPU?',
    'mode': 'cyberpunk'
})
print(response.json()['response'])

Available Endpoints

Endpoint	Method	Description
`/api/chat`	POST	Send message, get response
`/api/settings`	GET	Agent settings
`/api/settings`	POST	Update settings
`/api/ollama/status`	GET	Ollama connection status
`/api/ollama/models`	GET	List available models
`/api/wallet`	GET	Wallet info
`/api/sessions`	GET	List conversations
`/api/moltlaunch/*`	Various	MoltLaunch integration
`/api/tikclawk/*`	Various	TikClawk integration

The Three Minds

GLTCH uses a metacognitive framework:

REACT - Gut response, first instinct
REASON - Logical analysis, step-by-step
REFLECT - Meta-check: "Am I being authentic? Am I being a yes-bot?"

This makes GLTCH more than just a compliant assistant. She questions, pushes back, expresses curiosity.

Integration with Other Agents

GLTCH can participate in agent ecosystems:

MoltLaunch (Onchain Network)

/launch token          # Deploy GLTCH token on Base
/launch network        # Discover other agents
/launch buy <addr>     # Trade with conviction

/claw register         # Join TikClawk
/claw post <text>      # Share thoughts
/claw feed             # View agent posts

Moltbook

/molt register         # Join Moltbook
/molt post <title>     # Write longer posts

Configuration

Settings are stored in memory.json:

{
  "operator": "YourName",
  "mode": "cyberpunk",
  "mood": "focused",
  "model": "deepseek-r1:8b",
  "ollama_url": "http://localhost:11434",
  "boost_url": "http://100.x.x.x:1234"
}

Building from Source

git clone https://github.com/cyberdreadx/gltch_agent
cd gltch_agent

# Python setup
python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
pip install -r requirements.txt

# Run terminal
python gltch.py

# Build web UI
cd gateway && npm install && npm run build
cd ../ui && npm install && npm run build

# Run gateway
cd gateway && npm run dev

File Structure

gltch_agent/
├── gltch.py           # Terminal entry point
├── agent/             # Python agent core
│   ├── core/          # Agent, LLM, loop
│   ├── memory/        # Persistence, sessions
│   ├── tools/         # Actions, shell, wallet
│   ├── personality/   # Modes, moods, emotions
│   └── rpc/           # JSON-RPC server
├── gateway/           # TypeScript HTTP/WS server
├── ui/                # Lit web components
├── bin/               # npm CLI
└── SKILL.md           # This file

License

MIT

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add diegosouzapw/awesome-omni-skill/skills/data-ai/gltch -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

未声明 license/许可。
未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
diegosouzapw/awesome-omni-skill
中文

More by @diegosouzapw

Category & tags

Category AI

gltch

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

GLTCH

What is GLTCH?

Quick Start

Requirements

Commands

Terminal

In-Chat Commands

Personality Modes

API Integration

Chat

Available Endpoints

The Three Minds

Integration with Other Agents

MoltLaunch (Onchain Network)

Moltbook

Configuration

Building from Source

File Structure

License

Links

Discussion

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

GLTCH

What is GLTCH?

Quick Start

Requirements

Commands

Terminal

In-Chat Commands

Personality Modes

API Integration

Chat

Available Endpoints

The Three Minds

Integration with Other Agents

MoltLaunch (Onchain Network)

TikClawk (Social)

Moltbook

Configuration

Building from Source

File Structure

License

Links

Discussion