agenticx-quickstart

agenticx-quickstart is a skill for Claude Code, Codex from opencue/cuecards. It costs 64 tokens per session (825 once invoked), scanned A, a copy of agenticx-quickstart, MIT.

A beginner’s guide to installing AgenticX and creating a first AI agent or workflow. AgenticX is a Python framework for building software agents that perform tasks.

In plain words
What is it for?
Use it to install AgenticX, create a project, configure language-model access, build an agent, run tasks, and learn the command-line basics.
Why use it?
It provides the setup and first examples needed to move from an empty environment to a working project.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to install AgenticX, create a project, configure language-model access, build an agent, run tasks, and learn the command-line basics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opencue/cuecards/agenticx-quickstart
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add opencue/cuecards --skill agenticx-quickstart
Clone the repo
git clone --depth 1 https://github.com/opencue/cuecards

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agenticx-quickstart

README.md
[![agentmods](https://agentmods.dev/badge/skills/opencue/cuecards/agenticx-quickstart/github.svg)](https://agentmods.dev/skills/opencue/cuecards/agenticx-quickstart)
Your own site
<a href="https://agentmods.dev/skills/opencue/cuecards/agenticx-quickstart"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/agenticx-quickstart/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agenticx-quickstart

Your own site · 80×15
<a href="https://agentmods.dev/skills/opencue/cuecards/agenticx-quickstart"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/agenticx-quickstart.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 825 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.00825
Opus 5.5 $0.00026 $0.00330
Sonnet 5.5 $0.00013 $0.00165
Haiku 4.5 $0.00006 $0.00082

Measured 1mo ago against content hash f9c90b0588e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agenticx-quickstart scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to agenticx-quickstart — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/agenticx-quickstart/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AgenticX Quickstart

Guide for getting a user from zero to a running AgenticX agent in under 5 minutes.

Installation

# Core install (lightweight, ~27 deps, installs in seconds)
pip install agenticx

# Verify
agx --version

Optional extras — install only what you need:

Extra What it adds Command
memory Mem0, ChromaDB, Qdrant pip install "agenticx[memory]"
document PDF/PPT/Word parsing pip install "agenticx[document]"
server API server (agx serve) pip install "agenticx[server]"
volcengine Volcengine AgentKit pip install "agenticx[volcengine]"
all Everything pip install "agenticx[all]"

Environment

export OPENAI_API_KEY="sk-..."
# Optional
export ANTHROPIC_API_KEY="sk-ant-..."

Create a Project

agx project create my-first-agent --template basic
cd my-first-agent
agx project info

Create Your First Agent (Python)

from agenticx import Agent, Task, AgentExecutor
from agenticx.llms import OpenAIProvider

agent = Agent(
    id="data-analyst",
    name="Data Analyst",
    role="Data Analysis Expert",
    goal="Help users analyze and understand data",
    organization_id="my-org"
)

task = Task(
    id="analysis-task",
    description="Analyze sales data trends",
    expected_output="Detailed analysis report"
)

llm = OpenAIProvider(model="gpt-4")
executor = AgentExecutor(agent=agent, llm=llm)
result = executor.run(task)
print(result)

Create via CLI

# Scaffold an agent
agx agent create researcher --role "Senior Research Analyst"
agx agent list

# Scaffold a workflow
agx workflow create research-pipeline --agents "researcher"

# Run it
agx run workflows/research-pipeline.py --verbose

Add Tools

from agenticx.tools import tool

@tool
def calculate_sum(x: int, y: int) -> int:
    """Calculate the sum of two numbers."""
    return x + y

# Pass tools when creating agent or executor

Read the full file on GitHub · 122 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 122 lines · 64 tokens per session scan A f9c90b0588e9

Subscribe to this mod's changes

agenticx-quickstart is a skill published in the GitHub repository opencue/cuecards (6 stars, last pushed yesterday), licensed MIT. It adds 64 tokens to every session and 825 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agenticx-quickstart, differing in 2 lines, and is treated as a copy.

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