appendix-agentic-frameworks

appendix-agentic-frameworks is a skill for Claude Code, Codex from hajekim/agentic-design-patterns-extension. It costs 412 tokens per session (3,650 once invoked), scanned A, a copy of appendix-agentic-frameworks, MIT.

A comparison guide to agent frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, LlamaIndex, and Haystack.

In plain words
What is it for?
Use it to compare frameworks, choose one for a new agent system, and learn the main workflow and state-management approaches each provides.
Why use it?
These frameworks organize AI-agent workflows in different ways, so the guide helps match one to a linear, cyclical, team-based, or data-heavy project.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/hajekim/agentic-design-patterns-extension/appendix-agentic-frameworks
Any agent
npx skills add hajekim/agentic-design-patterns-extension --skill appendix-agentic-frameworks
Clone the repo
git clone --depth 1 https://github.com/hajekim/agentic-design-patterns-extension

Made for: Claude Code, Codex.

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README.md
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Per session 412 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,650 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00412 $0.03650
Opus 5 $0.00206 $0.01825
Sonnet 5 $0.00082 $0.00730
Haiku 4.5 $0.00041 $0.00365

Measured 4d ago against content hash 1cef80579caf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

appendix-agentic-frameworks 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 4d 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 appendix-agentic-frameworks — 3 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.

skills/appendix-agentic-frameworks/SKILL.md · 375 lines

How it starts

The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Appendix C - Quick Overview of Agentic Frameworks

Overview

The Agentic Frameworks landscape provides developers with structured tools for building, orchestrating, and deploying AI agents. Each framework operates at a different level of abstraction and optimizes for different design priorities — understanding their trade-offs is essential for building reliable, maintainable agent systems.

This appendix provides a comparative overview of the major frameworks: LangChain, LangGraph, Google ADK, CrewAI, Microsoft AutoGen, LlamaIndex, and Haystack — when to use each, their core abstractions, and key code patterns.

Core Principle: No framework is universally best — choose based on whether your workflow is linear (LangChain), cyclical (LangGraph), team-based (ADK/CrewAI), or data-intensive (LlamaIndex).

Framework Comparison Matrix

Framework Core Abstraction Workflow Type State Management Best For
LangChain Chain (LCEL) Linear DAG Stateless per run Simple pipelines, RAG, extraction
LangGraph Graph of nodes Cyclical + loops Explicit, persistent Complex agents, tool loops, HITL
Google ADK Agent team Orchestrated multi-agent Implicit (framework) Production multi-agent systems
CrewAI Agent + Task + Crew Sequential/hierarchical Role-based Team simulation, research workflows
AutoGen Conversational agents Conversation-driven Conversational Dynamic multi-agent conversations
LlamaIndex Data pipeline RAG-focused Index-based Knowledge-intensive agents, RAG
Haystack Pipeline nodes Modular search Search-optimized Enterprise search, QA systems

When This Skill Applies

Activate this framework selection guide when:

  • Starting a new agent project and choosing the technology stack
  • Migrating from one framework to another
  • Debugging framework-specific behavior or limitations
  • Combining multiple frameworks in a hybrid architecture
  • Evaluating build-vs-buy for agentic infrastructure

Read the full file on GitHub · 375 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. 4d ago First seen · 375 lines · 412 tokens per session scan A 1cef80579caf

Subscribe to this mod's changes

appendix-agentic-frameworks is a skill published in the GitHub repository hajekim/agentic-design-patterns-extension (1 stars, last pushed 5mo ago), licensed MIT. It adds 412 tokens to every session and 3,650 once invoked, about $0.0021 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to appendix-agentic-frameworks, differing in 3 lines, and is treated as a copy.