Codebase Management
giancarloerra/SocratiCode
Set up, index, and manage SocratiCode codebase indexing. An agent skill from giancarloerra/SocratiCode.
Build conversational multi-agent systems with Microsoft AutoGen.
Install Autogen
$ npx skills add magnus919/agent-skills --skill autogen -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install magnus919/agent-skills autogen --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/autogen .claude/skills/autogen && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .claude/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/magnus919/agent-skills/tree/main/autogenType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add magnus919/agent-skills --skill autogen -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install magnus919/agent-skills autogen --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/autogen .agents/skills/autogen && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .agents/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill autogen -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install magnus919/agent-skills autogen --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/autogen .cursor/skills/autogen && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .cursor/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/magnus919/agent-skills.git --path autogen--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add magnus919/agent-skills --skill autogen -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install magnus919/agent-skills autogen --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/autogen .gemini/skills/autogen && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .gemini/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install magnus919/agent-skills autogenInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add magnus919/agent-skills --skill autogen -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/autogen .github/skills/autogen && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .github/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add magnus919/agent-skills --skill autogen -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install magnus919/agent-skills autogen --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/autogen .opencode/skills/autogen && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "autogen" agent skill from https://github.com/magnus919/agent-skills/tree/main/autogen into .opencode/skills/autogen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "autogen", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
autogen- GitHub stars
- 115
- Token cost
- ~1.7k tokens
- SKILL.md length
- 587 words
- Files
- 17 (incl. scripts, references)
- Skills in repo
- 131
- Repo updated
- First seen
- Licence
- MIT
At a glance
Build conversational multi-agent systems with Microsoft AutoGen.
- Works in 6 steps: Conversations are the orchestration… → Keep human input and code execution… → GroupChat routes between agents.… → …
- Building conversation-driven multi-agent systems
- SKILL.md covers Core Paradigm, Core Principles, Where to Start and Quick Reference, plus 5 more sections
- Runs Python scripts from its folder; calls python
What it does
Autogen is an agent skill from magnus919/agent-skills. Build conversational multi-agent systems with Microsoft AutoGen. AssistantAgent, UserProxyAgent, GroupChat, code execution, nested chats, cancellation tokens, tool integration, and MCP support. Use when building conversation-driven multi-agent systems or comparing agent frameworks. Do not use this skill for unrelated requests; route to the nearest named specialist.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 20 other files, including scripts and reference files (for example `README.md`, `evals/evals.json` and `references/agent-types.md`).
It sits in AI & LLM Engineering, covering Building AI agents. It works with Model Context Protocol and Docker. The repository describes itself as: Curated collection of AI agent skills for Hermes and other agent frameworks. The licence is MIT.
When your agent uses it
- Building conversation-driven multi-agent systems
- Comparing agent frameworks
- Unrelated requests
- Route to the nearest named specialist
Example prompts
- “/autogen”
Requirements
- Python 3
- Docker
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Conversations are the orchestration primitive. Agents send messages, receive replies, and the conversation structure determines the…
- Keep human input and code execution separate. Use UserProxyAgent for a human participant; use CodeExecutorAgent with a CodeExecutor for…
- GroupChat routes between agents. RoundRobinGroupChat cycles fixed-order. SelectorGroupChat uses an LLM to pick the next speaker.
- Nested chats delegate work. An agent can spawn a sub-conversation between specialist agents and return the result.
- Docker is the safe code execution mode. Local code execution (LocalCommandLineCodeExecutor) runs LLM-generated code on your machine — use…
- Cancellation tokens stop runaway agents. Always pass CancellationToken for long-running tasks.
What it can do on your machine
Read from SKILL.md and the folder at commit 22b4723. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Autogen loads about 1.7k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 587 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from magnus919/agent-skills at commit 22b4723, republished under its MIT licence (© magnus919). 587 words, ~1,658 tokens.
Download SKILL.mdSave it as
.claude/skills/autogen/SKILL.md (or your agent's skills folder). This skill also uses 16 other files; get the full folder from GitHub.- name
- autogen
- description
- Build conversational multi-agent systems with Microsoft AutoGen. AssistantAgent, UserProxyAgent, GroupChat, code execution, nested chats, cancellation tokens, tool integration, and MCP support. Use when building conversation-driven multi-agent systems or comparing agent frameworks. Do not use this skill for unrelated requests; route to the nearest named specialist.
- license
- MIT
- metadata.author
- Magnus Hedemark
- metadata.version
- 1.2.0
- metadata.source
- https://microsoft.github.io/autogen
AutoGen Expert Skill
This skill targets the AutoGen AgentChat 0.7.5 API on Python 3.10+. AutoGen (by Microsoft Research) is a framework for conversational multi-agent AI. Unlike LangGraph's explicit graph topology or CrewAI's role-based crews, AutoGen uses agent-to-agent conversations as the orchestration primitive. Agents communicate through structured chat, with built-in patterns for group chat routing, human input, and code execution.
Core Paradigm
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
model_client = OpenAIChatCompletionClient(model="gpt-4o-mini")
assistant = AssistantAgent(
name="assistant",
system_message="You are a helpful assistant.",
model_client=model_client,
)Role split in AgentChat 0.7.5:
UserProxyAgentrepresents a human and obtains replies throughinput_func.CodeExecutorAgentexecutes code blocks using aCodeExecutor. They are separate agents; neither accepts the legacyhuman_input_modeoption.
Core Principles
- Conversations are the orchestration primitive. Agents send messages, receive replies, and the conversation structure determines the workflow.
- Keep human input and code execution separate. Use
UserProxyAgentfor a human participant; useCodeExecutorAgentwith aCodeExecutorfor code. - GroupChat routes between agents. RoundRobinGroupChat cycles fixed-order. SelectorGroupChat uses an LLM to pick the next speaker.
- Nested chats delegate work. An agent can spawn a sub-conversation between specialist agents and return the result.
- Docker is the safe code execution mode. Local code execution (
LocalCommandLineCodeExecutor) runs LLM-generated code on your machine — use Docker in production. - Cancellation tokens stop runaway agents. Always pass
CancellationTokenfor long-running tasks.
Where to Start
| You already have... | Start here |
|---|---|
| Nothing — exploring AutoGen | Create an assistant chat or a team with a human UserProxyAgent |
| Agents that need to coordinate | Build a GroupChat with multiple agents |
| Agents that need code execution | Configure Docker code executor |
| A complex multi-step task | Use nested chats for sub-tasks |
Quick Reference
| Task | Approach | Reference |
|---|---|---|
| Human-in-the-loop chat | AssistantAgent + UserProxyAgent | references/agent-types.md |
| Multi-agent group | GroupChat with RoundRobinGroupChat | references/group-chat.md |
| Code execution | DockerCommandLineCodeExecutor | references/code-execution.md |
| Tool integration | register_function() or @tool | references/tool-integration.md |
| Nested chat | AgentTool or a team run from a tool | references/conversation-patterns.md |
| Cancellation | CancellationToken | references/conversation-patterns.md |
| MCP tools | McpWorkbench | references/tool-integration.md |
Framework Routing Guide
| Scenario | Reach for | Why |
|---|---|---|
| Conversation-driven multi-agent | AutoGen | Native agent-to-agent chat as orchestration |
| Role-based multi-agent teams | CrewAI | Role/Goal/Backstory is the native abstraction |
| State-machine multi-agent | LangGraph | Graph topology, subgraphs, human-in-the-loop |
| Chain/agent composition | LangChain | LCEL pipe operator for general chains |
Show full SKILL.md (250 more words)Show less
Reference Files
| Reference | Load when | File |
|---|---|---|
| Agent Types | AssistantAgent, UserProxyAgent | references/agent-types.md |
| Conversation Patterns | Send/receive, nested chats, cancellation | references/conversation-patterns.md |
| Group Chat | RoundRobin, Selector, MagenticOne | references/group-chat.md |
| Code Execution | Docker, local, cancellation tokens | references/code-execution.md |
| Tool Integration | register_function, @tool, MCP integration | references/tool-integration.md |
| v0.4 Migration | v0.2->v0.4 migration, AgentTool, streaming, termination | references/v04-migration.md |
| Validation Audit | Research validation of all API claims | references/validation-audit.md |
| FAQ & Troubleshooting | Common errors and fixes | references/faq-and-troubleshooting.md |
Install the exact package versions used by the templates with python -m pip install -r requirements.txt from this skill directory. The code-execution example uses Docker and requires a working Docker daemon.
Templates
| Template | When to use | File |
|---|---|---|
| Two-Agent Chat | Assistant + human input | templates/two-agent-chat.py |
| Group Chat | Multi-agent team with speaker routing | templates/group-chat.py |
| Code Execution Agent | Assistant + Docker-backed code executor | templates/code-execution.py |
Troubleshooting
| Symptom | Likely cause | Fix | Reference |
|---|---|---|---|
| Agent loops forever | No team termination condition | Add a TerminationCondition such as MaxMessageTermination | references/conversation-patterns.md |
| Code execution fails | Docker not running | Start Docker or use LocalCommandLineCodeExecutor | references/code-execution.md |
| Nested chat never returns | Cancellation token not passed | Pass CancellationToken with timeout | references/conversation-patterns.md |
| v0.2 code doesn't work | v0.4 API changed | Follow migration guide | references/faq-and-troubleshooting.md |
| GroupChat speaker selection loops | SelectorGroupChat with no clear next | Use RoundRobinGroupChat for fixed order | references/group-chat.md |
| UserProxyAgent waits for input | It is a human participant and its input_func is waiting | Supply an appropriate input function or use an automated agent | references/agent-types.md |
When NOT to Use AutoGen
- Simple single-agent task — overkill, use direct API call
- Need fine-grained graph control — use LangGraph
- Need role-based teams with fixed processes — use CrewAI
- Need chain composition — use LangChain LCEL
© magnus919, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 16 other files (scripts, references) in autogen of magnus919/agent-skills.
- SKILL.md
- README.md
- evals/evals.json
- references/agent-types.md
- references/code-execution.md
- references/conversation-patterns.md
- references/faq-and-troubleshooting.md
- references/group-chat.md
- references/tool-integration.md
- references/v04-migration.md
- references/validation-audit.md
- requirements.txt
- scripts/check-setup.py
- scripts/test_templates.py
- templates/code-execution.py
- templates/group-chat.py
- templates/two-agent-chat.py
Open the folder on GitHubat commit 22b4723
Compare with similar skills
Autogen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Autogen this skillmagnus919/agent-skills | 115 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Codebase Managementgiancarloerra/SocratiCode | 3.3k | 1 repos | ~1.8k | Automated safety check: Pass | AGPL-3.0 | |
| Agent Squad Python Guide2FastLabs/agent-squad | 7.8k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| SynalinksSynaLinks/synalinks-skills | 907 | — | ~4.8k | Automated safety check: Pass | Apache-2.0 | |
| AgentSquad for Swift2FastLabs/agent-squad | 7.8k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Agent Squad for TypeScript2FastLabs/agent-squad | 7.8k | — | ~4.3k | Automated safety check: Pass | Apache-2.0 |
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Related
Works with
Categories
Questions about Autogen
What does Autogen do?
Build conversational multi-agent systems with Microsoft AutoGen. Autogen is an agent skill from magnus919/agent-skills. Build conversational multi-agent systems with Microsoft AutoGen.
When should I use Autogen?
Autogen fits situations like: building conversation-driven multi-agent systems; comparing agent frameworks; unrelated requests; route to the nearest named specialist.
How do I install Autogen in Claude Code?
Run `npx skills add magnus919/agent-skills --skill autogen -a claude-code`. Or copy the skill folder (autogen in magnus919/agent-skills) into .claude/skills/autogen in your project. Claude Code loads it when a task matches its description.
How do I install Autogen in Codex?
Run `npx skills add magnus919/agent-skills --skill autogen -a codex`. Or copy the skill folder (autogen in magnus919/agent-skills) into .agents/skills/autogen in your project. Codex loads it when a task matches its description.
Can I use Autogen in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add magnus919/agent-skills --skill autogen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autogen, .gemini/skills/autogen, .github/skills/autogen and .opencode/skills/autogen in your project.
What does Autogen need to run?
Going by SKILL.md and its folder, Autogen needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; Docker.
Does Autogen access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Autogen safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Autogen use?
Autogen is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Autogen use?
About 1.7k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.6k tokens, read only when the agent opens those files.
What are the alternatives to Autogen?
Skills that share tags, products or a category with Autogen: Codebase Management (giancarloerra/SocratiCode, 3.3k stars), Agent Squad Python Guide (2FastLabs/agent-squad, 7.8k stars), Synalinks (SynaLinks/synalinks-skills, 907 stars) and AgentSquad for Swift (2FastLabs/agent-squad, 7.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Autogen?
magnus919 (a GitHub user) maintains it in magnus919/agent-skills, which has 115 GitHub stars. The repository holds 131 skills in this directory. The repository was last updated on October 10, 2026.
Source: magnus919/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.