AutoSwarm: All Your Agents, Working as One (2.0k stars)
What it does
All text below is quoted directly from the project README.
>AutoSwarm: All Your Agents, Working as One (Codex · Claude Code · DeepSeek Harness · Muse · Grok · WorkBuddy· nanobot · and more)
Why AutoSwarm?:
- Selects the right agents based on their capabilities;
- Shares context and memory across agents;
- Connects complementary tools and workflows;
- Bridges data and application ecosystems;
- Runs tasks in parallel for faster execution;
- Coordinates agent collaboration and keeps everyone aligned;
- Verifies and synthesizes results into one coherent answer.
>Use AutoSwarm to read these 100 documents and summarize the key approaches and disagreements.
Repository
HKUDS/AutoSwarm
Repository stats
|Metric|Value|
|:-|:-|
|Stars|2,042|
|Forks|370|
|Last release|None|
|Languages|Python 87.9%, TypeScript 9.7%, CSS 2.2%|
|Contributors|9|
|AI contributor accounts (Claude / Codex / Cursor / Copilot)|None|
|AI co-authored commits|Claude: 40, Cursor: 1|
Main contributor
|Field|Value|
|:-|:-|
|GitHub|@LZH-YS1998|
|Commits to this repo|106 (top contributor)|
|Followers|87|
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44 points · 1 comment
手头 Codex、Claude Code、Grok 各干各的，切换还得重复讲需求？
AutoSwarm 是多 agent 协调层：任务交一次，它按能力挑 agent、共享上下文，最后合成一个结果。
同时用好几个 agent 的话，统一入口比来回切换省事。
先拿它协调哪两个 agent？
#多Agent #开源 @grok
HKUDS/AutoSwarm
3 likes · 1 repost · 137 views
手头 Codex、Claude Code、Grok 各干各的，切换还得重复讲需求？
AutoSwarm 是多 agent 协调层：任务交一次，它按能力挑 agent、共享上下文，最后合成一个结果。
同时用好几个 agent 的话，统一入口比来回切换省事。
先拿它协调哪两个 agent？
#多Agent #开源 @grok
HKUDS/AutoSwarm
5 likes · 222 views
AutoSwarm: Automating Agent Swarms
Large language model (LLM) agents increasingly automate complex tasks, with multi-agent systems seeking further performance gains through specialization and collaboration. However, distributing work across agents does not automatically yield complementary contributions, and inter-agent dependencies can turn local errors into task failure. To address these challenges, we propose AutoSwarm, a multi-agent framework for collaborative problem solving. Collaboration formation jointly defines responsibility boundaries and conditions for acceptance and downstream use, grounding capability allocation in contributions that other agents can assess and integrate toward a shared objective. Execution coordination couples agents' local progress through a shared state, using dependencies and supervisory relationships to govern agent activation, result handoffs, and integration while adapting subsequent actions to review feedback and emerging blockers. Experiments spanning long-horizon programming, interactive planning, and professional financial analysis demonstrate AutoSwarm's advantages over single-agent baselines and existing multi-agent frameworks. Source code is available at HKUDS/AutoSwarm.
Mentions
AutoSwarm: All Your Agents, Working as One (2.0k stars) What it does All text below is quoted directly from the project README. >AutoSwarm: All Your Agents, Working as One (Codex · Claude Code · DeepSeek Harness · Muse · Grok · WorkBuddy· nanobot · and more) Why AutoSwarm?: - Selects the right agents based on their capabilities; - Shares context and memory across agents; - Connects complementary tools and workflows; - Bridges data and application ecosystems; - Runs tasks in parallel for faster execution; - Coordinates agent collaboration and keeps everyone aligned; - Verifies and synthesizes results into one coherent answer. >Use AutoSwarm to read these 100 documents and summarize the key approaches and disagreements. Repository HKUDS/AutoSwarm Repository stats |Metric|Value| |:-|:-| |Stars|2,042| |Forks|370| |Last release|None| |Languages|Python 87.9%, TypeScript 9.7%, CSS 2.2%| |Contributors|9| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|None| |AI co-authored commits|Claude: 40, Cursor: 1| Main contributor |Field|Value| |:-|:-| |GitHub|@LZH-YS1998| |Commits to this repo|106 (top contributor)| |Followers|87| ────────────────────────────── 📌 How many great GitHub repos have you discovered and completely forgotten about? Don't let another useful tool disappear into your Reddit feed. Get the community's best repos, organized by category, plus key takeaways from real developer discussions, delivered to your inbox twice a week. 📬 Never lose track of great repos again. Subscribe free.
手头 Codex、Claude Code、Grok 各干各的，切换还得重复讲需求？ AutoSwarm 是多 agent 协调层：任务交一次，它按能力挑 agent、共享上下文，最后合成一个结果。 同时用好几个 agent 的话，统一入口比来回切换省事。 先拿它协调哪两个 agent？ #多Agent #开源 @grok HKUDS/AutoSwarm
手头 Codex、Claude Code、Grok 各干各的，切换还得重复讲需求？ AutoSwarm 是多 agent 协调层：任务交一次，它按能力挑 agent、共享上下文，最后合成一个结果。 同时用好几个 agent 的话，统一入口比来回切换省事。 先拿它协调哪两个 agent？ #多Agent #开源 @grok HKUDS/AutoSwarm
AutoSwarm: Automating Agent Swarms Large language model (LLM) agents increasingly automate complex tasks, with multi-agent systems seeking further performance gains through specialization and collaboration. However, distributing work across agents does not automatically yield complementary contributions, and inter-agent dependencies can turn local errors into task failure. To address these challenges, we propose AutoSwarm, a multi-agent framework for collaborative problem solving. Collaboration formation jointly defines responsibility boundaries and conditions for acceptance and downstream use, grounding capability allocation in contributions that other agents can assess and integrate toward a shared objective. Execution coordination couples agents' local progress through a shared state, using dependencies and supervisory relationships to govern agent activation, result handoffs, and integration while adapting subsequent actions to review feedback and emerging blockers. Experiments spanning long-horizon programming, interactive planning, and professional financial analysis demonstrate AutoSwarm's advantages over single-agent baselines and existing multi-agent frameworks. Source code is available at HKUDS/AutoSwarm.