I've made a few attempts at manually doing this w/ mcp and took a brief look at "claude swarm" https://github.com/parruda/claude-swarm - but in the short time I spent on it I wasn't having much success - admittedly I probably went a little too far into the "build an entire org chart of agents" territory
the main problem I have is that the agents just aren't used
For example, I set up a code reviewer agent today and then asked claude to review code, and it went off and did it by itself without using the agent
in one of anthropic's own examples they are specifically telling claude which agents to use which is exactly what I don't want to have to do:
> First use the code-analyzer sub agent to find performance issues, then use the optimizer sub agent to fix them
My working theory is that while Claude has been extensively trained on tool use and is often eager to use whatever tools are available, agents are just different enough that they don't quite fit - maybe asking another agent to do something "feels" very close to asking the user to do something, which is counter to their training
but maybe I just haven't spent enough time trying it out and tweaking the descriptions
It contains 100+ specialized agents covering the most requested development tasks - frontend, backend, DevOps, AI/ML, code review, debugging, and more. All subagents follow best practices and are maintained by the open-source framework community.
Just copy to .claude/agents/ in your project to start using them.
I wonder if this is also a good way to create experts for specific tasks/features of a codebase.
For example, a sub-agent for adding a new stat to an RPG. It could know how to integrate with various systems like items, character stats component, metrics, and so on without having to do as much research into the codebase patterns.
This is great. I hope that they expose the configuration through the SDK, but right now it works with Crystal (https://github.com/stravu/crystal) if you configure them in the CLI.
I'm working on a proper config screen for them that just modifies the agent files directly, and a future release will also give special formatting for agent output.
One nice realization I had when using a similar feature in roo:
You don't need a full agent library to write LLM workflows.
Rather: A general purpose agent with a custom addition to the system prompt can be instructed to call other such agents.
(Of course explicitly mamaging everything is the better choice depending on your business case. But i think it would be always cheaper to at least build a prototype using this method.)
It says they can be "fine tuned," but it looks like the agents are all using the same model with different system prompts? This would be more intriguing if they trained a debugger model from the ground up that could be used for the debugger agent. I suspect we'll get there eventually.
Claude Code introduces specialized sub-agents
(docs.anthropic.com)161 points by tekkertje 25 July 2025 | 62 comments
Comments
the main problem I have is that the agents just aren't used
For example, I set up a code reviewer agent today and then asked claude to review code, and it went off and did it by itself without using the agent
in one of anthropic's own examples they are specifically telling claude which agents to use which is exactly what I don't want to have to do:
> First use the code-analyzer sub agent to find performance issues, then use the optimizer sub agent to fix them
My working theory is that while Claude has been extensively trained on tool use and is often eager to use whatever tools are available, agents are just different enough that they don't quite fit - maybe asking another agent to do something "feels" very close to asking the user to do something, which is counter to their training
but maybe I just haven't spent enough time trying it out and tweaking the descriptions
It contains 100+ specialized agents covering the most requested development tasks - frontend, backend, DevOps, AI/ML, code review, debugging, and more. All subagents follow best practices and are maintained by the open-source framework community. Just copy to .claude/agents/ in your project to start using them.
For example, a sub-agent for adding a new stat to an RPG. It could know how to integrate with various systems like items, character stats component, metrics, and so on without having to do as much research into the codebase patterns.
I'm working on a proper config screen for them that just modifies the agent files directly, and a future release will also give special formatting for agent output.
¹ https://github.com/ruvnet/claude-flow
You don't need a full agent library to write LLM workflows.
Rather: A general purpose agent with a custom addition to the system prompt can be instructed to call other such agents.
(Of course explicitly mamaging everything is the better choice depending on your business case. But i think it would be always cheaper to at least build a prototype using this method.)