The hooks performance finding matches what I've seen. I run multiple Claude Code agents in parallel on a remote VM and the first thing I learned was that anything blocking in the agent's critical path kills throughput. Even a few hundred milliseconds per hook call compounds fast when you have agents making dozens of tool calls per minute.
The docker-based service pattern is smart too. I went a different direction for my own setup -- tmux sessions with worktree isolation per agent, which keeps things lightweight but means I have zero observability into what each agent is actually doing beyond tailing logs manually. This solves that gap in a way that doesn't add overhead to the agent itself, which is the right tradeoff.
Curious about one thing -- how does the dashboard handle the case where a sub-agent spawns its own sub-agents? Does it track the full tree or just one level deep?
Sub-agent trees are fully tracked by the dashboard. When an agent is spawned, it always has a parent agent id - claude is sending this in the hooks payload. When you mouse over an agent in the dashboard, it shows what agent spawned it. There currently isn't a tree view of agents in the UI, but it would be easy to add. The data is all there.
[Edit] When claude spawns sub-agents, they inherit the parent's hooks. So all sub-agents activity gets logged by default.
Are you guys spending hundreds (or thousands) of dollars a day on Claude tokens? Holy crap. I can't get more than one or two agents to do anything useful for very long before I'm hitting my usage limits.
I hit a lot of limits on Pro plan. Upgraded to Max $200/mo plan and haven't hit limits for awhile.
It's super important to check your plugins or use a proxy to inspect raw prompts. If you have a lot of skills and plugins installed, you'll burn through tokens 5-10x faster than normal.
Also have claude use sub-agents and agent teams. They're significantly lighter on token usage when they're spawned with fresh context windows. You can see in Agents Observe dashboard exactly what prompt and response claude is using for spawning sub-agents.
the blocking hooks observation matches what I would expect -- anything synchronous in the critical path has multiplicative effect when agents run 20-30 tool calls per task. even a 100ms write per call adds 2-3 seconds to a task, and that compounds across parallel agents fast.
Good to know background hooks make that much of a difference. How are you handling the case where multiple agent teams are writing to the same jsonl files simultaneously?
I'm not actually reading the jsonl files. Agents Observe just uses hooks and sends all hook data the server (running as a docker container by default).
Basic flow:
1. Plugin registers hooks that call a dump pipe script that sends hook events data to api server
2. Server parses events and stores them in sqlite by session and agent id - mostly just stores data, minimal processing
3. Dashboard UI uses websockets to get real-time events from the server
4. UI does most of the heavy lifting by parsing events, grouping by agent / sub-agent, extracting out tool calls to dynamically create filters, etc.
It took a lot of iterations to keep things simple and performant.
You can easily modify the app/client UI code to fully customize the dashboard. The API app/server is intentionally unopinionated about how events will be rendered. This was by design to add support for other agent events soon.
The hooks approach seems much cleaner for real-time. Did you run into any issues with the blocking hooks degrading performance before you switched to background?
Sort of. It wasn't really noticeable until I did an intentional audit of performance, then noticed the speed improvements.
Node has a 30-50ms cold start overhead. Then there's overhead in the hook script to read local config files, make http request to server, and check for callbacks. In practice, this was about 50-60ms per hook.
The background hook shim reduces latency to around 3-5ms (10x improvement). It was noticeable when using agent teams with 5+ sub-agents running in parallel.
But the real speed up was disabling all the other plugins I had been collecting. It piles up fast and is easy for me to forget what's installed globally.
I've also started periodically asking claude to analyze it's prompts to look for conflicts. It's shockingly common for plugins and skills to end up with contradictory instructions. Opus works around it just fine, but it's unnecessary overhead for every turn.
Thanks! This was step one in my daily driver stack - better observability. I also bundled up a bunch of other observability services in https://github.com/simple10/agent-super-spy so I can see the raw prompts and headers.
The next big layer for my personal stack is full orchestration. Something like Paperclip but much more specialized for my use cases.
The hooks performance finding matches what I've seen. I run multiple Claude Code agents in parallel on a remote VM and the first thing I learned was that anything blocking in the agent's critical path kills throughput. Even a few hundred milliseconds per hook call compounds fast when you have agents making dozens of tool calls per minute.
The docker-based service pattern is smart too. I went a different direction for my own setup -- tmux sessions with worktree isolation per agent, which keeps things lightweight but means I have zero observability into what each agent is actually doing beyond tailing logs manually. This solves that gap in a way that doesn't add overhead to the agent itself, which is the right tradeoff.
Curious about one thing -- how does the dashboard handle the case where a sub-agent spawns its own sub-agents? Does it track the full tree or just one level deep?
Sub-agent trees are fully tracked by the dashboard. When an agent is spawned, it always has a parent agent id - claude is sending this in the hooks payload. When you mouse over an agent in the dashboard, it shows what agent spawned it. There currently isn't a tree view of agents in the UI, but it would be easy to add. The data is all there.
[Edit] When claude spawns sub-agents, they inherit the parent's hooks. So all sub-agents activity gets logged by default.
Are you guys spending hundreds (or thousands) of dollars a day on Claude tokens? Holy crap. I can't get more than one or two agents to do anything useful for very long before I'm hitting my usage limits.
I hit a lot of limits on Pro plan. Upgraded to Max $200/mo plan and haven't hit limits for awhile.
It's super important to check your plugins or use a proxy to inspect raw prompts. If you have a lot of skills and plugins installed, you'll burn through tokens 5-10x faster than normal.
Also have claude use sub-agents and agent teams. They're significantly lighter on token usage when they're spawned with fresh context windows. You can see in Agents Observe dashboard exactly what prompt and response claude is using for spawning sub-agents.
I'd bet there are many. I know a few teams with spends in the thousands of dollars per day. It sounds crazy, but not too unrealistic.
I've been having the same issue. It's such a shame because it is levels above the other AIs
Cool project. The React reconciler underneath Claude Code's terminal layer is a solid foundation for this kind of real-time rendering.
the blocking hooks observation matches what I would expect -- anything synchronous in the critical path has multiplicative effect when agents run 20-30 tool calls per task. even a 100ms write per call adds 2-3 seconds to a task, and that compounds across parallel agents fast.
th
Good to know background hooks make that much of a difference. How are you handling the case where multiple agent teams are writing to the same jsonl files simultaneously?
I'm not actually reading the jsonl files. Agents Observe just uses hooks and sends all hook data the server (running as a docker container by default).
Basic flow:
1. Plugin registers hooks that call a dump pipe script that sends hook events data to api server
2. Server parses events and stores them in sqlite by session and agent id - mostly just stores data, minimal processing
3. Dashboard UI uses websockets to get real-time events from the server
4. UI does most of the heavy lifting by parsing events, grouping by agent / sub-agent, extracting out tool calls to dynamically create filters, etc.
It took a lot of iterations to keep things simple and performant.
You can easily modify the app/client UI code to fully customize the dashboard. The API app/server is intentionally unopinionated about how events will be rendered. This was by design to add support for other agent events soon.
The hooks approach seems much cleaner for real-time. Did you run into any issues with the blocking hooks degrading performance before you switched to background?
Sort of. It wasn't really noticeable until I did an intentional audit of performance, then noticed the speed improvements.
Node has a 30-50ms cold start overhead. Then there's overhead in the hook script to read local config files, make http request to server, and check for callbacks. In practice, this was about 50-60ms per hook.
The background hook shim reduces latency to around 3-5ms (10x improvement). It was noticeable when using agent teams with 5+ sub-agents running in parallel.
But the real speed up was disabling all the other plugins I had been collecting. It piles up fast and is easy for me to forget what's installed globally.
I've also started periodically asking claude to analyze it's prompts to look for conflicts. It's shockingly common for plugins and skills to end up with contradictory instructions. Opus works around it just fine, but it's unnecessary overhead for every turn.
great idea. I am curious what the future of coding with multiple terminals and agents will look like and this looks like a great start!
Thanks! This was step one in my daily driver stack - better observability. I also bundled up a bunch of other observability services in https://github.com/simple10/agent-super-spy so I can see the raw prompts and headers.
The next big layer for my personal stack is full orchestration. Something like Paperclip but much more specialized for my use cases.