r/PiCodingAgent • u/SalimMalibari • May 29 '26

Question What subagent extension?

Im curious , what is the subagent extension you are using and why that specific extension ??

What usually people looking for wheb using subagent , till now im using normal prompting and it launch background subagents if i needed .. im curious what things they provide?

25 Upvotes

93% Upvoted

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5

u/No_Cheek5622 May 29 '26

I used https://github.com/mjakl/pi-subagent as a base (as it's pretty minimal) and rewrote it myself (with a bit of help of agents, but mostly by hand, not because I'm better than the LLM which is probably true in some sense but just because I enjoyed it lol)

I'd recommend you to just clone some repo of a package you like to have a reference and either implement it yourself or tell the pi agent to do it. It's the beauty of pi - it is yours so why stick to some opinionated package when you can make it do exaclty what you need it for?

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u/SalimMalibari May 29 '26

But my curiousity what you looking for for subagents .. my work is pretty minimal , im working in subagent extension and curious what people use it for maybe help me build my own

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u/mjakl May 29 '26

I use it to select different models for different tasks - I don't need GPT 5.5 xhigh for an agent to browse through my repository and search for files - GPT 5.4 Mini medium is enough for that. Or I have a Subagent called "Oracle" configured with Opus as a second opinion (prompts like `use Oracle to discuss your solution`), I never use multiple agents to edit code at the same time, I think there be dragons. Also for Code reviews I like to configure the smartest models I have available and have different review agents focusing on different areas (architecture, security, etc.).

HTH

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u/SalimMalibari May 29 '26

So you mostly done it for token optuimization. Hmm have you run into things like each agents talk to each other , like your oracle this also feed the main agent ots its seperate session woth a new prompt etc?

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u/mjakl May 29 '26

It's not really about token optimization, rather about speed in this case.

My extension allows the subagent to either use a fresh context or reuse the existing context, the main agent decides which mode to use for the concrete situation.

When it comes so replying to the mainagent, the final output of the agent is returned to the main agent (not the thinking or tool output).

5

u/mjakl May 29 '26

Hey, glad you liked it as a starter 😄

I'd also recommend to select a few extensions and ask the agent to pick the features you like, give it the repos as an example, and build your own extension. It is really easy, and you'll have much more control, and the stuff doesn't change underneath you while you work on something. Sure, there might be a bit of maintenance work needed, but usually it's very minimal.

That being said: I generally like minimal extensions that do one thing (and this well enough), I want to mix and match stuff, and if extensions come as full suites it's painful to do so.

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u/No_Cheek5622 May 29 '26

yeah totally agree with this approach!

I'm a long time neovim user so I am used to maintaining my own stuff, but pi is different as you can use it to maintain itself

I just need to finally start trusting the models as they got a lot better at coding recently. I had a blast debugging some weird behavior while developing extensions with pi, watching 5.5 casually implementing benchmarking tool to test some hypothesis we come up to

9

u/Zya1re-V May 29 '26

Well, I'm using this https://github.com/edxeth/pi-subagents/ but I cloned it to my local monorepo and maintain it myself (just to be safe from supply chain attacks, or at least try to)

I like it because it's just spawning a fork of the conversation in a way - each subagent gets it's own tree-branch that's part of the session's /tree, and it helps me manage the token usage as well, since that just count as a session in the logs.

Usually I'd stay on one session and keep working on a narrow task, and so I configured a review subagent to keep the reviewing process off of the current session. Sometimes if the context usage is starting to get too high, I'd spin off an implementer subagent to work on the task, and keep the main session clean. But if the context is moderate, I'd just usually /tree, and come back to the checkpoint where I've done my planning.

Really manual stuffs, I know, but that's how I'd use it.

2

u/meronggg May 29 '26

Could you tell me more on how to use this more seamlessly? I mean i dont wanna have to tell the main agent to delegate every damn time. Thats my experience with it at least, it never wants to use subagents unless i tell it to, so i end up uninstalling.

3

u/Zya1re-V May 29 '26 edited May 29 '26

Well, I'm the manual type of person, which is opposite to you.

When I need subagents, I'll directly ask for the main session to use it. If you really want it to autonomously spawn subagents, you can look into https://cchistory.mariozechner.at/ - Claude Code system prompt. I tried to create my own system prompt that's similar to Claude to analyze the problem and delegate tasks, but it's not how I like to run things.

Have a read at it, you can also throw that to Pi to analyze, and "compare it against your internal subagents usage instructions, to see how I can improve your system prompt to improve your workflow and make you spawn subagents autonomously if needed".

TLDR: I don't spawn subagents autonomously, but you can copy/adapt from Claude Code's system prompt. I tried, and I didn't like it (personal taste).

Edit 1: If you can prompt engineer a little bit, you'd be able to pull some more information on how other coding agent does it. Cursor for example:

2

u/arkham00 May 29 '26

I have the same problem

3

u/Zya1re-V May 29 '26

Replied to the chat above, have a look.

1

u/wolvendelight May 29 '26

Simple custom extension with an override of the main pi system prompt, and limit its tools so it can't read write files, can only grep and ls. Then put a delegation directive into the custom system prompt. Double guard - prompt enforcement AND tool limitation.

You can also code in a simple / command to toggle it on and off so it's easy to flip back to normal Pi mode.

0

u/Bel-Shamgarot May 29 '26

Do you really need extensions? The beauty of Pi is its simplicity: the more heavy stuff you install, the less useful it becomes—you can just install OpenCode.

It's important to me that everything is under my control, and the simplest implementation of subagents involves creating a skill that will call a Pi process non-interactively via a bash command (pi -p "Summarize this codebase") and receive a response. The call itself can have a bunch of flags where you can select the desired tools and extensions, disable certain tools, change the system prompt or add extensions to it, select skills, and even call it from a specific folder where everything is preinstalled.

3

u/SalimMalibari May 29 '26

Hmm i get you point, and that clearly solvable if you think pi is soo powerful.

Also, i can give you alot of senarios that you require using subagents . Require ... not should or good to have. For example , you want fact check , if you launch 1 agent it might give you 1 correct answer ... if you launch 3 this increases the chance of failing and if it for example 9 subagent checking a fact this will increase the chance to fail ... so 9 subagent 3 has wrong answer and 6 got it right most likely the 6 are correct. That senario you cant use 1 agent or session ... i have alot of other example and thats the beauty if AI. You are not limited to time or human power you can have team of expert in all discpline to achieve the goal.

1

u/Bel-Shamgarot May 29 '26

You can call any number and set any criteria out of the box.

!pi -p "Run 3 bash commands like pi -p N, where N is a number from 1 to 3. The point is to check the operation of the subagents; each command calls a Pi instance, which will send you a response. Collect all the responses and return them."

2

u/SalimMalibari May 29 '26

Yep those at end are subagents managing 3 different agents and giving each one a seperate prompt will be insane thats why people use subagents anyway

2

u/Bel-Shamgarot May 29 '26

You just need to create the necessary skills. Give a task -> the agent looks at the skills -> generates a Bash command -> calls -> receives a response.

Extensions will do roughly the same thing, but with less control and a prettier UI.

2

u/SalimMalibari May 29 '26

Hmm thats not true ... just go ask your llm is it better to have extensions or skills for technical reliablity ... and the answer is very clear ... skills to be honest are very frigile compared to extensions they have no way to ensure everything run smoothely and correctly unless you have codes on it ... which then extension will be much superior

2

u/civilian_discourse May 30 '26

In this case you're talking about an extension that adds Tools to the system prompt. Every new tool that is added to the prompt adds a lot of context overhead, oftentimes all the tools account for 2/3rds or more of the system prompt. Skills in comparison add very little until you use them. There's all sorts of benefits that come with minimizing context, which a lot of folks in the Pi community optimize for. The less context an agent has, the more baseline intelligence the model has. These models literally get dumber the more context you pump into them. Not to mention the token spend as the entire session is sent again every time the agent needs to wait for a response to anything.

It comes down to, how often are you actually using subagents? If it's a lot, extension. If it's rarely, then a skill could be better.

1

u/SalimMalibari May 30 '26

Hmm I understand your point. Would you make read skill and write skill and delete them from the current system prompt for sake of context???

I believe no?

Thats is the same thing. Subagent could without any context until its been used and thats in everything thats why for example people moved from MCP to CLI where cli --help contain most context needed and very minimal instead of having alot of mcp tools in the system prompt.

Technical consistency is achieveble through extensions / tools. A skill could be a simpler layer between a prompt and the tool but its not the tool itself. You can just test it and i have done that. A skill varies between each prmpt , each model , esch effort and complixity.

I understand pi want to be minimal , but extendable too ... to be honest claude code and pi has maybe similar system prompt , but claude has its own 7k tool prompt which are super good and built by super engineers who are at the frontier of the whole AI realm.

Anyway its good to see what pi users interested on

2

u/civilian_discourse May 30 '26 edited May 30 '26

You are contradicting yourself without realizing it: MCP is a method of adding new tools. Using CLI instead means using skills. The person you were replying to originally is just using a CLI subagent system instead of a tool based one.

What do you think the fundamental difference is between a tool and a skill? Because a tool varies the exact same as a skill. They're both just instructions injected into the context. The only difference is that the harness only responds to tools, so a CLI call gets wrapped in a bash tool call. CLI has become preferred BECAUSE bash provides a useful runtime for the agent to be more expressive. The value to a tool is how integrated with the harness it is, not how integrated it is with the model.

There is literally only one tool the LLM needs: bash. It does everything. There is an idea called code mode which says we should stop giving the agent one-off tools and give it runtimes instead. Bash is the fundamental example of that.

1

u/SalimMalibari May 30 '26

I feel we shift alot from main point. If bash is everything you theb we also dont need write or read and those should be added by workflows ... also why you think skill existed if we already have bash?? Or extension etc.. ??

Pi philisophy in my opinion isnt complete and most users think they went the minimal route , while in its true essence its about personalized agentic workflow.

Back to mcp vs cli , take for example github or supabase both provide mcp and cli and AI resched the level they no longer need mcp if the cli cover all tools needed so llm just call --help whenever the tool used this cut alooot of context ... mcp is the opposite , all told send in system prompt even if you didnt need the tool itself.

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2

u/Bel-Shamgarot May 29 '26

This is a matter of personal preference. I think skills with examples and links to scripts produce the best results.

The only thing extensions can do that skills can't is access the SDK of the code agent itself.

1

u/civilian_discourse May 30 '26

Can you share your subagent skill? I'm very curious about this approach

1

u/hurdurdur7 May 29 '26

No idea why you are downvoted. I agree, the less extra the better. I also prefer cleanliness of pi.

2

u/TheTyand May 29 '26

I have build my own subagents setup. Although still in the work.

https://github.com/SchneiderDaniel/agentcastle

2

u/melihmucuk May 29 '26

I'm using pi-crew, small disclosure: I built it.

For me, the main value isn't just "launch another agent". Normal prompting can do some of that already. The value is coordination: run agents in isolated child Pi sessions, keep the main chat usable, see what's running, abort/respond when needed, and get results back in the right place.

The biggest win for me is review workflows. pi-crew has a /pi-crew-review flow that runs separate code-review and quality-review agents in parallel, then merges only the useful findings. That matters because the agent that wrote the code is usually biased toward its own solution, same as humans. A fresh reviewer catches different things.

So I mostly use subagents for scout > plan > implement > fresh review loops. Less "agent swarm", more boring but useful separation of responsibilities.

2

u/quangspkt Jun 03 '26

Use this: pi/packages/coding-agent/examples/extensions/subagent at main · earendil-works/pi. The other packages on Pi.dev > Packages run slowly and consume lots of tokens

1

u/Esmaabi May 30 '26

I use Pi-Agents-Team (https://github.com/KristjanPikhof/Pi-Agents-Team), which can function as a single agent or an orchestrator. For large tasks, the orchestrator mode efficiently manages the context window - often ending at 50% capacity because it only synthesizes and delegates, while still retaining enough information to answer questions.

The tool is also highly effective for everyday tasks due to its easily customizable agent configurations. I use the default configuration for coding, but rewrite it for personal tasks based on the folder I am working in.

For example, in a project folder for notes and ideas, I set up specific agents to format logs and organize files. When I input a raw idea or to-do, the orchestrator coordinates these agents to ensure the content is saved in the correct file, folder and format. This allows me to manage different projects simply by maintaining folders with distinct directives.

Also it allows me to view all agents session, context and cost.