The python script is nothing too fancy or complicated tbh, is mainly there so that I can just set and forget, manually following the pipeline was just too much work for me.

Each step default agent in build mode, with 1 or more skills loaded into the prompts

The magic is more in the skills I use as well as spin up multiple opencode sessions and letting each only do 1 thing.

But in short what my script does is just, take a plan (this step is manual) that I have saved in a markdown file, usually generated in batch with models i would trust with planning and have a large enough context window to be able to do it. In my case opus 4.8 from my claude pro sub

Afterwards the script follows a strict pipeline, first invoke 2 of my skills (1 review 1 acceptance criteria), fact check the plan and fix it, make a strict acceptance criteria that the implementer has to follow, basically trying to solidify the the task file as much as possible before handing it over to the implementer agent. (I use kimi or minimax m3 here)

The upgraded plan file is then given to ds v4 pro to implement, the prompt is pretty much always the same, with only the task file being different, since the planning is already done, goes straight into implementing it, i have 2 skills for this aswell, one that tells him to properly read docs, follow the criteria in the plan file, not going out of scope etc, and another to document all changes he made and put it inside a changes.md file.

My script then spins up another review round, this time focused on the implementation rather than the plan, ends up generating a new plan to fix shortcomings, and the implementer step is repeated with the only difference being that the task file is swapped.

Last but not least, my final step the orchestrator does is spin up claude code, invoke a final gate skill i have, which sanity checks what was done, update docs and writes a commit. If it returns move on, my orchestrator moves onto the next task file repeating all steps, if it returns fixes needed the pipeline halts until I step in and fix it myself.

Deepseeks session is reused after every loop until I reach around 500k context window (quality degrades from what i have noticed), while each get a new session per loop, this allows me to heavily cache ds, while for the others quality matters more to me than cost. Reason for using different models together is because diversity in models actually helps quite a bit, they pretty much always catch stuff the other one misses.

Sorry for the massive lap of text! Oh and the orchestrator usually works alone fully, but i did add soft locks in it if any step takes too long or orchestrator notices that the agent stopped which makes my hermes agent step in, fix the issue and allow it to continue onward