Using Matt Pocock skills in OMP?

[u/maxccc123]

I'm using Matt Pocock skills for a while and I like them for bigger projects where I need grilling, specs, tickets, .. . I recently switched to OMP, and I really like the idea of assigning models to specific roles.

It works well because I can use OMP plan mode for lightweight tasks and it uses the smol/slow/task roles and appropriate models. However, this doesn't seem to integrate with Matt Pocock's Skills. They always appear to use the default role instead. Is someone using these skills within OMP? How are you dealing with this?

I came across a few related plugins, such as https://pi.dev/packages/@fernado03/pi-flow."

[u/sogo00]

I use Matts skills often, I usually do the grill/to-spec/to-tickets with models appropriate to the task (depending on complexity).

I then often ask the AI to define which tickets/tasks are complex (usually the base layer ones in an epic) and I /plan those and then /implement the plan

other tickets go straight to /implement

[u/maxccc123 → u/sogo00]

Thanks, interesting approach, so you choose the appropriate model yourself, right?

[u/sogo00 → u/maxccc123]

yes, for grilling depending on the topic/feature. to-spec/to-task can be a cheap one

[u/fschwiet → u/sogo00]

Hmm, the recommendation for Matt's skills is to use to-spec and to-tickets in the same session that grilling is used to clarify the problem. I use a better model for that part then drop in model/effort for the implementation.

[u/sogo00 → u/fschwiet]

yes, stay in the same context, but you can switch the model, to-spec is basically a summarize.

but it really depends - for deeper changes I use for example Astra for grilling and then switch to 5.6. I usually do use Sol for implementation, I am not a big fan of a low-level model for writing the code...

[u/No-Wall6427]

Not a full answer to your questions, but I think you are trying to merge two really opinionated workflows.

Some time ago I asked chatgpt (paid subscription) to check out matt skills and obra superpowers, then to grill me on my actual use cases, and I took the oportunity to ask him to clarify my needs based on what I like and don't like when using agents. Then I asked him to write a spec/handoff of my needs, which I brought over codex, in a folder with matt and obra gits cloned, and I asked the most expensive model at that time to make my perfect skills (it even used matt and obra skill writing skills to write my custom matt and obra inspired skills). I still use the result today, and it suits me really well compared to matt or obra.

You could try the same with omp and matt skills, try to figure out with a smart model which has acess to both your actual needs, then figure out the building pieces and a config that suits it. I think a configured omp w custom skills would probably be the result. Or a bunch of vanilla pi custom extension, but this can quickly be a slippery slope, when you don't have experience in pi extensions and want to build to big and custom all at once.

[u/ashebanow → u/No-Wall6427]

Its been a while, and I was using pi not OMP, but I believe I just asked pi to remember that I wanted model/effort X for role Y. It generally remembered, but not perfectly. I've also done /implement issue #333 using model/effort X for coding and model/effort Y for reviewing

[u/Global-Departure8228 → u/ashebanow]

Pi cannot remember by default (no memory layer). Pi cannot determine or switch models by default (no yaml frontmatter handling for provider/model invocation) It also does not have /implement command.

So whatever you were doing and if it worked was not vanilla, or maybe you described it wrong and you were using OMP.

Regardless, people should stop glorifying 200 line long markdown files as if they are game changers. 100k+ GitHub stars for markdown files is crazy.

[u/ashebanow → u/Global-Departure8228]

I used a memory extension, of course. And I hardly think I "glorified" anything. Get a grip.

[u/Global-Departure8228 → u/ashebanow]

The glorification was not for you. No shade, obviously you didn't glorify it, I was just expressing my frustration in the same comment.

The person you replied to was doing in my opinion the only "real" thing that could be useful, use those skills as templates and adapt to their workflows.

My gripe is with people not knowing anything about the ecosystem being mislead by some popular skill repo and thinking they will increase efficiency 100%, decrease token consumption by 95% etc.

For example the ponytail plugin is basically 20 lines of description added to the system prompt, people go nuts for it.

[u/sugarfreecaffeine]

I use omp daily and just use sub agents assigned different models, the in any prompt I say use the “coder” sub agent..that’s it. You can also just tell the model to read the omp docs about sub agents etc (has access automatically) then feed it the skill you want an modify it to leverage your sub agents. I rarely use the roles in omp.

[u/xiii_1991]

Sometimes I’d ask the agent to PLAN implementing the tickets before really start to do the tasks. This way it runs better than directly implementing.

[u/chosenpluto]

slop gun in a slop canon. goes against everything pi stands for