510 karma · joined July 11, 2007
Socials: - github.com/awwaiid
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Then I do it again from scratch; this time it takes less steering. I have it update the skill further.
I've been doing this on a few different tests and building a skill which is taking less and steering to do app-specific and team-specific manual testing faster and faster. The first times through it took longer than manually testing the feature. While I've only started doing this recently, it is now taking less time than I would take, and posting screenshots of the results and testing steps in the PR for dev review. Ongoing exploration!
Speaking of which, an interesting thing to contemplate is if it is worth automating what you did, or if making the videos happens rarely enough that you'd start from scratch with a new manus or other ai session.
llm install llm-ollama
and then you use whatever model you like, anything llm has installed. See https://llm.datasette.io/en/stable/plugins/installing-plugin... for plugin install info.Here is a sample session. You can't see it ... but it is very slow on my CPU-only non-apple machine (each response took like 30 seconds) :)
>>> from gremllm import Gremllm
>>> counter = Gremllm("counter", model="gemma3n:e2b")
>>> counter.value = 5
>>> counter.increment()
>>> counter.value
None
>>> counter.value
None
>>> counter.value
None
>>> counter.what_is_your_total()
6
6
... also I don't know why it kept saying my value is None :) . The "6" is doubled because one must have been a print and the other is the return value. >>> from gremllm import Gremllm
>>> player = Gremllm('dungeon_game_player')
>>> player.go_into_cave()
'Player has entered the cave.'
>>> player.look_around()
{'location': 'cave', 'entered_cave_at': '2025-07-02T21:59:02.136960'}
>>> player.pick_up_rock()
'You picked up a rock.'
>>> player.inventory()
['rock']
(further attempts at this have ... varying results ...)If you trust where you are curling from, and you trust everyone they trust and that they definitely haven't been hacked, then great! Blindly eval that code! That's what I do :)
That said, I based the memory capture on https://github.com/cloudsftp/reSnap/tree/latest which is a shell script that slurps out of process space device files. If you can find something like that which works on the rPP then I can blindly slap it in there and we can see what happens!
The one use-case that is _close_ to ready-for-useful: I often take business meeting notes. In these notes I often write a T in a circle to indicate a TODO item. I am going to add a bit of config in there, basically "If you see a circle-T, then go add that to my todo list if it isn't already there. If you see a crossed-out circle-T then go mark it as done on the todo list" .
I got slightly distracted implementing this, working instead toward a pluggable "if you see X call X.sh" interface. Almost there though :)
"proof" to partner of tablet investment value based on interactive fiction conversation == excellent strategy and nothing could go wrong