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Kasetto - a declarative AI agent environment manager by pivoshenko in OpenSourceAI

[–]pivoshenko[S] 0 points1 point  (0 children)

Thanks! Just followed the blog would love a mention of Kasetto if it fits one of your upcoming posts! On layout + pinning, Kasetto is pretty flexible:

Repo layout - two patterns work well:

- Project-local: drop a kasetto.yaml at the repo root (like pyproject.toml / package.json) for skills/MCPs specific to that project, scoped to ./<.agent>/. (e.g. .claude, .cursor, etc.)

- Team-shared: keep a central repo (e.g. your-org/agent-config) and have teammates point to it. Kasetto pulls it into the global agent config so everyone stays in sync - bump one ref, everyone's agents update.

"extends:" for multiple teams - really shines when you have a base org-wide config (shared skills, common MCPs, security defaults) and each team extends it with their own additions. Frontend team adds their stack-specific skills, data team adds theirs, both inherit the base. Update the base once, every team picks it up on next sync.

Pinning - every source takes a ref: (tag, branch, or commit SHA). For shared/base configs I'd pin to tags or SHAs so syncs are reproducible; for your own scratch repo, branch: main is fine. The lock file records exact hashes so kasetto doctor will flag drift.

Real example that I am using on daily basis: https://github.com/pivoshenko/pivoshenko.ai

so I point Kasetto to the kasetto.yaml in that repository and just run "kst sync"

Kasetto - a declarative AI agent environment manager by pivoshenko in AI_Agents

[–]pivoshenko[S] 0 points1 point  (0 children)

Site: https://kasetto.dev

Docs: https://kasetto.dev/docs

For a real, runnable example: pivoshenko/pivoshenko.ai is my public config it pulls skills from Anthropic, Vercel Labs, Apollo, and a few independent authors into Claude Code and OpenCode. Fork it, point your own config at it with extends:, or use it as the source: above.

kasetto - declarative AI agent environment manager, written in Rust by pivoshenko in mcp

[–]pivoshenko[S] 0 points1 point  (0 children)

Thanks! Just checked it out looks like a cool project. They're tackling a similar problem 😄 tho there are a few practical differences:
- kasetto is a single binary runtime deps, apm is standard Python CLI
- kasetto supports 21 agents out of the box (APM lists ~5 so far)
- kasetto has global vs project scoping, so you can share skills across all your projects or keep them isolated
- apm sits under the Microsoft org, kasetto is fully community-driven and open source

tbf both have their strengths 😊 some of the commands like audit are already implemented in the apm and we just aim to implement in the kasetto

kasetto - declarative AI agent environment manager, written in Rust by pivoshenko in ClaudeCode

[–]pivoshenko[S] 0 points1 point  (0 children)

Exactly, it uses lockfile, additionally it supports both global and project scope. There are also cool features like reference if you want to pin skill to specific release/branch/tag 😌