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Execution sherpas for AI agents built on ai-constitution

Project description

ai-sherpa

Execution sherpas for AI agents built on ai-constitution.

Where ministers set policy, sherpas do the work. Each sherpa is a Python module that wraps a concrete operation: starting services, shutting down cleanly, reading plans, indexing design data, talking to NextCloud, crawling APIs, walking a new user through onboarding.

Sherpas

Sherpa Purpose Mandatory?
boot Initialize the agent stack — start services, build prompt, hand to the agent yes
exit Mechanical shutdown — set session flag, stop services in parallel, save checkpoint yes
onboarding Walk a new org through the variable registry; render templates yes (populated in M3)
scrum Read active plans, evaluate dependencies, alert on blockers optional
design Indexed design intelligence — component specs, tokens, freeform requests optional
nextcloud CRUD on NextCloud via the Pi API service optional
crawler Discover APIs/tools/services from curated sources, classify, dedup, import to Knowledge optional
scaffold Sherpa generator template — python -m ai_sherpa scaffold <new-name> n/a (tooling)

CLI

python -m ai_sherpa                       # list available sherpas
python -m ai_sherpa <name> [args...]      # run a sherpa
python -m ai_sherpa scaffold <new-name>   # generate a new sherpa from the template

Honest portability disclaimer (v0.0.1)

Most sherpas in this v0.0.1 release were lifted from raj-sadan and still reference raj-sadan's specific filesystem layout (e.g. <repo-root>/memory/journal/, gateway/*.cjs adapters). They run correctly when consumed as a git submodule from a host repo whose layout matches raj-sadan's — that's the intended consumer path right now.

A future v0.2.0 refactor will inject paths via configuration so every sherpa is fully portable in isolation. Tracked as a follow-up to RAJ-70.

Status

v0.0.1 — populated by Linear issues RAJ-60, RAJ-68, RAJ-69, RAJ-70. Onboarding sherpa is M3 (RAJ-61). Public release is M5 (RAJ-75).

See also

License

MIT.

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