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.
Metadata
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