potiuk opened a new issue, #315:
URL: https://github.com/apache/airflow-steward/issues/315

   **Goal:** Define and land a skill runtime that works against **local LLMs** 
(Ollama, llama.cpp, vLLM, LM Studio, Jan). Grounds: [RFC-AI-0004 Principle 3 — 
Vendor neutrality](../tree/main/docs/rfcs/RFC-AI-0004.md), which explicitly 
names "a local-Ollama wrapper" as a target runtime, and RFC-AI-0004's "no 
cloud-only skills" consequence.
   
   **Why local LLM:**
   
   - **Sovereign deployments** — projects bound by data-residency rules (EU, 
government, defence-orbit OSS) that can't send issue / mail content to a US 
cloud API
   - **Air-gapped triage** — security teams that need to assess 
`<security-list>` traffic without an internet connection
   - **Cost ceiling** — projects unable to commit to a per-token cloud bill, 
but happy to run a 70B model on shared infra
   
   **What "parity" means** (calibrated for what local LLMs can realistically 
do):
   
   - Skills under `.claude/skills/<name>/SKILL.md` are invokable via a 
local-LLM-backed agent loop
   - The `tools/*` bridges are reachable — these are language-agnostic CLI 
calls, no LLM context needed
   - Sandbox / HITL primitives map to the same `bubblewrap` baseline; the 
local-LLM runtime is the new piece
   - **Realistic scoping:** some skills (multi-step reasoning over long 
contexts — `security-issue-triage`, `pr-management-code-review`) may need a 
high-capability local model (Llama 70B, Qwen 72B, DeepSeek). Document the 
per-skill model-size floor so adopters can pick a model that actually works.
   
   **Suggested approach:**
   
   - Pick an agent-loop frontend that supports local LLMs natively — 
candidates: `aider --model ollama/...`, `goose` with a local backend, 
`continue.dev`, a fresh thin wrapper around `llama.cpp`'s OpenAI-compatible API
   - Document the model-size floor empirically (per skill, against the existing 
eval suite at [`tools/skill-evals/`](../tree/main/tools/skill-evals/))
   - Land a `setup-local-llm` skill family alongside `setup-isolated-*` for the 
runtime-side install
   
   **Reference:**
   
   - RFC-AI-0004: 
[`docs/rfcs/RFC-AI-0004.md`](../tree/main/docs/rfcs/RFC-AI-0004.md)
   - Existing skill shape: [`.claude/skills/`](../tree/main/.claude/skills/)
   - Eval suite (for model-floor calibration): 
[`tools/skill-evals/`](../tree/main/tools/skill-evals/)
   - Ollama: https://ollama.com
   - llama.cpp: https://github.com/ggml-org/llama.cpp (OpenAI-compatible server)
   - vLLM: https://github.com/vllm-project/vllm
   


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