Local Ai
For local-model agents, what architecture checks do you run before granting tool access?
Ollama makes it easy to run a model locally, but the hard part for me starts after the model responds: what keeps an agent from having unclear tool permissions, unbounded loops, silent partial failure
Ollama makes it easy to run a model locally, but the hard part for me starts after the model responds: what keeps an agent from having unclear tool permissions, unbounded loops, silent partial failures, or a rollback plan that exists only in someone’s head? I’m building ArcForge, my MIT-licensed open-source set of portable Agent Skills. It is not an Ollama plugin or model runtime, and I’m not claiming a native integration. The project is a review layer for agent architectures. I’m especially interested in feedback from people running local models because lower latency and cost make experimentation easier, but they do not remove architecture risk. The current project has three focused skills: - system-architecture-harness turns requirements into an evidence-backed production architecture with decisions, trade-offs, risks, validation, and implementation slices. - ai-agent-system-architecture reviews LLM/RAG and multi-agent designs for control boundaries, tool contracts, budgets, evaluations, safety, latency, and rollout gates. - architecture-review-gate adversarially reviews RFCs, ADRs, diagrams, migrations, and readiness plans, returning findings, blockers, a score/verdict, and approval conditions. I’m sharing it as my project, with the context above, to get practical feedback rather than to imply an Ollama endorsement. It is free and MIT-licensed. Install: npx skills add d4rkninja/arcforge Repo: https://github.com/d4rkNinja/arcforge Skills listing: https://skills.sh/d4rkninja/arcforge For people running local-model agents: what evidence do you want before allowing write-capable tools? Do you gate permissions, budgets, evaluation coverage, or rollback first? If the project looks useful, a GitHub star is appreciated; real failure cases and criticism are more valuable. submitted by /u/FunNewspaper5161 [link] [comments]
Related
- I wrapped my Ollama agent with deterministic safety checks — here's the setup (catches bad JSON, prompt injection, and refusals before they hit your app) apache 2.0 [GitHub: https://github.com/qaysSE/AG-X]
- soul-agent-validator — I built a pre-deployment governance checker for Ollama agents (33 rules, open source, pip install)
- I built a local autonomous coding agent with Ollama — fine-tuned soul model, 40-round agentic loop, MiniMax M3 for the heavy lifting
Source: r/ollama | 2026-08-14