Prism: Make Your AI Editor Delegate

Bryan Barton Posted on May 31 • Originally published at github.com Prism: Make Your AI Editor Delegate # ai # mcp # cursor # ollama Prism: Make Your AI Editor Delegate By Bryan Barton Developer AI tooling is getting better, but a lot of workflows still have the same bad shape: Ask the premium model to do everything. Give it the task. Give it the repo rules. Give it the runbooks. Give it the skill docs. Give it the CI output. Give it the Kubernetes dump. Give it the prior chat. Then hope it can stay focused long enough to produce something useful. That works until it does not. The model becomes the planner, the researcher, the shell operator, the log reader, the docs scraper, the code reviewer, and the final writer. Every turn gets heavier. Every answer drags more context behind it. Prism is an experiment in a different shape: Keep the premium model as the orchestrator. Move the narrow work to local specialists. The Problem Is Not Just Token Cost Token cost is the easy thing to measure. Context quality is the thing developers actually feel. When your main AI session is packed with every skill, instruction, and evidence blob, you are paying twice: money for tokens the premium model did not need attention for a conversation that gets harder to steer Most agent frameworks try to solve this by becoming the new orchestrator. Prism does not. Prism assumes your editor is already the control plane. Cursor, Claude Desktop, or any MCP host can remain where decisions happen. Prism sits underneath as a delegation layer. The orchestrator asks for help. Prism runs a constrained local specialist. The specialist returns a compact summary. The orchestrator synthesizes the result. No swarm. No replacement IDE. No giant hidden workflow engine. Just smaller prompts in the place where smaller prompts matter. What Prism Is Prism is an MCP server and CLI for running repo-defined specialists on local Ollama. Each specialist is plain text: an agent spec optional skills optional constitu