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@@ -30,21 +30,18 @@ Monorepo with Git submodules. Each submodule has its own Go module (except `el`
 - **Interactive AI shell** — `s/sh` gives you a readline prompt that resumes your last session per directory, with streaming output and live model/backend switching
 - **One-shot queries that compose with Unix pipes** — `cat error.log | s/bfg "what caused this?" | s/bfg "suggest a fix"`
 - **Parallel fan-out** — `s/bfg -parallel 4` spawns N agents on the same prompt and collects results
-- **Multi-agent workflows in plain shell** — create named sessions, pass prompts between them via files, coordinate with `statewait`; no framework or SDK
+- **Multi-agent workflows in plain shell** — create named sessions, pass prompts between them, coordinate with `statewait`; no framework or SDK
 - **Subagent delegation** — agents can fork ephemeral subagents that run independently and return results
 - **Tier-based routing** — `route` dispatches subtasks to worker or expert models based on complexity; the orchestrator picks the tier, the system picks the backend/model
-- **Orchestrator/worker system** — specialized agents for task decomposition (`orchestrator`) and scoped execution (`worker`/`expert`); workers read code and reason about implementation within their assigned scope
-- **Any model, any backend** — Ollama (local), OpenAI, Anthropic, OpenRouter, GitHub Copilot, Kiro; switch per-session with one write
+- **Orchestrator/worker system** — specialized agents for task decomposition (`orchestrator`) and scoped execution (`worker`/`expert`)
+- **Any model, any backend** — Ollama (local), OpenAI, Anthropic, OpenRouter, GitHub Copilot, Kiro; switch per-session
 - **Sandboxed execution** — every tool call runs inside a Landlock sandbox with configurable filesystem access
 - **Extensible via plain scripts** — drop executables into a directory and the agent picks them up; built-in tools cover file I/O, LSP (go-to-definition, references, rename, diagnostics), persistent memory, web search, and browser screenshots
 - **Domain skills** — teach the agent your project's conventions with a markdown file; loaded on demand
 - **AI code completion** — `u/complete` reads a prefix from stdin and prints the completion to stdout; plug it into any editor that can shell out
-- **Multiple frontends** — terminal (`s/sh`), acme (`ollie-acme` + `Kmpl`), Emacs (`ellie`), KDE (plasmoid, standalone GUI, Kate plugin), and a browser-based web UI; all talk to the same 9P server
-- **Remote access** — mount a remote server's namespace locally with `9pfuse`, or use the HTTP gateway with `curl` or the web UI
-- **Store federation** — point tools or transcripts at a remote 9P mount to share across machines
+- **Multiple frontends** — terminal, acme, Emacs, KDE (plasmoid, standalone GUI, Kate plugin), and a browser-based web UI
 - **Prompt optimization** — `u/optimize` generates N candidate prompts in parallel, then judges them to return the best one
 - **Automatic context compaction** — long conversations are summarized transparently when approaching the model's context limit
-- **Per-agent 9P principals** — each agent session mounts the filesystem as its own user; 9P permission enforcement prevents self-prompting loops and enforces access boundaries
 
 ## Getting started