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✳ Dosk — Zero prompt local AI assistant.

Dosk — Zero Prompt, Local Intelligence

Dosk

Local-first agent runtime. Turns context into durable work — with your explicit approval.

discord twitter


Caution

Research and exploration. Dosk is under active development: this repo is a workspace for experimenting with local-first agents, capture, and runtime design—not a finished, stability-guaranteed product. Expect rough edges, shifting APIs, and incomplete features. Use it to learn, prototype, and contribute; don’t rely on it for life-critical or compliance-sensitive workloads without your own hardening.


What Dosk is

Dosk is an execution system

The core objects are:

  • Task — a unit of intent with a goal, constraints, and dependencies
  • Run — an execution of a task: steps, tool calls, decisions, outcomes
  • Artifact — a durable output: file, draft, checklist, verified result
  • Approval — an explicit human gate before side effects happen
  • Policy — rules that govern what can run, what stops, what logs
  • Recovery — what happens when a run fails, is interrupted, or the machine restarts
  • Prediction — contextual task suggestions based on screen activity, time, and patterns — no prompting required

Every surface (bar, workspace, CLI, command menu, operator panel, APIs, MCP) is a thin client of the same runtime loop. They don't invent separate behavior. They all read from and write to the same task model.

See VISION.md for the full philosophy.


Core capabilities

Zero-prompt AI

Dosk watches your context — screen, calendar, browser, files, learned patterns — and surfaces tasks without you asking. "You've been reading research articles all afternoon — want a summary drafted?" or "Your Downloads folder has 47 unorganized files." You review, approve, Dosk executes.

Anticipation, not autonomy. You stay in control.

Status: beta — prediction engine in crates/dosk-runtime-core, UI panel scaffolded, Tauri command exposure in progress.

Resumable work

Runs are durable. If a run fails, the machine restarts, or you switch surfaces, Dosk picks up mid-task with full context restored. No starting from zero. No reconstructing intent.

Multiple surfaces, one runtime

Start work in the desktop bar, inspect it in the workspace, approve it from the CLI, resume it later. Every surface reads and writes to the same task model.

Status: in development — bar, workspace, CLI working; voice surface coming soon.

Trust, not theater

Approvals, audit trails, policies, and recovery aren't features layered on top — they're load-bearing primitives in the runtime.


What's inside

Layer What it does Status
crates/dosk-runtime-core Execution kernel: causal events, versioned state, typed tool dispatch, DAG graph runner, run state machine, resource scheduler Stable
crates/screenpipe-engine Local capture and API backend — screen, audio, OCR, accessibility Stable
crates/screenpipe-audio Audio capture and transcription Stable
crates/screenpipe-screen Screen capture and OCR Stable
crates/dosk-noone AI agent runtime with task prediction engine Stable
apps/dosk-app Desktop app (Tauri + Next.js) Stable

Develop

Prerequisites: Rust (cargo), Bun for JS/TS, platform deps in CONTRIBUTING.md.

# Build the capture backend
cargo build --release --features metal,apple-intelligence

# Desktop app (macOS)
cd apps/dosk-app
bun install
bun tauri build --features metal,apple-intelligence

Tests:

cargo test        # Rust
bun test          # JS/TS

Key paths:

  • apps/dosk-app/ — desktop app (Tauri + Next.js)
  • crates/dosk-runtime-core/ — execution kernel (events, state, graph, scheduler)
  • crates/screenpipe-engine/ — capture and API backend
  • crates/dosk-noone/ — agent runtime with prediction engine

What we don't do (yet)

  • Solved autonomous execution — we're honest about current limits
  • Invisible always-right background execution — approvals are required
  • Mandatory cloud — local-first, zero sign-in for core functionality
  • Canvas theater — this is not a visual thinking app

Roadmap

Near-term

  • Tauri command for predictions (scaffolding done, wiring in progress)
  • Calendar integration for meeting prep predictions
  • Pattern learning from approval history
  • Approval refinement — richer gates, scoped permissions

Medium-term

  • Email automation with approval gates
  • Meeting recording and recall
  • Artifact versioning (diffs, rollbacks)
  • Multi-run workflows spanning days or weeks
  • Policies as code

Long-term

  • Voice-first runtime surface
  • Cross-device resumability
  • Distributed runtime — multi-user approval, delegation, handoff

Documentation

Doc Purpose
VISION.md Product vision and principles
CONTRIBUTING.md Build, run, submit changes
TESTING.md Regression checklist for sensitive areas
CLAUDE.md Agent and maintainer notes

Contributing

See CONTRIBUTING.md. AI-assisted PRs welcome — run cargo test and bun test, and check TESTING.md before touching window management, audio, or capture.

contributors

discord · x · vision

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