Full autonomy when you trust it. Full control when you don't.
Wallfacer is an autonomous engineering platform that works across multiple levels of abstraction. Start with a conversation when you're exploring an idea. Move to specs when the shape becomes clear. Track tasks when it's time to execute. Drop into code when you need precision. Agents operate at every level, and you decide how much freedom they get.
Open source. Runs locally. No IDE lock-in. No cloud dependency. Bring your own LLM provider.
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| Task board: coordinate parallel agent execution |
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| Plan mode: design before you build |
Every AI coding tool today pins you to one interaction mode. Chat-based tools are fast but lose structure at scale. Spec-driven tools add discipline but slow you down on day one. Task boards help you coordinate but don't understand your architecture. Wallfacer connects all of these into a continuous workflow.
Adaptive abstraction. Chat for greenfield exploration, specs for complex systems (a recursive tree of markdown specs that agents read, iterate on, break down, and dispatch as tasks), tasks for parallel execution, code for surgical edits. Move between levels as your project evolves.
Autonomy spectrum. Run the full loop autonomously (implement, test, commit, push) or step in at any point. Dial autonomy up or down per task, per spec, per project.
Spec as intermediate representation. Ideas don't go straight to code. They become structured specs that agents can reason about, iterate on, and implement against. Specs are versioned and reviewable.
Per-task git worktrees. Each task works in its own git worktree for safe parallel execution. Multiple agents work simultaneously without stepping on each other.
Operator visibility. Live logs, traces, timelines, diff review, and usage and cost tracking. A full audit trail from idea to merged code.
Self-development. Wallfacer builds Wallfacer. Most recent capabilities were developed by the system itself.
Harness flexibility. Works with Claude Code, Codex, Cursor, OpenCode, and Pi through a pluggable harness layer. Pick one per task or per agent role; not locked to any single provider.
Install:
curl -fsSL https://raw.githubusercontent.com/changkun/wallfacer/main/install.sh | sh
Check prerequisites:
wallfacer doctor
Start the server:
wallfacer run # execs your chosen harness CLI directly as a host process
A browser window opens automatically. Add your Claude credential (OAuth token via claude setup-token, or API key from console.anthropic.com) in Settings. See Getting Started for the full walkthrough.
Other commands: wallfacer status (print or watch board state), wallfacer spec (validate or scaffold specs), and wallfacer auth (cloud sign-in). Run wallfacer <command> -help for flags.
flowchart LR
Idea([Idea]) --> Chat[Planning Chat]
Chat --> Spec[Root Spec]
Spec --> BreakDown[Break Down]
BreakDown --> Leaves[Leaf Specs]
Leaves --> Tasks[Dispatched Tasks]
Tasks --> Commits([Commits])
Wallfacer lets you work at whichever abstraction level fits the problem, and move between them as the shape becomes clearer.
graph LR
Chat[Chat
exploratory] --> Spec[Spec
structured design]
Spec --> Task[Task
scoped execution]
Task --> Code[Code
surgical edits]
Move left for more freedom and lower commitment; move right for more precision and higher commitment. Agents operate at every level, and autonomy dials up or down independently at each one. Specs move through a seven-state lifecycle (vague to drafted to validated to testing to complete, with stale and archived off to the side), and the planning chat exposes slash commands like /create, /validate, /break-down, and /dispatch to drive them.
Read more: Concepts, Plan, and Chat.
Wallfacer runs every task through a small, composable set of primitives:
implement.User-authored agents and fleets live as YAML under ~/.wallfacer/{agents,flows}/ and are edited on the unified Agent Graph surface (the old Agents and Flows pages merged into it). Clone a built-in to pin it to a harness, override its system prompt, or insert a review step, without restarting the server. Task prompts are refined in place from Plan mode.
Read more: Agent Graph.
The board (shown above) coordinates many agent tasks at once. Drag cards across the lifecycle, batch-create with dependency wiring, refine prompts before execution, and let autoimplement promote backlog items as capacity opens. Each task runs as a host process in its own git worktree.
Design before you build (shown above). The three-pane plan view gives you an explorer tree (left), a focused markdown view (center), and the planning chat (right). Break large ideas into structured specs, validate dependencies, and dispatch leaf specs to the board when the design is right.

Inspect what happened, when, and why before you accept any automated output. Every task produces a structured event timeline, a diff against the default branch, and an AI-generated oversight summary.

Track token usage and cost by task, activity, and turn, so operations stay measurable as automation scales. The per-activity breakdown (implementation, testing, refinement, oversight) shows exactly where budget goes.
Five composable sub-agent roles (each pinned to any installed harness) arrange into flows (implement, plus user-authored clones) that can be inspected or rewritten from the sidebar.
Development is organized into three parallel tracks with shared foundations. See specs/README.md for the full dependency graph and spec index.
Foundations (complete): Execution backend interface, storage backend interface, file explorer, host terminal, multi-workspace groups, Windows support.
Local Product: Developer workflow. Spec coordination (document model, planning UX, drift detection), agents and flows (composable sub-agent pipelines), routine tasks (scheduled spawns), file and image attachments, host mounts, oversight risk scoring, visual verification, live serve.
Cloud Platform: Multi-tenant hosted service. Tenant filesystem, K8s execution backend, cloud infrastructure, multi-tenant control plane, tenant API.
Shared Design: Cross-track specs. Authentication, agent abstraction, native sandboxes (Linux, macOS, Windows), overlay snapshots.
User Manual is the full reading order. Guides are grouped by what you are doing.
Get Started
| Guide | Topics |
|---|---|
| Getting Started | Installation, credentials, sign-in, first task |
| Concepts | Mental model: workspaces, tasks, specs, agents, autonomy |
Use Wallfacer
| Guide | Topics |
|---|---|
| Board | Task board, lifecycle, dependencies, search, task detail |
| Chat | Chat sessions, slash commands, @mentions |
| Plan | Spec mode, lifecycle states, dispatch, planning chat |
| Agent Graph | Agents, fleets, harness pinning, live traces |
| Routines | Scheduled cards that spawn tasks on an interval |
| Whiteboard | Free-form drawing canvas per workspace |
Operate
| Guide | Topics |
|---|---|
| Automation | Autoimplement, auto-test, auto-submit, auto-retry, circuit breakers |
| Oversight | Oversight summaries, timelines, logs, diff review, analytics |
| Mission Control | Unified spec and task graph, acting on the pipeline |
| Workspaces | Workspace management, git integration, branches, GitHub |
| Configuration | Settings, env vars, harnesses, CLI, shortcuts |
Build On (Internals) is the deep reference for how the system works. Start at Technical Internals.
| Reference | Topics |
|---|---|
| Architecture | System design, package map, handler organization, end-to-end walkthrough |
| Data & Storage | Data models, persistence, event sourcing, spec document model |
| Task Lifecycle | State machine, turn loop, dependencies, failure categorization |
| Git Operations | Worktree lifecycle, commit pipeline, branch management |
| API & Transport | HTTP route reference, SSE, WebSocket terminal, middleware |
| Auth & Identity | OIDC, device sign-in, principal context, cloud mode |
| Automation | Background watchers, autoimplement, agon, circuit breakers, routines |
| Agent Graph Runtime | Embedded topos runtime, agentic execution, live traces |
| Plan Mode | Spec tree, agent sessions, slash commands, dispatch, undo |
| Workspaces & Config | Workspace manager, harness routing, templates, env config |
| Development Setup | Building, testing, make targets, release workflow |
Contributing? See CONTRIBUTING.md for the developer orientation, build commands, and conventions.
Wallfacer started as a task board for coordinating concurrent agent runs and grew from there: spec coordination, oversight, refinement, an integrated IDE. Most recent capabilities were developed by Wallfacer itself. See docs/origin.md for the long version.
$ claude mcp add wallfacer \
-- python -m otcore.mcp_server <graph>