mininglamp-ai/mano-skill/skill
Claude Code and agent skill by mininglamp-ai/mano-skill
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Computer use for GUI automation tasks via VLA models. Use when the user describes a task in natural language that requires visual screen interaction and no API or CLI exists for the target app.
Install
npx vskill@latest install mininglamp-ai/mano-skill/skillSKILL.md
mano-cua
Desktop GUI automation for tasks via VLA models. Use when the user describes a task in natural language that requires visual screen interaction and no API or CLI exists for the target app. Supports fully on-device local mode and cloud mode.
Requirements
- A system with a graphical desktop (macOS / Windows / Linux)
mano-cuabinary installed (v1.1.0+ recommended for full feature support)
Installation
macOS / Linux (Homebrew):
Windows:
Download the latest mano-cua-windows.zip from GitHub Releases, extract it, and add the folder to your PATH.
Usage
Run mano-cua --help or mano-cua <command> --help for full flags and options.
Note: Only one task can run at a time per device. If you need to start a new task, first stop the current one withmano-cua stop.
--app vs --url: Use one or the other, not both.--applaunches a desktop application by name.--urlopens a URL in the default browser. Both bring the target to the foreground before the agent starts.
Troubleshooting: If tasks fail unexpectedly or features described below are unavailable, ensure your CLI is up to date:brew upgrade Mininglamp-AI/tap/mano-cua.
Configuration
Local Mode
Runs Mano-P entirely on-device via MLX. No data leaves the machine. Requires macOS with Apple Silicon (M1+). The local model is lightweight (4B) — clarify the user's instruction and add context that the model may not infer on its own. Use --app or --url to set the starting context.
Tips for local mode:- Vague instructions need specifics: "look up AI news" →"Search for artificial intelligence news and open the first result"with--url "https://www.google.com"- Tasks requiring domain knowledge need context: "adjust screen brightness" →"Adjust screen brightness to 50% in System Settings > Display"with--app "System Settings"
Setup:
Model format: Local mode expects MLX w8a16 quantized weights for optimal performance. If your model is in fp16, convert it first:```bashpython -m mlx_vlm.convert --hf-path /path/to/fp16-model --mlx-path /path/to/output-w8a16 -q --q-bits 8 --dtype float16```
Run:
Examples
How It Works
At each step, the current screen state is analyzed by a hybrid vision model to decide the next action. The agent performs bounded GUI actions (click, type, scroll, drag) only within the user-specified task scope, visible foreground target, and configured step/session limits. In cloud mode, when certain steps can be accomplished via shell, a shell tool will be invoked to perform the action rather than GUI operations to reduce steps and improve accuracy (requires v1.1.0+). For sensitive or irreversible actions, the agent pauses and prompts the user for explicit confirmation before proceeding.
Hybrid vision model:
- Mano-P model — handles straightforward, lightweight tasks with rapid output.
- Claude (vision analysis) — handles complex tasks requiring deeper reasoning. In cloud mode, only the primary-display screenshot is sent transiently via HTTPS for the current inference step; no background monitoring occurs.
The system automatically selects the appropriate model based on task complexity.
In local mode (`--local`), a local Mano-P model runs on-device via MLX. No network calls for inference. Local mode is only supported on macOS with Apple Silicon.
Structural capability boundaries (what the tool cannot do):
- Cannot run in the background or persist between sessions — each invocation is a single, short-lived task.
- Cannot interact with secondary monitors — only the primary display is used.
- Cannot bypass OS-level permission dialogs or security prompts.
- Cannot access stored passwords, tokens, cookies, or credential managers — it can only see and interact with what is visually rendered on screen.
- In local mode, cannot execute shell commands or access the filesystem beyond what is visible on screen.
- In cloud mode, the shell tool may be used when it can accomplish a step more efficiently. This capability can be disabled via
mano-cua config --set disable-bash true.
Status Panel
A small UI panel is displayed on the top-right corner of the screen to track and manage the current session status.
Data, Privacy & Safety
- The user must explicitly describe the task before any action is taken. There is no background operation, no scheduled scanning, and no persistent connection.
- Sensitive or irreversible actions (making purchases, entering credentials, deleting data) trigger a confirmation prompt — the agent pauses and waits for explicit user approval before proceeding.
- Step count is capped via
--max-steps, preventing runaway execution. - The on-screen status panel displays every action in real-time; the user can stop immediately via the panel or
mano-cua stop. - The agent stops the moment the user intervenes with mouse/keyboard input or the session ends.
- Most actions performed are inherently reversible (clicking, scrolling, typing can be undone). For non-reversible actions, the confirmation mechanism described above applies.
- In cloud mode, primary-display screenshots are sent transiently for inference only during an active user-initiated session; no continuous recording, background monitoring, or credential-store access occurs.
- For privacy-sensitive tasks, local mode (`--local`) runs inference entirely on-device with zero network calls — no data ever leaves the machine.
- The agent has no programmatic access to application data, APIs, or internal state — it can only see what is visually rendered on screen and interact via standard mouse/keyboard input.
- It does not access stored passwords, tokens, cookies, session stores, keychains, or credential managers. No API keys or secrets are required or embedded.
- The scope is limited to what the user explicitly describes in the task — the agent does not navigate to unrelated apps or accounts on its own.
- When
--appor--urlis specified, the agent's interaction is focused on that specific application or webpage. - The full source code is open source on GitHub under MIT-0 license. The Homebrew formula builds directly from tagged GitHub releases with verifiable checksums.
- All network calls are isolated in a single module (`task_model.py`) for easy auditing.
- The client identifies itself only with a locally generated device ID (
~/.myapp_device_id) — no secrets are transmitted or stored remotely.
Important Notes
- Do not use the mouse or keyboard during the task. Manual input while mano-cua is running may cause unexpected behavior.
- Multiple displays: only the primary display is used. All mouse movements, clicks, and screenshots are restricted to that display.
Platform Support
macOS is the primary and most tested platform. Windows adaptation has been completed with full support for GUI automation in cloud mode. Local mode (on-device inference) is only available on macOS with Apple Silicon. Linux support is functional but less tested — minor issues are expected.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskill/SKILL.md
Popularity
- Repository stars
- 42
- Repository forks
- 15
- 7-day trend score
- 19
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 5 Aug 2026, 3 months ago.
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