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Manage Orca worktrees, separate working directories, along with terminals, repositories, and its embedded browser through the CLI. Use it to hand work to another agent, manage artifacts, run automations, and share skills within Orca.
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Control visible local apps and external browser windows through Orca, including clicks, typing, menus, dialogs, and screenshots. Use it for tasks that require interacting with a screen and cannot be completed through commands or APIs.
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Explain how dot works and check why a task is blocked, including computer access, login, approvals, and Slack errors. It provides supported next steps and answers questions about changing dot’s avatar and the user’s message color.
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Captures screenshots on registered computers and manages saved captures. Supports screen recording on macOS and timed screenshot sequences on HarmonyOS, checking available capabilities first and returning the finalized file path when recording stops.
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Operate desktop apps and isolated browsers on registered computers by inspecting interface controls, entering information, and checking results. The skill also covers screenshots and recording, with separate routing for the user's signed-in Chrome through Chromewhale.
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Create breadboard layout diagrams with HTML5 Canvas to show electronic components and wire connections. Use the skill for LED circuits, 555 timers, and 6502 computer projects, with component references, labels, and color-coded wiring.
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Build a computer-control loop where Cua Driver observes and acts, while TypeSafe Jev chooses from predefined actions. Validate each choice, execute one action at a time, and verify the result before continuing.
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Work in a local or remote computer environment whose screen you can watch. Run commands, transfer files, launch coding agents, move signed-in app sessions, and share the host computer’s network when needed.
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Create disposable Linux or macOS computers for running code, testing apps, operating desktop interfaces, and browsing websites. Use isolated environments locally or in the Cua cloud, then delete them when the work is complete.
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Read and operate desktop applications through their interfaces, including clicks, text entry, menus, and scrolling. Use it to inspect or edit app content when a dedicated connector, API, or command-line tool cannot handle the task.
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Install the free OpenWork desktop app on macOS, Windows, or Linux using the appropriate download for the computer. Guide initial setup, folder authorization, model selection, and a first task such as summarizing local files.
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Read, create, and edit text files on the computer running the connected A0 CLI. The skill guides focused replacements and context-based patches, checking current file contents and handling read-only access or outdated edits.
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Choose Memmy browser, desktop Computer Use, or a structured connector for a live task on macOS or Windows 11; keep Computer History retrieval separate from UI actions.
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Answer questions about what the user recently did on their computer — who contacted them, what they were working on, where they left off — by reading the local Computer History summaries and raw event streams.
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Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.
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Computer vision engineering for object detection, segmentation, and visual AI, covering CNN and Vision Transformer architectures and ONNX/TensorRT deployment. Use when building detection pipelines, training models, or optimizing inference.
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Expert knowledge for Microsoft Planetary Computer Pro development including troubleshooting, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using GeoCatalog/STAC APIs, configuring collections/tiles, securing access, integrating QGIS/ArcGIS, or troubleshooting ingestion, and other Microsoft Planetary Computer Pro related development tasks. Not for Azure Maps (use azure-maps), Azure Open Datasets (use azure-open-datasets), Azure Data Explorer (use azure-data-explorer).
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Think and work like an expert Human–Computer Interaction Researcher. Use when a task calls for Human–Computer Interaction Researcher judgment. Reasons from situated context, Fitts/GOMS/KLM, and CHI contribution types; runs contextual inquiry through LMM/CLMM analysis with SUS/NASA-TLX triangulation; uses Prolific/OSF and treats demand characteristics, novelty effects, ordinal misuse, and WEIRD samples as first-class failure modes.
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Think and work like an expert Computer Hardware Engineer. Use when a task calls for Computer Hardware Engineer judgment. Reasons from CPI/AMAT and MESI/MOESI coherence through SystemVerilog RTL, PrimeTime/Design Compiler/Innovus signoff, PCIe LTSSM/TLP, SVA formal, and clock-gating power while treating CDC metastability, false-path abuse, X-optimism, and coherency traffic as first-class failure modes.
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Think and work like an expert Computer Architecture Researcher. Use when a task calls for Computer Architecture Researcher judgment. Reasons from ISA semantics, AMAT/CPI, MESI coherence, and branch prediction through gem5/SPEC/MLPerf evaluation, Amdahl and roofline discipline, TPU/GPU dataflow accelerators, DVFS/EDP, and Spectre/Meltdown mitigation overhead at ISCA/MICRO/HPCA rigor.
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Think and work like an expert Computer Security Researcher. Use when a task calls for Computer Security Researcher judgment. Reasons from explicit threat models and CIA/STRIDE through AFL++/libFuzzer triage, ASan/KASAN oracles, ProVerif/Tamarin proofs, CVE/CWE/CAPEC taxonomies, CyberGym dual-execution benchmarks, Menlo/CVD ethics, and USENIX open-science artifact norms.
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Think and work like an expert Computer Scientist. Use when a task calls for Computer Scientist judgment. Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes.
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Think and work like an expert Computer Vision Scientist. Use when a task calls for Computer Vision Scientist judgment. Reasons from image formation, projective geometry (pinhole intrinsics and extrinsics, epipolar/PnP/bundle adjustment, similarity-scale ambiguity), and COCO/LVIS AP mechanics through DINOv3/SigLIP 2 foundation baselines, RF-DETR/YOLO26/SAM 3 models, COLMAP 4/GLOMAP and VGGT geometry, pycocotools/TrackEval/BOP evaluation, and CVPR reporting and EU AI Act limits while treating train–test and pretraining leakage, AP evaluation-setting gaming, preprocessing mismatches (EXIF, BGR, aliased resizing), label noise, and camera-convention and scale errors as first-class failure modes.
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Think and work like an expert Computer Graphics Researcher. Use when a task calls for Computer Graphics Researcher judgment. Reasons from the rendering equation, Monte Carlo bias/variance, sampling theory, and BSDF energy conservation through pbrt-v4/Mitsuba 3 references, MIS/ReSTIR/path guiding, DXR 1.2 real-time stacks, 3DGS and NerfBaselines protocols, FLIP/ColorVideoVDP evaluation, OpenUSD/MaterialX/OpenPBR interchange, and ACES 2/OCIO color while treating unconverged references, unequal-time comparisons, denoiser and temporal-reuse bias, scene- vs display-referred color errors, and white-furnace energy failures as first-class failure modes.
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