Maintain and validate OpenShell builds for Windows on x64 and ARM64 using MSVC, Microsoft's C++ toolchain. Check compilation, build executables, run tests on native hosts, and report artifacts and unsupported driver behavior.
Manage isolated working environments in OpenShell using its command-line tool. Register gateways, create and connect to sandboxes, configure credential providers, and reuse workload templates with shared images, environment settings, and computing resources.
Create GitHub issues for OpenShell bugs, feature requests, and tasks using the gh command-line tool. Organize firsthand use cases, impact, and completion criteria into the project's templates, then return the created issue link.
Generate an OpenShell SBOM, an inventory of software components, with Syft. Fill missing license details from public registries, export CSV files for compliance review, and inspect or validate SBOMs attached to container images.
Handle network requests blocked by an OpenShell sandbox by checking its current access rules and proposing the smallest necessary change. Wait for approval and confirmation that the policy has reloaded before retrying the request.
Diagnose failed model requests from OpenShell sandboxes to hosted APIs or local servers such as Ollama and vLLM. Check provider attachment, access rules, credentials, network layout, and client settings to identify the narrowest configuration change needed.
Monitor GitHub Actions builds and tests with the gh command-line tool. Track runs until completion, inspect branch or pull request checks, read failed job logs, and rerun failed jobs or entire workflows.
Launch and supervise gator agents for specific GitHub issues or pull requests in OpenShell. Check isolated execution environments, inspect logs, restart stalled agents, and test model or image overrides without changing default settings.
Diagnose unreachable or unhealthy OpenShell gateways and sandbox startup failures. Identify the underlying execution platform, then examine logs, authentication, certificates, and configuration with the matching tools to narrow down the cause.
Review an authorized security issue in its private workflow. Check the affected code, assess whether the report is valid, explain severity and attack prerequisites, and propose a remediation plan with focused tests.
Assess OpenShell issues by checking first-hand use cases, reproduction evidence, existing behavior, and duplicates. Prepare a concise technical assessment, request specific missing information, and leave acceptance and roadmap decisions to human maintainers.
Agent runbook for Proteina-Complexa parameter sweeps through the separately installed first-party CLI and config generator. Use for cartesian-product hyperparameter scans, sweeper YAML authoring, configuration comparisons, ablations, tuning, success-rate ranking, or Pareto searches over quality and wall-clock cost. Do not use for a single existing-job launch or SLURM submission template. SKILL.md performs the orchestration; bundled executables only inspect local readiness and write a run manifest.
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Add, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs. Covers direct YAML edits and complexa target/validate target commands; running a campaign with an already registered target belongs to complexa-design.
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Generate synthetic PCB inspection images on Kubernetes with the SMT Defect Image Generation (DIG) DAG in CDF Orchestration. The DAG renders components in simulation, turns the renders into realistic golden images (sim2real), and uses AnomalyGen to add texture defects such as solder bridges, excess solder or missing components. Simulation can also render shift, tombstone and sideflip pose defects. Use it to build DIG payloads, pick a pipeline mode (full, simulation, sim2real or defect-only), check GPU readiness, follow a run, and match each defect image to its golden and simulated source. Not for running Simulation, Augmentation or AnomalyGen on their own.
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Agent runbook for evaluating an existing PDB directory through the separately installed first-party Proteina-Complexa CLI. Use to refold or score designs, compute interface pAE, i_pLDDT, scRMSD, motif RMSD, or designability, run complexa analysis, or assess third-party BindCraft, AlphaProteo, or RFdiffusion outputs. SKILL.md selects and invokes the evaluation configuration; bundled executables only inspect local readiness and write a run manifest.
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Run the CDF Orchestration Event Video Generation DAG on Kubernetes or OSMO - image-to-video anomaly generation, auto-labeling, and anomaly dataset generation. Select for requests about event video generation, anomaly video generation, image-to-video synthesis, Cosmos3 image2video, anomaly dataset creation, safety/surveillance SDG, or generating person-falling, person-climbing, person-running, fighting, smoking/vaping, fire/smoke, or shoplifting video clips from a seed image. Covers both event_video_generation_dag_k8s and the external-endpoints-only event_video_generation_dag_osmo. Runs environment setup first when controller readiness is unknown. Not for person-crop clothing/attribute augmentation (that is cdf-image-attribute-augmentation) and not for video style transfer.
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Run the CDF Orchestration Image Attribute Augmentation DAG on Kubernetes - person-crop clothing augmentation, attribute search, and augmented dataset generation. Select for requests about image attribute augmentation, person attribute search, person re-identification data, clothing augmentation, attribute captions, augmentation payloads, run status, or result retrieval. Runs environment setup first when controller readiness is unknown. Not for video or defect-image generation.
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Prepare payloads, run and monitor the Autonomous Vehicle Dataset Generation Airflow workflow, and inspect results for driving-clip retrieval and Cosmos3-Nano variants. Existing clips with no retrieval use cdf-video-data-augmentation; seed-image event or anomaly generation uses cdf-event-video-generation.
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Use when the user asks to deploy, install, reinstall, redeploy, upgrade, or connect to the CDF Orchestration Airflow controller. Owns the end-to-end deploy sequence and runs the cdf-orchestration-preflight audit first. Covers make setup, controller image builds, Helm installation, controller connection, port-forwarding, and post-install verification. Not for standalone prerequisite audits or remediation, K3s environments, authoring DAGs, or running workflow payloads.
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Use when a user describes a custom CDF Orchestration pipeline — a specific ordered combination of stages such as augmentation only, auto-labeling only, detection+captioning only, or image attribute augmentation without full auto-labeling — that no existing DAG in airflow/dags/workflows/ covers, and asks for a new Kubernetes DAG. Also use to check that a generated or existing DAG's model/container/prompt choices match an external spec document (e.g. a CDF `launchable.md`). Not for requests that an existing DAG already covers, including payload-only changes such as different inputs, endpoints, models, or variant counts — route those to the matching workflow skill, unless the user still wants a separate DAG after being pointed to it.
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Set up missing Linux prerequisites and audit whether a Cosmos Data Factory (CDF) Orchestration checkout and its Kubernetes or OSMO environment are ready to install the controller and run every packaged DAG. Use for prerequisite, pre-setup, Kubernetes, GPU, RWX/NFS, credential, controller-readiness, and quick-start checks. Not for deploying the controller (use cdf-orchestration-setup, which calls this audit first), authoring payloads, or running workflows.
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Component-owned guidance for CDF Simulation requests submitted directly or through Airflow-triggered DIG Flow Catalog prompts — golden THT board, THT pin-geometry variation, good/clean SMT images, structural pose defects, and solder texture defects, from a board USD. Turns one matched prompt into one validated `cdf.CDFJob` build and its compiled JobOrder payload; it never executes a render itself. Requires a caller-supplied board USD and output root, asks for either when missing from an interactive request, and resolves optional details with fixed, documented defaults.
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Run the CDF Video Data Augmentation Airflow workflow on Kubernetes or OSMO to create Cosmos video-to-video variants and auto-label both source and generated videos. Use for VDA payload authoring, preflight, execution, monitoring, output verification, or result retrieval. OSMO requires external endpoints. Standalone augmentation or auto-labeling configuration belongs to the respective component skill. Not for retrieval-driven CDF pipelines or image-to-video event generation.
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Diagnose a specific failing, hanging, or incorrect Holoscan CLI command. The skill guides reproducible investigation, isolates the responsible layer, applies a minimal fix, and checks the same command and focused tests to verify the result.
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