Routes Alibi users to the right explanation, confidence, prototype, or optional-backend workflow and points them to the bundled helpers needed to run it.
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Operate the Align-Anything multimodal alignment package, including training, serving, remote reward models, and satellite projects.
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Use AlpaSim repository guidance for autonomous-driving simulation setup, Hydra wizard runs, runtime services, ego drivers and plugins, ASL evaluation, controller/physics/traffic components, gRPC contracts, and operational troubleshooting.
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Route AlphaGPT data ingestion, factor mining, live strategy, and dashboard workflows.
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Route AlphaFold protein structure prediction setup, data preparation, local prediction, model configuration, output interpretation, and relaxation workflows.
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Use AlphaFold 3 PyTorch for protein and biomolecular structure-prediction workflows, heterogeneous molecule inputs, PDB/mmCIF/MSA/template preparation, bounded model inference, training configuration, and local CLI or Gradio operation.
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Use this skill for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection. Covers the local AlphaFold 3 inference package, its JSON dialect, run_alphafold workflow, outputs, troubleshooting, and safe helper scripts.
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Use AnnData to build, inspect, combine, store, lazily read, and extend annotated data matrices in memory and on disk.
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Use anomalib for anomaly-detection install, data/model selection, training and evaluation, deployment and inference, and benchmark pipelines.
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Use ANTsPy/antspyx for medical image IO, ANTsImage metadata, image operations, registration, segmentation, visualization, and learning helper workflows.
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Routes AnyDoor zero-shot object-level image customization workflows.
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Use NASA's apod-api Flask service and standalone APOD parser for date, count, range, media, deployment, Docker, and troubleshooting workflows.
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Routes AppAgent setup, exploration, and deployment workflows for Android-device task automation.
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Use ArcGIS API for Python for GIS administration, spatial dataframes, feature/raster analysis, mapping, location services, geospatial deep learning, app automation, and Knowledge Graph workflows.
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Routes Argos Translate workflows for offline machine translation, package installation, CLI usage, runtime settings, and troubleshooting.
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Use Google ADK Python to build agents, Workflow graphs, tools, runtime services, CLI apps, evaluations, deployments, and ADK repository changes.
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Routes ACT++, ACT, Diffusion Policy, VINN, and MuJoCo simulation workflows for bimanual ALOHA episode data and imitation-learning tasks.
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Operate the Agriculture_KnowledgeGraph agricultural Neo4j graph, Django demo, entity labeling, crawler, and relation-extraction workflows.
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Guide alphafold2-pytorch protein sequence, MSA, distogram, angle-logit, coordinate-refinement, recycling, embedding, and structure-utility workflows with version-aware troubleshooting.
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Use AReaL for large-scale asynchronous LLM reinforcement learning, agentic RL, distributed post-training, inference/agent services, backend planning, and customization workflows.
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Use Argilla 2.x for human-feedback dataset annotation, Python SDK dataset workflows, server deployment/operations, webhooks, and legacy v1/Rubrix migration.
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Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.
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Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.
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Route AI-Optimizer reinforcement-learning collection tasks across model-based RL, easy-MARL, offline RL, safe command builders, and repository limitations.
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