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Find your next superpower If you are an agent, refer to our llms.txt for full access.Supports naming workflows for founders, agencies, and businesses. Selects either name generation or evaluation based on the supplied brief or existing options, including feedback, ranking, and scoring.
Reviews a local Flows app using flows-review-checks as the certification standard. Writes artifacts in numbered code review feedback folders and repeats reviews until no Must Fix items remain before design review.
Uses the Modal SDK to run Python in serverless cloud containers with on-demand GPUs. Supports model training, fine-tuning, inference, web endpoints, scheduled batch jobs, and workload scaling.
Run a TAO training/evaluation/inference container on an NVIDIA Brev GPU instance. Instance provisioning (create/search/stop/delete/login) is delegated to the official brev-cli agent skill or the Brev MCP server; this skill covers only the TAO-specific part — running the container over brev exec via the four-verb docker contract. Trigger phrases include "run on Brev", "Brev GPU instance", "TAO on…
Supports training, evaluation, export, quantization, and inference for SegFormer. Its lightweight transformer architecture uses hierarchical feature extraction for efficient semantic segmentation.
Handles a single training, evaluation, and export workflow for any TAO model without iterative augmentation, AutoML, or DEFT. Routes action details to model-specific skills and platform, credentials, and dataset intake to tao-launch-workflow.
Produces side-by-side comparisons of two or more .NET templates to support project template selection. Explains differences in parameters, supported features, frameworks, and classifications before project creation.
Supports out-of-core DataFrame operations, lazy evaluation, fast aggregation, visualization, and machine learning on very large datasets. Works with CSV, HDF5, Arrow, and Parquet files, including datasets with billions of rows.
Runs autoresearch experiments continuously on a selected schedule. Uses CronCreate with intervals such as ten minutes, hourly, daily, weekly, or monthly.
Guides LLM tracing and custom span creation with OpenInference semantic conventions. Supports instrumentation for Phoenix AI observability, including production deployment contexts.
Creates detailed, multi-step implementation plans before code changes begin. Applies when the design is approved or requirements are settled.
Covers quality control, normalization, dimensionality reduction, clustering, differential expression, and visualization. Also supports converting Seurat or SingleCellExperiment RDS files to h5ad for established exploratory single-cell analysis workflows.
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Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name