/deep-research

Checks every installed skill for structure, declared permissions and safety, then produces a health report of what passes and what fails.

Runs a chain of skills defined in a pipeline file, with quality gates between steps and a final summary showing the result of each step.

Generates a new skill from a plain-language description, together with its permission manifest and a test file.

Scans your project, detects its tech stack and activates only the relevant skills, saving the choice as a project configuration file.

Turns a raw dataset into a clean, well-split, leakage-free base for modeling: profiling, cleaning, train/validation/test splits and balance checks.

Designs features for a tabular ML problem inside a leakage-safe pipeline: encodings, scaling, interactions and date-based features.