Chengkun Rao

Reads a GitHub repository's README, picks the smallest reproducible target (inference or eval), installs deps, runs it, and logs every step so you can trust the result.

Parses a README, extracts environment and asset requirements, builds a conda env spec, and generates step-by-step setup notes so the repo actually runs without path errors or missing checkpoints.

Executes bounded guess-and-check experiments—small-subset validation, batch sweeps, short hyperparameter searches—on your deep-learning repo without consuming full compute budgets.

Finds the exact dataset split, preprocessing step, or evaluation protocol a deep-learning repo needs but didn't document—by cross-referencing the original paper and repo files.

Rigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest t…

Takes a task family, dataset, benchmark, and state-of-the-art references, then generates candidate research angles with a rationale for each — filtered for novelty and feasibility.

Maps a machine-learning repository's model architecture, training flow, and config insertion points—without running code. Flags unusual patterns or missing safety checks.

Explores a research repo's architecture, identifies reusable modules, and generates isolated branch changes to swap backbones, add adapters, or integrate LoRA without breaking the main codebase.

Runs a deep-learning repo's smoke test or eval command, captures outputs, and writes them into a normalized repro_outputs/ folder with patch notes and environment metadata.

Takes a traceback, CUDA error, shape mismatch, or NaN loss and walks through the root cause with conservative reasoning before suggesting a fix — no wild patches.

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric e…