ai-research-reproduction
ai-research-reproduction
Use when
- The user wants the agent to reproduce an AI paper repository.
- The target is a code repository with a README, scripts, configs, or documented commands.
- The goal is a minimal trustworthy run, not unlimited experimentation.
- The user needs standardized outputs that another human or model can audit quickly.
- The task spans more than one stage, such as intake plus setup, or setup plus execution plus reporting.
Do not use when
- The task is a general literature review or paper summary.
- The task is to design a new model, benchmark suite, or training pipeline from scratch.
- The repository is not centered on AI or does not expose a documented reproduction path.
- The user primarily wants a deep code refactor rather than README-first reproduction.
- The user is explicitly asking for only one narrow phase that a sub-skill already covers cleanly.
- The user is explicitly authorizing exploratory branch-only experimentation instead of trusted reproduction.
More from lllllllama/ai-research-workflow-skills
minimal-run-and-audit
Trusted-lane execution and reporting skill for README-first AI repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, or end-to-end orchestration by itself.
8paper-context-resolver
Optional narrow helper skill for README-first AI repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
8env-and-assets-bootstrap
Environment and assets sub-skill for README-first AI repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.
8repo-intake-and-plan
Narrow helper skill for README-first AI 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 trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
8safe-debug
Trusted-lane debug skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.
7analyze-project
Trusted-lane analysis skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.
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