ai-paper-reproduction
ai-paper-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.
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RigorPilot explore-code skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
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