explore-run
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.
Install
With your agent
Install OMGSkills skill "lllllllama/rigorpilot-skills:explore-run" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/lllllllama/RigorPilot-Skills /tmp/RigorPilot-Skills && ln -s /tmp/RigorPilot-Skills/skills/explore-run ~/.claude/skills/explore-runFrom README
explore-run Use this as the Rigor Improve / Rigor Explore run leaf skill. The installed slug remains explore-run for compatibility. Use the shared operating principles in ../ai-research-reproduction/references/agent-operating-principles.md; this skill should guide candidate run planning while preserving model judgment about the active repo. When to apply When the researcher explicitly authorizes exploratory runs. When the task is a small-subset validation, short-cycle training probe, batch sweep, idle-GPU search, or quick transfer-learning trial. When the output should rank candidate runs rather than certify trusted success. When not to apply When the user wants trusted training execution or conservative verification. When there is no explicit exploratory authorization. When the task is repository , intake, or debugging. Clear boundaries This skill owns exploratory execution planning and summary only.
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