Transform EXPERIMENT_PLAN.md into GPU-backed experiments with structured logging.
npx skills add https://github.com/xqinag/ARIS-new --skill experiment-bridge-xqinag
Please help me install this Agent Skill. Skill: experiment-bridge Source: https://github.com/xqinag/ARIS-new/tree/main/skills/experiment-bridge Command: npx skills add https://github.com/xqinag/ARIS-new --skill experiment-bridge-xqinag
Bridges the gap between idea discovery and executable experimentation by turning an EXPERIMENT_PLAN.md into runnable GPU-backed experiments with a structured results flow.
Provide an EXPERIMENT_PLAN.md and say "implement experiments" to deploy initial GPU runs.
High-intent search queries and answers about installing and using this skill.
To automate GPU-backed experiments, provide an EXPERIMENT_PLAN.md and trigger the workflow to implement code, deploy automatically, run sanity checks, and collect structured initial results.
Executing multi-stage milestone experiments on a GPU involves reading an EXPERIMENT_PLAN.md, implementing the code, and deploying it sequentially across milestones while collecting parseable logs and initial results.
Yes, the automated experiment workflow supports optional code review, allowing teams to validate implementation against the plan before automatic deployment to GPU resources.
Yes, you can run automated experiments by configuring the workflow with a BASE_REPO and enabling COMPACT mode to adapt the execution and deployment process to your specific context.
To ensure parseable logs during GPU experiment deployment, the workflow executes sanity-first checks and structures the logging output automatically for easy evaluation of initial results.
Automating experiment implementation relies entirely on a provided EXPERIMENT_PLAN.md, meaning deployments cannot proceed without a structured plan and correctly configured GPU resources.
HeXiao-55Convert EXPERIMENT_PLAN.md into executable GPU experiments and initial results.
THUFanZdTurn EXPERIMENT_PLAN.md into runnable GPU experiments and collect results.
czh-ee-2023Deploy experiments from an experiment plan to GPU resources and collect initial results.
goupup-aiAutomate ML training experiment deployment across local, remote, Vast.ai, and Modal GPU environments.
