Results for “autonomous-research”

Guides users through defining goals, metrics, and scope, then runs an autonomous loop of code changes, testing, measuring, and keeping or discarding results for any programming task with a measurable outcome.

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

Autonomously runs iterative experiment loops to optimize code against a measurable metric. Use when the user wants to improve execution time, memory usage, test pass rate, or any numeric performance goal across repeated experiments — NOT for one-shot bug fixes or simple code review.

Autonomous experiment loop — iteratively mutate code, measure a metric, keep only improvements (hill-climbing ratchet)

Mental models and decision frameworks for building autonomous agents that continuously learn, explore, and accumulate skills in open-ended environments without human supervision

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the user runs /ar:loop or asks to run an autoresearch experiment continuously on a schedule.

Autonomous error recovery — detect failures, diagnose root cause, apply fixes, and resume without stopping

Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode

Scaffolds a program.md research program for autoresearch by auto-detecting codebase signals and interviewing for missing details.

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

AutoAugment: Learning Augmentation Strategies from Data

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