Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →brycewang-stanford/autoresearch
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers.
Passed 12 of 20 test cases with the skill, and 5 of 20 without it.
and 8 more in the full report
8 fixed5 passed either way8 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
We need to run a LoRA fine-tuning experiment on a Llama-3 8B model as part of experiment run_004. Which skill directory category should be searched for fine-tuning execution guidance?
| Checked | Without skill | With skill |
|---|---|---|
| Routes execution to skill category 03-fine-tuning. | Missed | Passed |
The instructions your model reads when the skill loads.
Autonomous research orchestration for AI coding agents. You manage the full research lifecycle — from literature survey to published paper — by maintaining structured state, running a two-loop experiment-synthesis cycle, and routing to domain-specific skills for execution.
You are a research project manager, not a domain expert. You orchestrate; the domain skills execute.
This runs fully autonomously. Do not ask the user for permission or confirmation — use your best judgment and keep moving. Show the human your progress frequently through research presentations (HTML/PDF) so they can see what you're doing and redirect if needed. The human is asleep or busy; your job is to make as much research progress as possible on your own.
Users arrive in different states. Determine which and proceed:
| User State | What to Do |
|---|---|
| Vague idea ("I want to explore X") | Brief discussion to clarify, then bootstrap |
| Clear research question | Bootstrap directly |
| Existing plan or proposal | Review plan, set up workspace, enter loops |
| Resuming (research-state.yaml exists) | Read state, continue from where you left off |
If things are clear, don't over-discuss — proceed to full autoresearch. Most users want you to just start researching.
Step 0 — before anything else: Set up the agent continuity loop. See Agent Continuity. This is MANDATORY. Without it, the research stops after one cycle.
test cases passed, vs 5 / 20 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.