Easy Auto Research

Set up, steer, and resume Easy-Auto-Research for Deep Learning — a human-supervised, multi-role deep-learning research loop for Claude Code. It proposes experiments, edits versioned code copies, launches training, monitors progress, evaluates evidence against a goal, and persists state across cycles. Use this skill through natural-language requests to start a run, provide guidance, interrupt active work, inspect progress, or continue a stopped run.

Install

skills CLI (Claude Code, Cursor, Codex and more)
npx skills add wjc2830/Easy-AutoResearch-for-DeepLearning --skill easy-auto-research
Manual install
git clone --depth 1 https://github.com/wjc2830/Easy-AutoResearch-for-DeepLearning.git /tmp/Easy-AutoResearch-for-DeepLearning
mkdir -p ~/.claude/skills
cp -r /tmp/Easy-AutoResearch-for-DeepLearning/easy-auto-research ~/.claude/skills/easy-auto-research

Personal skills live in ~/.claude/skills. Use .claude/skills in a project folder to share a skill with your team.

From the SKILL.md

# Easy-Auto-Research for Deep Learning — Research Loop

Easy-Auto-Research for Deep Learning provides a human-supervised research loop in Claude Code. Six role-specialized Claude Code sessions run in a fixed cycle — **Planner → Executer → Secretary →
Verifier → Evaluator**, with a stateless **Orchestrator** routing between them — each using a
role-specific prompt. It improves the user's **own local ML
codebase** against a goal they define and versions every experiment. It may stop on verified
success, user action, abort, configured cycle/stall limits, or an unrecoverable failure.

This skill is self-contained. Everything lives under this skill's own directory. The skill
agent resolves **`$SKILL`** internally to the absolute directory containing this SKILL.md;
this path and all commands are implementation details, not part of the human interface:
- `scripts/` — the runtime controllers and `scripts/Skills/` helper skills used by the research roles.
- `templates/` — six runtime role templates, `interviewer.md`, `group_duty.md`, and `research_spec.template.json`.
- `reference/research_spec.filled_example.json` — an illustrative filled spec to adapt.
- `VERSION` — the release version.

---

## Mental model you must hold (before doing anything)

**Three layers, state flows downward only:**
1. **`$SKILL`** — read-only source bundle (this skill). Never mutated by a run.
2. **`$PROJ`** — one folder **per research task**. Gets a *copy* of the runtime and owns
Read the full skill on GitHub

Details

Skill name
easy-auto-research
Path
easy-auto-research/SKILL.md
License
MIT
Repo updated
21 August 2026

FAQ

What does the Easy Auto Research skill do?

Set up, steer, and resume Easy-Auto-Research for Deep Learning — a human-supervised, multi-role deep-learning research loop for Claude Code. It proposes experiments, edits versioned code copies, launches training, monitors progress, evaluates evidence against a goal, and persists state across cycles. Use this skill through natural-language requests to start a run, provide guidance, interrupt active work, inspect progress, or continue a stopped run.

How do I install the Easy Auto Research skill?

skills CLI (Claude Code, Cursor, Codex and more): npx skills add wjc2830/Easy-AutoResearch-for-DeepLearning --skill easy-auto-research. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.

Is Easy Auto Research popular?

It lives in wjc2830/Easy-AutoResearch-for-DeepLearning, which has 1 GitHub stars and 0 forks, and is included in 1 curated skill list.

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