ARIS is a collection of Markdown-based skills that define a workflow for autonomous machine-learning research, including idea discovery, experiment automation, and review loops. Researchers and AI coding agents use it across tools such as Claude Code, Codex, Cursor, and OpenClaw without depending on a single framework. The catalogue entries are ARIS workflow skills and agents.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleepnpx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 29 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 262 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.03581 |
| Opus 5 | $0.00035 | $0.01791 |
| Sonnet 5 | $0.00014 | $0.00716 |
| Haiku 4.5 | $0.00007 | $0.00358 |
Grade C, and why
dse-loop scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- `rm -rf`, `rm -r`, or any recursive deletion How it starts
The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSE Loop: Autonomous Design Space Exploration
🔁 Do not wrap this skill in
/loop/CronCreate. It already loops internally until its objective is met or it times out. Unlike the verdict-bearing review/audit skills, its stop gate is an objective machine-checkable metric (Type-A), so its self-termination is safe same-model — the reason not to wrap it is scheduler duplication, not the verdict fence. Seeshared-references/external-cadence.md.
Autonomously explore a design space: run → analyze → pick next parameters → repeat, until the objective is met or timeout is reached. Designed for computer architecture and EDA problems.
Context: $ARGUMENTS
Safety Rules — READ FIRST
NEVER do any of the following:
sudoanythingrm -rf,rm -r, or any recursive deletionrmany file you did not create in this session- Overwrite existing source files without reading them first
git push,git reset --hard, or any destructive git operation- Kill processes you did not start
If a step requires any of the above, STOP and report to the user.
Constants (override via $ARGUMENTS)
| Constant | Default | Description |
|---|---|---|
TIMEOUT |
2h | Total wall-clock budget. Stop exploring after this. |
MAX_ITERATIONS |
50 | Hard cap on number of design points evaluated. |
PATIENCE |
10 | Stop early if no improvement for this many consecutive iterations. |
OBJECTIVE |
minimize | minimize or maximize the target metric. |
Override inline: /dse-loop "task desc — timeout: 4h, max_iterations: 100, patience: 15"
Typical Use Cases
| Problem | Program | Parameters | Objective |
|---|---|---|---|
| Microarch DSE | gem5 simulation | cache size, assoc, pipeline width, ROB size, branch predictor | maximize IPC or minimize area×delay |
| Synthesis tuning | yosys/DC script | optimization passes, target freq, effort level | minimize area at timing closure |
| RTL parameterization | verilator sim | data width, FIFO depth, pipeline stages, buffer sizes | meet throughput target at min area |
| Compiler flags | gcc/llvm build + benchmark | -O levels, unroll factor, vectorization, scheduling | minimize runtime or code size |
| Placement/routing | openroad/innovus | utilization, aspect ratio, layer config | minimize wirelength / timing |
| Formal verification | abc/sby | bound depth, engine, timeout per property | maximize coverage in time budget |
| Memory subsystem | cacti / ramulator | bank count, row buffer policy, scheduling | optimize bandwidth/energy |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 297 lines · 70 tokens per session scan C ae8e147011f7
dse-loop is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (15,970 stars, last pushed yesterday), licensed MIT. It adds 70 tokens to every session and 3,581 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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