dse-loop

dse-loop is a skill for Claude Code from wanshuiyin/Auto-claude-code-research-in-sleep. It costs 70 tokens per session (3,581 once invoked), scanned C, original, MIT.

An automated loop for testing different computer-architecture or electronic-design settings. It runs a program, studies each result, chooses new settings, and repeats until a target is reached or time runs out.

In plain words
What is it for?
Use it for design-space exploration, parameter sweeps, and iterative tuning in computer architecture and electronic design automation (EDA).
Why use it?
It removes the need to manually try many parameter combinations when looking for a better design configuration.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is [`shared-references/external-cadence.md`](../shared-references/external-cadence.md)..

Good fit Use it for design-space exploration, parameter sweeps, and iterative tuning in computer architecture and electronic design automation (EDA).

Compare 6 skills from other repositories ↓
About the project

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.

wanshuiyin/Auto-claude-code-research-in-sleep · 15,970 stars · on GitHub

Install

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.

Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep
agentmods
npx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop

Made for: Claude Code.

Wrote 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.

agentmods badge for dse-loop

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop/github.svg)](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/dse-loop)
Your own site
<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.

agentmods 80×15 button for dse-loop

Your own site · 80×15
<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>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,581 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 7 Apr 2026
  • Snyk pass 7 Apr 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 11d ago against content hash ae8e147011f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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
skills/dse-loop/SKILL.md · 297 lines

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. See shared-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:

  • sudo anything
  • rm -rf, rm -r, or any recursive deletion
  • rm any 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

Read the full file on GitHub · 297 lines

Changes

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.

  1. 11d ago First seen · 297 lines · 70 tokens per session scan C ae8e147011f7

Subscribe to this mod's changes

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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