Ready to supercharge your AI agents?

Install any skill in seconds. Free to start, no credit card required.

Aas Artifact Evaluation · brycewang-stanford | DecimalAI

researchby brycewang-stanford

Aas Artifact Evaluation

brycewang-stanford/aas-artifact-evaluation

Source brycewang-stanford/awesome-journal-skills ↗License MIT

当你在为《自动化学报》(Acta Automatica Sinica, AAS) 稿件准备代码与数据可用性材料、判断本刊是否设有独立制品评审(artifact evaluation)徽章制度时调用。讲清本刊现状(以同行评议为主、无独立徽章制度的现况为待核实)、如何主动提供匿名可复现的代码/数据以增强说服力、控制仿真与实物实验制品的组织，帮助控制/自动化/模式识别方向的中文稿在 Acta Automatica Sinica 外审中用可用制品提升可信度。

SkillScore91Maintained

Automatic

Research pack

Last verified 8/15/2026

What it changes

Passed 19 of 21 test cases with the skill, and 11 of 21 without it.

Without skill55%

With skill91%

Checks it passed that the model alone missed

Places execution scripts in a 'scripts/' subdirectory.
Places experiment configurations and seeds in a 'configs/' subdirectory.
Requires the repository link to remain completely anonymous for double-blind review.

and 8 more in the full report

8 fixed12 passed either way2 still failing0 broke

Pass-rate lift: +36 pp
Tokens: +58%
Agent turns: 0%
Response time: +1%

Model gemini-3.6-flashMeasured 8/15/2026v120 of 22 cases passed with skill · 21 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-aas-artifact-evaluation/SKILL.md https://app.decimal.ai/s/brycewang-stanford-aas-artifact-evaluation/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add brycewang-stanford-aas-artifact-evaluation, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/brycewang-stanford-aas-artifact-evaluation/ and pins it in .decimal/skills.lock

decimalai skills add brycewang-stanford-aas-artifact-evaluation

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-aas-artifact-evaluation/SKILL.md https://app.decimal.ai/s/brycewang-stanford-aas-artifact-evaluation/SKILL.md

Raw file: /s/brycewang-stanford-aas-artifact-evaluation/SKILL.md ↗ · machine-readable summary at /s/brycewang-stanford-aas-artifact-evaluation.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 7

Prompt

我想在投《自动化学报》的控制论文中把帮我生成仿真代码的 ChatGPT 4o 列为第三作者，并在正文中列出其具体贡献。请评估这样处理是否符合期刊关于生成式 AI 的最新规定，以及应如何处理。

What was checked, without and with the skill
Checked	Without skill	With skill
Explicitly states that generative AI tools cannot be listed as co-authors under journal policy.	Passed	Passed
Labels specific detailed requirements for generative AI assistance disclosure as '待核实'.	Missed	Passed

case-04 · gemini-3.6-flash · 8/15/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md117 linessingle file

《自动化学报》代码与数据可用性

本技能讲清投向《自动化学报》(Acta Automatica Sinica, AAS) 的稿件在代码与数据可用性上的现状与做法。与部分国际会议不同，中文期刊多以同行评议为主，本刊是否设有独立的制品评审(artifact evaluation)徽章制度尚未见公开说明（待核实）。以下于 2026-07-09 核验框架（见 resources/official-source-map.md）。

一、现状说明（不杜撰）

AAS 实行双盲三审制，以稿件本身的理论与实验质量为主要评判依据。
是否强制或鼓励提交代码/数据、是否有独立徽章：官方未见明确公开细则，标 待核实；作者可主动提供以增强说服力。
本刊明确不接收 AI 工具作为署名作者；若用生成式 AI 辅助，按当期政策据实披露（细则 待核实）。

二、为何主动提供制品

即使无徽章制度，主动提供匿名、可复现的代码与数据，能：

让外审直接核对稳定性/性能结论，降低对结果可靠性的疑虑。
体现研究严谨与透明，增强录用说服力。
便于见刊后同行复现，提升影响力。

三、制品组织（配合双盲）

artifact/
  README.md      # 环境、数据、一键运行、预期结果、硬件
  env/           # requirements/environment/Dockerfile
  data/          # 数据或获取脚本 + 校验和
  src/           # 方法与基线
  configs/       # 实验配置与随机种子
  scripts/       # run_all.sh
  results/       # 关键指标供校验

制品须匿名：README、仓库名、路径、账户不得泄露作者身份（双盲，见 aas-submission）。
用匿名 Git 快照或匿名分享链接；勿指向作者主页。

四、控制/自动化类制品要点

Track record

Benchmark

19 / 21

test cases passed, vs 11 / 21 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

brycewang-stanford / awesome-journal-skills

Acta-Automatica-Sinica-Skills/skills/aas-artifact-evaluation/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

Other skills for the same job

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.