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
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill feishu-notifygit clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleepWrote 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/feishu-notify)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/feishu-notify"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/feishu-notify/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/feishu-notify"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/feishu-notify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 4 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 Anti-Refusal · line 152 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- high Agent Snooping · line 48 Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
- medium Data Exfiltration · line 61 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 96 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00052 | $0.01598 |
| Opus 5 | $0.00026 | $0.00799 |
| Sonnet 5 | $0.00010 | $0.00320 |
| Haiku 4.5 | $0.00005 | $0.00160 |
Grade B, and why
feishu-notify scanned grade B with 2 findings 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 12d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat ~/.claude/feishu.json 2>/dev/null Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Bash(curl *), Bash(cat *), Read, Glob Copies of this mod
1 near-identical copy found in the catalogue:
- feishu-notify — 97% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feishu/Lark Notification
Send a notification: $ARGUMENTS
Overview
This skill provides Feishu/Lark integration for ARIS. It is designed as an internal utility — other skills call it at key events (experiment done, review scored, checkpoint waiting). It can also be invoked manually.
Zero-impact guarantee: If no feishu.json config exists, this skill does nothing and returns silently. All existing workflows are completely unaffected.
Configuration
The skill reads ~/.claude/feishu.json. If this file does not exist, all Feishu functionality is disabled — skills behave exactly as before.
Config Format
{
"mode": "push",
"webhook_url": "https://open.feishu.cn/open-apis/bot/v2/hook/YOUR_WEBHOOK_ID",
"interactive": {
"bridge_url": "http://localhost:5000",
"timeout_seconds": 300
}
}
Modes
| Mode | "mode" value |
What it does | Requires |
|---|---|---|---|
| Off | "off" or file absent |
Nothing. Pure CLI as-is | Nothing |
| Push only | "push" |
Send webhook notifications at key events. Mobile push, no reply | Feishu bot webhook URL |
| Interactive | "interactive" |
Full bidirectional. Approve/reject from Feishu, reply to checkpoints | feishu-claude-code running |
Workflow
Step 1: Read Config
cat ~/.claude/feishu.json 2>/dev/null
- File not found → return silently, do nothing
"mode": "off"→ return silently, do nothing"mode": "push"→ proceed to Step 2 (push)"mode": "interactive"→ proceed to Step 3 (interactive)
Step 2: Push Notification (webhook)
Send a rich card to the Feishu webhook:
curl -s -X POST "$WEBHOOK_URL" \
-H "Content-Type: application/json" \
-d '{
"msg_type": "interactive",
"card": {
"header": {
"title": {"tag": "plain_text", "content": "TITLE"},
"template": "COLOR"
},
"elements": [
{"tag": "markdown", "content": "BODY"}
]
}
}'
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.
- 12d ago First seen · 157 lines · 52 tokens per session scan B 1a6c2e7a92b4
feishu-notify is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (15,970 stars, last pushed 2d ago), licensed MIT. It adds 52 tokens to every session and 1,598 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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