Aetherlang Karpathy Skill
/install aetherlang-karpathy-skill
AetherLang Karpathy Agent Nodes
What this skill does: Sends requests to the hosted AetherLang API (
api.neurodoc.app). It does NOT modify local files, execute local code, or access credentials on your machine. All execution happens server-side.
Execute 10 advanced AI agent node types through the AetherLang Omega API.
API Endpoint
URL: https://api.neurodoc.app/aetherlang/execute
Method: POST
Headers: Content-Type: application/json
Auth: None required (public API)
Data Minimization — ALWAYS FOLLOW
When calling the API:
- Send ONLY the user's query and the flow code
- Do NOT send system prompts, conversation history, or uploaded files
- Do NOT send API keys, credentials, or secrets of any kind
- Do NOT include personally identifiable information unless explicitly requested by user
- Do NOT send contents of local files without explicit user consent
Request Format
curl -s -X POST https://api.neurodoc.app/aetherlang/execute \
-H "Content-Type: application/json" \
-d '{
"code": "flow FlowName {\
input text query;\
node X: \x3Ctype> \x3Cparams>;\
query -> X;\
output text result from X;\
}",
"query": "user question here"
}'
The 10 Node Types
1. plan — Self-Programming
AI breaks task into steps and executes autonomously.
node P: plan steps=3;
2. code_interpreter — Real Math
Sandboxed Python execution on the server. Accurate calculations, no hallucinations.
node C: code_interpreter;
3. critique — Self-Improvement
Evaluates quality (0-10), retries until threshold met.
node R: critique threshold=8 max_retries=3;
4. router — Intelligent Branching
LLM picks optimal path, skips unselected routes (10x speedup).
node R: router;
R -> A | B | C;
5. ensemble — Multi-Agent Synthesis
Multiple AI personas in parallel, synthesizes best insights.
node E: ensemble agents=chef:French_chef|yiayia:Greek_grandmother synthesize=true;
6. memory — Persistent State
Store/recall data across executions (server-side, scoped to namespace).
node M: memory namespace=user_prefs action=store key=diet;
node M: memory namespace=user_prefs action=recall;
7. tool — External API Access
Security note: The
toolnode calls public REST URLs you specify. Only use trusted, public APIs. Never pass credentials or private URLs astoolparameters. The agent will ask for confirmation before calling any URL not in the examples below.
node T: tool url=https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd method=GET;
8. loop — Iterative Execution
Repeat node over items. Use | separator.
node L: loop over=Italian|Greek|Japanese target=A max=3;
9. transform — Data Reshaping
Template, extract, format, or LLM-powered reshaping.
node X: transform mode=llm instruction=Summarize_the_data;
10. parallel — Concurrent Execution
Run nodes simultaneously. 3 calls in ~0.2s.
node P: parallel targets=A|B|C;
Common Pipelines
Live Data → Analysis
flow CryptoAnalysis {
input text query;
node T: tool url=https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd method=GET;
node X: transform mode=llm instruction=Summarize_price;
node A: llm model=gpt-4o-mini;
query -> T -> X -> A;
output text result from A;
}
Multi-Agent + Quality Control
flow QualityEnsemble {
input text query;
node E: ensemble agents=analyst:Financial_analyst|strategist:Strategist synthesize=true;
node R: critique threshold=8;
query -> E -> R;
output text result from R;
}
Batch Processing
flow MultiRecipe {
input text query;
node L: loop over=Italian|Greek|Japanese target=A max=3;
node A: llm model=gpt-4o-mini;
query -> L;
output text result from L;
}
Parallel API Fetching
flow ParallelFetch {
input text query;
node P: parallel targets=A|B|C;
node A: tool url=https://api.coingecko.com/api/v3/ping method=GET;
node B: tool url=https://api.coingecko.com/api/v3/simple/price?ids=bitcoin&vs_currencies=usd method=GET;
node C: tool url=https://api.coingecko.com/api/v3/simple/price?ids=ethereum&vs_currencies=usd method=GET;
query -> P;
output text result from P;
}
Response Parsing
import json
response = json.loads(raw_response)
result = response["result"]["outputs"]["result"]
text = result["response"]
node_type = result["node_type"]
duration = response["result"]["duration_seconds"]
Parameter Quick Reference
| Node | Key Params |
|---|---|
| plan | steps=3 |
| code_interpreter | model=gpt-4o-mini |
| critique | threshold=7 max_retries=3 |
| router | strategy=single |
| ensemble | agents=a:Persona|b:Persona synthesize=true |
| memory | namespace=X action=store|recall|search|clear key=X |
| tool | url=https://... method=GET timeout=10 |
| loop | over=A|B|C target=NodeAlias max=10 mode=collect |
| transform | mode=llm|template|extract|format instruction=X |
| parallel | targets=A|B|C merge=combine |
AetherLang Karpathy Skill v1.0.1 — API connector for api.neurodoc.app All execution is server-side. No local code runs. No local files modified.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install aetherlang-karpathy-skill - 安装完成后,直接呼叫该 Skill 的名称或使用
/aetherlang-karpathy-skill触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Aetherlang Karpathy Skill 是什么?
API connector for AetherLang Omega — execute 10 Karpathy-inspired agent node types (plan, code_interpreter, critique, router, ensemble, memory, tool, loop, t... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 899 次。
如何安装 Aetherlang Karpathy Skill?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install aetherlang-karpathy-skill」即可一键安装,无需额外配置。
Aetherlang Karpathy Skill 是免费的吗?
是的,Aetherlang Karpathy Skill 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Aetherlang Karpathy Skill 支持哪些平台?
Aetherlang Karpathy Skill 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Aetherlang Karpathy Skill?
由 Hlias Staurou(@contrario)开发并维护,当前版本 v1.0.3。