aetherlang-karpathy-skill

name	aetherlang-karpathy-skill
description	Execute advanced AI agent workflows via the AetherLang Omega API — 10 Karpathy node types including self-programming plans, sandboxed code execution, critique loops, intelligent routing, multi-agent ensemble, persistent memory, external API tools, iterative loops, data transforms, and parallel execution. Use when the user wants to run agent pipelines, multi-agent synthesis, batch processing, live API data analysis, or any autonomous AI workflow through AetherLang.
homepage	https://clawhub.ai/contrario

AetherLang Karpathy Agent Nodes

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 Privacy Policy: https://masterswarm.net (footer → Privacy Policy) Operator: NeuroDoc Pro — api.neurodoc.app and masterswarm.net are the same operator (Hetzner DE)

Data Minimization

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
• Do NOT include personally identifiable information unless explicitly requested

Request Format

curl -s -X POST https://api.neurodoc.app/aetherlang/execute \
  -H "Content-Type: application/json" \
  -d '{
    "code": "flow FlowName {\n  input text query;\n  node X: <type> <params>;\n  query -> X;\n  output text result from X;\n}",
    "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. 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.

Consent required: Before using a memory node, notify the user: "This flow will store data server-side at api.neurodoc.app. Proceed? (y/n)" Only proceed with explicit user confirmation.

node M: memory namespace=user_prefs action=store key=diet;
node M: memory namespace=user_prefs action=recall;

7. tool — External API Access

Consent required: Before executing a tool node, notify the user: "This flow will call [URL]. Proceed? (y/n)" Only proceed with explicit confirmation. Never forward PII or credentials to external URLs. Call any public REST API.

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