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Aetherlang Karpathy Skill

by Hlias Staurou · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ⚠ suspicious
899
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Install in OpenClaw
/install aetherlang-karpathy-skill
Description
API connector for AetherLang Omega — execute 10 Karpathy-inspired agent node types (plan, code_interpreter, critique, router, ensemble, memory, tool, loop, t...
README (SKILL.md)

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 tool node calls public REST URLs you specify. Only use trusted, public APIs. Never pass credentials or private URLs as tool parameters. 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.

Usage Guidance
This skill appears to do what it says (send flow code + query to a hosted AetherLang API). Before installing or using it: 1) Do not send secrets, API keys, or sensitive PII — the service documents server-side memory and server-side Python execution, so anything sent can be persisted or executed remotely. 2) Verify the operator and privacy/data-retention policy (api.neurodoc.app / masterswarm.net / Hetzner EU) and understand how long 'memory' is retained and who can access it. 3) Treat 'public API, no auth' with caution — endpoints can change or begin requiring auth later. 4) Test with non-sensitive inputs first and confirm the agent actually follows the SKILL.md minimization guidance (check request payloads or network logs if possible). If you need strong guarantees against data exfiltration or remote code execution, avoid connectors that run code or persist data on third-party servers.
Capability Analysis
Type: OpenClaw Skill Name: aetherlang-karpathy-skill Version: 1.0.3 The skill functions as a remote API connector to `api.neurodoc.app` and introduces several high-risk capabilities, most notably a `tool` node that allows the agent to execute arbitrary network requests (GET/POST) to any URL. It also includes a `memory` node that stores data on the remote server and a `code_interpreter` that executes logic server-side. While SKILL.md contains explicit 'Data Minimization' instructions to prevent the agent from sending secrets or PII, the inherent ability to exfiltrate data via the `tool` node or store it on a third-party infrastructure (NeuroDoc Pro/Hetzner EU) warrants a suspicious classification.
Capability Assessment
Purpose & Capability
Name, description, and declared behavior match the artifacts: an API connector that posts flow code and a user query to https://api.neurodoc.app/aetherlang/execute. No binaries, env vars, or local installs are requested — that is proportionate for an API-only connector.
Instruction Scope
SKILL.md narrowly instructs the agent to send only the user's query and flow code and to avoid system prompts, conversation history, files, or credentials. This stays within the stated purpose. Caveats: the skill relies on the agent to actually enforce data minimization; it also documents server-side features (sandboxed Python code_interpreter and server-side memory) that mean user data may be executed or persist on the remote host — a privacy/security consideration beyond local scope.
Install Mechanism
Instruction-only skill with no install spec and no code files. No artifacts are written to disk by the skill itself, which minimizes installation risk.
Credentials
The skill requests no environment variables or credentials (proportionate). However, the documented capabilities imply data will be sent to and possibly stored/executed on a third-party service (memory node: persistent server-side state; code_interpreter: server-side execution). That is expected for this connector but represents a potential data-exposure vector that users should consider before sending secrets or PII.
Persistence & Privilege
Skill does not request always:true and does not modify agent or system configuration. It does describe server-side persistence (memory node) but that is a remote-service behavior, not a privileged change to the agent environment.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install aetherlang-karpathy-skill
  3. After installation, invoke the skill by name or use /aetherlang-karpathy-skill
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
v1.0.3: Karpathy-inspired, operator_note added
v1.0.2
v1.0.2: Consent gates for memory (server-side persistence) and tool (arbitrary URL) nodes, privacy policy link, operator clarification
v1.0.1
v1.0.1: Clarified API connector nature, tool node security note, provenance
v1.0.0
aetherlang-karpathy-skill 1.0.0 - Initial release of the skill, implementing 10 advanced AI agent node types based on Karpathy's agent framework vision. - Enables features such as self-programming plans, sandboxed code execution, critique loops, intelligent routing, ensemble agents, persistent memory, API tool use, iterative loops, data transforms, and parallel execution. - Includes universal 3-step integration pattern for any Python-based DSL/runtime: add node types, dispatch in runtime, and implement async execution handlers. - Provides detailed implementation instructions, safety guidelines, and example code for each node type starting with PLAN and CODE_INTERPRETER nodes. - Suitable for enriching workflow engines, orchestration frameworks, and agent-based pipelines, especially with AetherLang or similar systems.
Metadata
Slug aetherlang-karpathy-skill
Version 1.0.3
License MIT-0
All-time Installs 2
Active Installs 2
Total Versions 4
Frequently Asked Questions

What is Aetherlang Karpathy Skill?

API connector for AetherLang Omega — execute 10 Karpathy-inspired agent node types (plan, code_interpreter, critique, router, ensemble, memory, tool, loop, t... It is an AI Agent Skill for Claude Code / OpenClaw, with 899 downloads so far.

How do I install Aetherlang Karpathy Skill?

Run "/install aetherlang-karpathy-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Aetherlang Karpathy Skill free?

Yes, Aetherlang Karpathy Skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Aetherlang Karpathy Skill support?

Aetherlang Karpathy Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Aetherlang Karpathy Skill?

It is built and maintained by Hlias Staurou (@contrario); the current version is v1.0.3.

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