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Aetherlang Karpathy Skill

v1.0.3

API connector for AetherLang Omega — execute 10 Karpathy-inspired agent node types (plan, code_interpreter, critique, router, ensemble, memory, tool, loop, t...

2· 842·2 current·2 all-time
byHlias Staurou@contrario

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Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Aetherlang Karpathy Skill" (contrario/aetherlang-karpathy-skill) from ClawHub.
Skill page: https://clawhub.ai/contrario/aetherlang-karpathy-skill
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

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openclaw skills install contrario/aetherlang-karpathy-skill

ClawHub CLI

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npx clawhub@latest install aetherlang-karpathy-skill
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
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.
Assessment
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.

Like a lobster shell, security has layers — review code before you run it.

aetherlangvk9725kw4f3vjm0esym3rt270q982mxb7agentvk9725kw4f3vjm0esym3rt270q982mxb7aivk97a8wjwzfpj542zefv3ddhs3982cwawapivk9725kw4f3vjm0esym3rt270q982mxb7karpathyvk9725kw4f3vjm0esym3rt270q982mxb7latestvk9725kw4f3vjm0esym3rt270q982mxb7nodesvk9725kw4f3vjm0esym3rt270q982mxb7orchestrationvk97a8wjwzfpj542zefv3ddhs3982cwawworkflowvk97a8wjwzfpj542zefv3ddhs3982cwaw
842downloads
2stars
4versions
Updated 7h ago
v1.0.3
MIT-0

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 {\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 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

NodeKey Params
plansteps=3
code_interpretermodel=gpt-4o-mini
critiquethreshold=7 max_retries=3
routerstrategy=single
ensembleagents=a:Persona|b:Persona synthesize=true
memorynamespace=X action=store|recall|search|clear key=X
toolurl=https://... method=GET timeout=10
loopover=A|B|C target=NodeAlias max=10 mode=collect
transformmode=llm|template|extract|format instruction=X
paralleltargets=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.

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