genlayer-dev-claw-skill
Build GenLayer Intelligent Contracts - Python smart contracts with LLM calls and web access. Use for writing/deploying contracts, SDK reference, CLI commands, equivalence principles, storage types. Triggers: write intelligent contract, genlayer contract, genvm, gl.Contract, deploy genlayer, genlayer CLI, genlayer SDK, DynArray, TreeMap, gl.nondet, gl.eq_principle, prompt_comparative, strict_eq, genlayer deploy, genlayer up. (For explaining GenLayer concepts, use genlayer-claw-skill instead.)
Install
mkdir -p .claude/skills/genlayer-dev-claw-skill && curl -L -o skill.zip "https://mcp.directory/api/skills/download/8461" && unzip -o skill.zip -d .claude/skills/genlayer-dev-claw-skill && rm skill.zipInstalls to .claude/skills/genlayer-dev-claw-skill
About this skill
GenLayer Intelligent Contracts
GenLayer enables Intelligent Contracts - Python smart contracts that can call LLMs, fetch web data, and handle non-deterministic operations while maintaining blockchain consensus.
Quick Start
Minimal Contract
# v0.1.0
# { "Depends": "py-genlayer:latest" }
from genlayer import *
class MyContract(gl.Contract):
value: str
def __init__(self, initial: str):
self.value = initial
@gl.public.view
def get_value(self) -> str:
return self.value
@gl.public.write
def set_value(self, new_value: str) -> None:
self.value = new_value
Contract with LLM
# v0.1.0
# { "Depends": "py-genlayer:latest" }
from genlayer import *
import json
class AIContract(gl.Contract):
result: str
def __init__(self):
self.result = ""
@gl.public.write
def analyze(self, text: str) -> None:
prompt = f"Analyze this text and respond with JSON: {text}"
def get_analysis():
return gl.nondet.exec_prompt(prompt)
# All validators must get the same result
self.result = gl.eq_principle.strict_eq(get_analysis)
@gl.public.view
def get_result(self) -> str:
return self.result
Contract with Web Access
# v0.1.0
# { "Depends": "py-genlayer:latest" }
from genlayer import *
class WebContract(gl.Contract):
content: str
def __init__(self):
self.content = ""
@gl.public.write
def fetch(self, url: str) -> None:
url_copy = url # Capture for closure
def get_page():
return gl.nondet.web.render(url_copy, mode="text")
self.content = gl.eq_principle.strict_eq(get_page)
@gl.public.view
def get_content(self) -> str:
return self.content
Core Concepts
Contract Structure
- Version header:
# v0.1.0(required) - Dependencies:
# { "Depends": "py-genlayer:latest" } - Import:
from genlayer import * - Class: Extend
gl.Contract(only ONE per file) - State: Class-level typed attributes
- Constructor:
__init__(not public) - Methods: Decorated with
@gl.public.viewor@gl.public.write
Method Decorators
| Decorator | Purpose | Can Modify State |
|---|---|---|
@gl.public.view | Read-only queries | No |
@gl.public.write | State mutations | Yes |
@gl.public.write.payable | Receive value + mutate | Yes |
Storage Types
Replace standard Python types with GenVM storage-compatible types:
| Python Type | GenVM Type | Usage |
|---|---|---|
int | u32, u64, u256, i32, i64, etc. | Sized integers |
int (unbounded) | bigint | Arbitrary precision (avoid) |
list[T] | DynArray[T] | Dynamic arrays |
dict[K,V] | TreeMap[K,V] | Ordered maps |
str | str | Strings (unchanged) |
bool | bool | Booleans (unchanged) |
⚠️ int is NOT supported! Always use sized integers.
Address Type
# Creating addresses
addr = Address("0x03FB09251eC05ee9Ca36c98644070B89111D4b3F")
# Get sender
sender = gl.message.sender_address
# Conversions
hex_str = addr.as_hex # "0x03FB..."
bytes_val = addr.as_bytes # bytes
Custom Data Types
from dataclasses import dataclass
@allow_storage
@dataclass
class UserData:
name: str
balance: u256
active: bool
class MyContract(gl.Contract):
users: TreeMap[Address, UserData]
Non-Deterministic Operations
The Problem
LLMs and web fetches produce different results across validators. GenLayer solves this with the Equivalence Principle.
Equivalence Principles
1. Strict Equality (strict_eq)
All validators must produce identical results.
def get_data():
return gl.nondet.web.render(url, mode="text")
result = gl.eq_principle.strict_eq(get_data)
Best for: Factual data, boolean results, exact matches.
2. Prompt Comparative (prompt_comparative)
LLM compares leader's result against validators' results using criteria.
def get_analysis():
return gl.nondet.exec_prompt(prompt)
result = gl.eq_principle.prompt_comparative(
get_analysis,
"The sentiment classification must match"
)
Best for: LLM tasks where semantic equivalence matters.
3. Prompt Non-Comparative (prompt_non_comparative)
Validators verify the leader's result meets criteria (don't re-execute).
result = gl.eq_principle.prompt_non_comparative(
lambda: input_data, # What to process
task="Summarize the key points",
criteria="Summary must be under 100 words and factually accurate"
)
Best for: Expensive operations, subjective tasks.
4. Custom Leader/Validator Pattern
result = gl.vm.run_nondet(
leader=lambda: expensive_computation(),
validator=lambda leader_result: verify(leader_result)
)
Non-Deterministic Functions
| Function | Purpose |
|---|---|
gl.nondet.exec_prompt(prompt) | Execute LLM prompt |
gl.nondet.web.render(url, mode) | Fetch web page (mode="text" or "html") |
⚠️ Rules:
- Must be called inside equivalence principle functions
- Cannot access storage directly
- Copy storage data to memory first with
gl.storage.copy_to_memory()
Contract Interactions
Call Other Contracts
# Dynamic typing
other = gl.get_contract_at(Address("0x..."))
result = other.view().some_method()
# Static typing (better IDE support)
@gl.contract_interface
class TokenInterface:
class View:
def balance_of(self, owner: Address) -> u256: ...
class Write:
def transfer(self, to: Address, amount: u256) -> bool: ...
token = TokenInterface(Address("0x..."))
balance = token.view().balance_of(my_address)
Emit Messages (Async Calls)
other = gl.get_contract_at(addr)
other.emit(on='accepted').update_status("active")
other.emit(on='finalized').confirm_transaction()
Deploy Contracts
child_addr = gl.deploy_contract(code=contract_code, salt=u256(1))
EVM Interop
@gl.evm.contract_interface
class ERC20:
class View:
def balance_of(self, owner: Address) -> u256: ...
class Write:
def transfer(self, to: Address, amount: u256) -> bool: ...
token = ERC20(evm_address)
balance = token.view().balance_of(addr)
token.emit().transfer(recipient, u256(100)) # Messages only on finality
CLI Commands
Setup
npm install -g genlayer
genlayer init # Download components
genlayer up # Start local network
Deployment
# Direct deploy
genlayer deploy --contract my_contract.py
# With constructor args
genlayer deploy --contract my_contract.py --args "Hello" 42
# To testnet
genlayer network set testnet-asimov
genlayer deploy --contract my_contract.py
Interaction
# Read (view methods)
genlayer call --address 0x... --function get_value
# Write
genlayer write --address 0x... --function set_value --args "new_value"
# Get schema
genlayer schema --address 0x...
# Check transaction
genlayer receipt --tx-hash 0x...
Networks
genlayer network # Show current
genlayer network list # Available networks
genlayer network set localnet # Local dev
genlayer network set studionet # Hosted dev
genlayer network set testnet-asimov # Testnet
Best Practices
Prompt Engineering
prompt = f"""
Analyze this text and classify the sentiment.
Text: {text}
Respond using ONLY this JSON format:
{{"sentiment": "positive" | "negative" | "neutral", "confidence": float}}
Output ONLY valid JSON, no other text.
"""
Security: Prompt Injection
- Restrict inputs: Minimize user-controlled text in prompts
- Restrict outputs: Define exact output formats
- Validate: Check parsed results match expected schema
- Simplify logic: Clear contract flow reduces attack surface
Error Handling
from genlayer import UserError
@gl.public.write
def safe_operation(self, value: int) -> None:
if value <= 0:
raise UserError("Value must be positive")
# ... proceed
Memory Management
# Copy storage to memory for non-det blocks
data_copy = gl.storage.copy_to_memory(self.some_data)
def process():
return gl.nondet.exec_prompt(f"Process: {data_copy}")
result = gl.eq_principle.strict_eq(process)
Common Patterns
Token with AI Transfer Validation
See references/examples.md → LLM ERC20
Prediction Market
See references/examples.md → Football Prediction Market
Vector Search / Embeddings
See references/examples.md → Log Indexer
Debugging
- GenLayer Studio: Use
genlayer upfor local testing - Logs: Filter by transaction hash, debug level
- Print statements:
print()works in contracts (debug only)
Reference Files
references/sdk-api.md- Complete SDK API referencereferences/equivalence-principles.md- Consensus patterns in depthreferences/examples.md- Full annotated contract examples (incl. production oracle)references/deployment.md- CLI, networks, deployment workflowreferences/genvm-internals.md- VM architecture, storage, ABI details
Links
- Docs: https://docs.genlayer.com
- SDK: https://sdk.genlayer.com
- Studio: https://studio.genlayer.com
- GitHub: https://github.com/genlayerlabs
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