evm-token-decimals
affaan-m/everything-claude-code
Prevent silent decimal mismatch bugs across EVM chains with runtime lookup and chain-aware caching.
What is evm-token-decimals?
Handles ERC-20 token decimal precision safely across multiple EVM chains. Use this when reading balances, calculating fiat values, comparing amounts across chains, or handling bridged assets to avoid off-by-magnitude errors.
- Query token decimals at runtime instead of hardcoding
- Cache decimals by (chain_id, token_address) pair to avoid repeated calls
- Normalize token amounts to consistent decimal precision (e.g., 18-decimal WAD)
- Handle non-standard or reverted decimals() calls defensively with fallbacks
- Support Python, TypeScript, Solidity, and CLI implementations
How to install evm-token-decimals
npx skills add https://github.com/affaan-m/everything-claude-code --skill evm-token-decimalsHow to use evm-token-decimals
- 1.Query decimals() at runtime for each token using the provided ERC-20 ABI
- 2.Cache the result by chain ID and token address to avoid repeated RPC calls
- 3.Use exact arithmetic (Decimal, BigInt) instead of floats when normalizing amounts
- 4.Divide raw balances by 10^decimals to get human-readable values
- 5.Re-query decimals after bridging or wrapper changes to catch precision drift
Use cases
- Building portfolio trackers that aggregate balances across multiple EVM chains
- Calculating USD values from on-chain token balances without precision loss
- Comparing stablecoin amounts across different chains where decimals may differ
- Handling bridged token assets that may have different decimal precision than originals
- Creating DeFi bots that need exact arithmetic for swaps and transfers
- DeFi developers building bots, dashboards, or aggregators
- Smart contract developers normalizing token amounts in Solidity
- Python/TypeScript backend engineers reading on-chain balances
- Portfolio tracker builders
- Anyone handling multi-chain token arithmetic
evm-token-decimals FAQ
Most symbols exist on multiple chains with different decimals. USDC is 6 on some chains and 18 on others. Always query at runtime.
Catch the exception, log a warning with the chain and token address, and default to 18. Keep the fallback visible in logs.
Cache by (chain_id, token_address) tuple. The same token address on different chains may have different decimals.
Query decimals for each token on each chain, normalize to a consistent precision (e.g., 18-decimal WAD), then compare.
Use Decimal (Python), BigInt (JavaScript), or Solidity's native uint256. Never use float for token arithmetic.
Full instructions (SKILL.md)
Source of truth, from affaan-m/everything-claude-code.
name: evm-token-decimals description: Prevent silent decimal mismatch bugs across EVM chains. Covers runtime decimal lookup, chain-aware caching, bridged-token precision drift, and safe normalization for bots, dashboards, and DeFi tools. metadata: origin: ECC direct-port adaptation version: "1.0.0"
EVM Token Decimals
Silent decimal mismatches are one of the easiest ways to ship balances or USD values that are off by orders of magnitude without throwing an error.
When to Use
- Reading ERC-20 balances in Python, TypeScript, or Solidity
- Calculating fiat values from on-chain balances
- Comparing token amounts across multiple EVM chains
- Handling bridged assets
- Building portfolio trackers, bots, or aggregators
How It Works
Never assume stablecoins use the same decimals everywhere. Query decimals() at runtime, cache by (chain_id, token_address), and use decimal-safe math for value calculations.
Examples
Query decimals at runtime
from decimal import Decimal
from web3 import Web3
ERC20_ABI = [
{"name": "decimals", "type": "function", "inputs": [],
"outputs": [{"type": "uint8"}], "stateMutability": "view"},
{"name": "balanceOf", "type": "function",
"inputs": [{"name": "account", "type": "address"}],
"outputs": [{"type": "uint256"}], "stateMutability": "view"},
]
def get_token_balance(w3: Web3, token_address: str, wallet: str) -> Decimal:
contract = w3.eth.contract(
address=Web3.to_checksum_address(token_address),
abi=ERC20_ABI,
)
decimals = contract.functions.decimals().call()
raw = contract.functions.balanceOf(Web3.to_checksum_address(wallet)).call()
return Decimal(raw) / Decimal(10 ** decimals)
Do not hardcode 1_000_000 because a symbol usually has 6 decimals somewhere else.
Cache by chain and token
from functools import lru_cache
@lru_cache(maxsize=512)
def get_decimals(chain_id: int, token_address: str) -> int:
w3 = get_web3_for_chain(chain_id)
contract = w3.eth.contract(
address=Web3.to_checksum_address(token_address),
abi=ERC20_ABI,
)
return contract.functions.decimals().call()
Handle odd tokens defensively
try:
decimals = contract.functions.decimals().call()
except Exception:
logging.warning(
"decimals() reverted on %s (chain %s), defaulting to 18",
token_address,
chain_id,
)
decimals = 18
Log the fallback and keep it visible. Old or non-standard tokens still exist.
Normalize to 18-decimal WAD in Solidity
interface IERC20Metadata {
function decimals() external view returns (uint8);
}
function normalizeToWad(address token, uint256 amount) internal view returns (uint256) {
uint8 d = IERC20Metadata(token).decimals();
if (d == 18) return amount;
if (d < 18) return amount * 10 ** (18 - d);
return amount / 10 ** (d - 18);
}
TypeScript with ethers
import { Contract, formatUnits } from 'ethers';
const ERC20_ABI = [
'function decimals() view returns (uint8)',
'function balanceOf(address) view returns (uint256)',
];
async function getBalance(provider: any, tokenAddress: string, wallet: string): Promise<string> {
const token = new Contract(tokenAddress, ERC20_ABI, provider);
const [decimals, raw] = await Promise.all([
token.decimals(),
token.balanceOf(wallet),
]);
return formatUnits(raw, decimals);
}
Quick on-chain check
cast call <token_address> "decimals()(uint8)" --rpc-url <rpc>
Rules
- Always query
decimals()at runtime - Cache by chain plus token address, not symbol
- Use
Decimal,BigInt, or equivalent exact math, not float - Re-query decimals after bridging or wrapper changes
- Normalize internal accounting consistently before comparison or pricing
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