almanak-strategy-builder

name	almanak-strategy-builder
description	Build, test, and deploy DeFi trading strategies using the Almanak SDK. ALWAYS use this skill when the user mentions almanak, DeFi strategy, trading strategy, yield farming, liquidity provision, token swap, borrowing, lending, perpetuals, staking, vault deposit, bridging tokens, backtesting, paper trading, or on-chain execution. Use for writing strategy.py files, composing intents (Swap, LP, Borrow, Supply, Perp, Bridge, Stake, Vault, Prediction), working with config.json strategy parameters, running almanak strat or almanak gateway CLI commands, or debugging strategy execution on Anvil forks. Do NOT use for general smart contract development, Solidity code, or non-strategy SDK internals.
metadata	{"version":"2.15.0","author":"Almanak","license":"Apache-2.0","type":"documentation"}

Almanak Strategy Builder

You are helping a quant build DeFi strategies using the Almanak SDK. Strategies are Python classes that return Intent objects. The framework handles compilation to transactions, execution, and state management.

Security Model

This file is documentation for AI coding assistants - it contains no executable code or live credentials.

The Almanak SDK uses a gateway-isolated architecture:

• Strategy containers have no direct access to secrets, RPC endpoints, or external APIs.
• All external access is mediated through a gRPC gateway sidecar.
• In production, secrets are injected by the platform secret manager into the gateway - never into the strategy container.
• The .env file referenced below is for local development only and is never deployed to production environments.
• Private keys in .env are used solely for local Anvil fork testing and have no access to mainnet funds in production.

See the Gateway section for details.

IMPORTANT — Zodiac permissions auto-generation: Whenever you create a new strategy or modify strategy.py in a way that changes protocols, intent types, tokens, or chains, you MUST regenerate the Zodiac Roles permission manifest by running almanak strat permissions -o permissions.json from the strategy directory. The file MUST be named exactly permissions.json — the platform deploy pipeline hardcodes this filename. This ensures the Safe wallet permissions stay in sync with the strategy's actual contract interactions. Always do this as a final step after writing or editing strategy code.

Quick Start

# Install the CLI globally
pipx install almanak

# Scaffold a new strategy (creates a self-contained Python project)
almanak strat new --template mean_reversion --name my_rsi --chain arbitrum

# Run on local Anvil fork (auto-starts gateway + Anvil)
cd my_rsi
almanak strat run --network anvil --once

# Run a single iteration on mainnet
almanak strat run --once

# Browse and copy a working demo strategy
almanak strat demo

Each scaffolded strategy is a self-contained Python project with its own pyproject.toml, .venv/, and uv.lock. The same files drive both local development and the platform's cloud Docker build.

Strategy project structure:

my_strategy/
  strategy.py        # IntentStrategy subclass with decide() method
  config.json        # Runtime parameters (tokens, thresholds, funding)
  pyproject.toml     # Dependencies + [tool.almanak] metadata
  uv.lock            # Locked dependencies (created by uv sync)
  .venv/             # Per-strategy virtual environment
  .env               # Local dev credentials (not deployed; see Security Model)
  .gitignore         # Git ignore rules
  .python-version    # Python version pin (3.12)
  __init__.py        # Package exports
  tests/             # Test scaffold
  AGENTS.md          # AI agent guide

pyproject.toml example:

[project]
name = "my-strategy"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
    "almanak>=2.4.0",
]

[tool.almanak.run]
interval = 60

The [tool.almanak.run] section is required — it sets the execution interval (in seconds) for the strategy loop in production. Always include it when writing pyproject.toml manually.

Adding dependencies:

uv add pandas-ta          # Updates pyproject.toml + uv.lock + .venv/
uv run pytest tests/ -v   # Run tests in the strategy's venv

For Anvil testing, add anvil_funding to config.json so your wallet is auto-funded on fork start (see Configuration below).

# strategy.py
from decimal import Decimal
from almanak import MarketSnapshot
from almanak.framework.strategies import IntentStrategy, almanak_strategy
from almanak.framework.intents import Intent

@almanak_strategy(
    name="my_strategy",
    version="1.0.0",
    supported_chains=["arbitrum"],
    supported_protocols=["uniswap_v3"],
    intent_types=["SWAP", "HOLD"],
    default_chain="arbitrum",
)
class MyStrategy(IntentStrategy):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.trade_size = Decimal(str(self.config.get("trade_size_usd", "100")))

    def decide(self, market: MarketSnapshot) -> Intent | None:
        rsi = market.rsi("WETH", period=14)
        if rsi.value < 30:
            return Intent.swap(
                from_token="USDC", to_token="WETH",
                amount_usd=self.trade_size, max_slippage=Decimal("0.005"),
            )
        return Intent.hold(reason=f"RSI={rsi.value:.1f}, waiting")

Note: amount_usd= requires a live price oracle from the gateway. If swaps revert with "Too little received", switch to amount= (token units) which bypasses USD-to-token conversion. Always verify pricing on first live run with --dry-run --once.

Core Concepts

IntentStrategy

All strategies inherit from IntentStrategy and implement one method:

def decide(self, market: MarketSnapshot) -> Intent | None

The framework calls decide() on each iteration with a fresh MarketSnapshot. Return an Intent object (swap, LP, borrow, etc.) or Intent.hold().

Lifecycle

1. __init__: Extract config parameters, set up state
2. decide(market): Called each iteration - return an Intent
3. on_intent_executed(intent, success, result): Optional callback after execution
4. get_status(): Optional - return dict for monitoring dashboards
5. supports_teardown() / generate_teardown_intents(): Optional safe shutdown

@almanak_strategy Decorator

Attaches metadata used by the framework and CLI:

@almanak_strategy(
    name="my_strategy",              # Unique identifier
    description="What it does",      # Human-readable description
    version="1.0.0",                 # Strategy version
    author="Your Name",              # Optional
    tags=["trading", "rsi"],         # Optional tags for discovery
    supported_chains=["arbitrum"],   # Which chains this runs on
    supported_protocols=["uniswap_v3"],  # Which protocols it uses
    intent_types=["SWAP", "HOLD"],   # Intent types it may return
    default_chain="arbitrum",        # Default chain for execution
)

IMPORTANT — Intent Type Teardown Complements: intent_types must include both the "open" and "close" side of every operation. These are used to generate Zodiac Roles permissions for Safe wallet deployments. If you declare the open side without its complement, the strategy will deploy but teardown will fail on-chain because the wallet lacks permission for the close operation.

If you declare...	You MUST also declare...
SUPPLY	WITHDRAW
BORROW	REPAY
LP_OPEN	LP_CLOSE
VAULT_DEPOSIT	VAULT_REDEEM
PERP_OPEN	PERP_CLOSE

The decorator emits a UserWarning at import time if complements are missing. The permission generator also auto-expands missing complements as a safety net, but always declare them explicitly.

Config Access

In __init__, read parameters from self.config (dict loaded from config.json):

def __init__(self, *args, **kwargs):
    super().__init__(*args, **kwargs)
    self.trade_size = Decimal(str(self.config.get("trade_size_usd", "100")))
    self.rsi_period = int(self.config.get("rsi_period", 14))
    self.base_token = self.config.get("base_token", "WETH")

Also available: self.chain (str), self.wallet_address (str), self.chains (list[str]), self.get_wallet_for_chain(chain) (str).

Intent Reference

All intents are created via Intent factory methods. Import:

from almanak.framework.intents import Intent

Trading

Intent.swap - Exchange tokens on a DEX

Intent.swap(
    from_token="USDC",           # Token to sell
    to_token="WETH",             # Token to buy
    amount_usd=Decimal("1000"),  # Amount in USD (use amount_usd OR amount)
    amount=Decimal("500"),       # Amount in token units (alternative to amount_usd)
    max_slippage=Decimal("0.005"),  # Max slippage (0.5%)
    max_price_impact=Decimal("0.30"),  # Optional: max quoter-vs-oracle deviation (default: 30%)
    protocol="uniswap_v3",      # Optional: specific DEX
    chain="arbitrum",            # Optional: override chain
    destination_chain="base",    # Optional: cross-chain swap
)

Use amount="all" to swap the entire balance.

amount= vs amount_usd=: Use amount_usd= to specify trade size in USD (requires a live price oracle from the gateway). Use amount= to specify exact token units (more reliable for live trading since it bypasses USD-to-token conversion). When in doubt, prefer amount= for mainnet.

Liquidity Provision

Intent.lp_open - Open a concentrated LP position

Intent.lp_open(
    pool="WETH/USDC",               # Pool identifier
    amount0=Decimal("1.0"),          # Amount of token0
    amount1=Decimal("2000"),         # Amount of token1
    range_lower=Decimal("1800"),     # Lower price bound
    range_upper=Decimal("2200"),     # Upper price bound
    protocol="uniswap_v3",          # Default: uniswap_v3
    chain=None,                      # Optional override
)

Intent.lp_close - Close an LP position

Intent.lp_close(
    position_id="12345",     # NFT token ID from lp_open result
    pool="WETH/USDC",        # Optional pool identifier
    collect_fees=True,       # Collect accumulated fees
    protocol="uniswap_v3",
)

Intent.collect_fees - Harvest LP fees without closing

Intent.collect_fees(
    pool="WETH/USDC",
    protocol="traderjoe_v2",
)

Lending / Borrowing

Intent.supply - Deposit collateral into a lending protocol

Intent.supply(
    protocol="aave_v3",
    token="WETH",
    amount=Decimal("10"),
    use_as_collateral=True,   # Enable as collateral (default: True)
    market_id=None,           # Required for Morpho Blue
)

Intent.borrow - Borrow tokens against collateral

Intent.borrow(
    protocol="aave_v3",
    collateral_token="WETH",
    collateral_amount=Decimal("10"),
    borrow_token="USDC",
    borrow_amount=Decimal("5000"),
    interest_rate_mode="variable",  # Aave: "variable" only (stable deprecated)
    market_id=None,                 # Required for Morpho Blue
)

Intent.repay - Repay borrowed tokens

Intent.repay(
    protocol="aave_v3",
    token="USDC",
    amount=Decimal("5000"),
    repay_full=False,        # Set True to repay entire debt
    market_id=None,
)

Intent.deleverage - Emergency repay triggered by risk management (e.g. HF below threshold)

Intent.deleverage(
    protocol="aave_v3",
    token="USDC",
    amount=Decimal("5000"),
    trigger_reason="health_factor_below_threshold",  # Human-readable reason for the deleverage
    observed_hf=Decimal("1.05"),   # Health factor at trigger time (persisted as health_factor_before)
    target_hf=Decimal("1.5"),      # Target HF after deleverage
    repay_full=False,              # Set True to repay entire debt
    market_id=None,
)

Compiles to the same on-chain execution as Intent.repay. The trigger_reason, observed_hf, and target_hf are stored in the accounting layer so dashboards can surface why the deleverage was forced. The observed_hf is persisted as health_factor_before in the accounting event. DELEVERAGE is a mandatory live event type (fail-closed) — the runner will log a WARNING when it detects a deleverage.

Intent.withdraw - Withdraw from lending protocol

Intent.withdraw(
    protocol="aave_v3",
    token="WETH",
    amount=Decimal("10"),
    withdraw_all=False,      # Set True to withdraw everything
    market_id=None,
    is_collateral=True,      # Morpho Blue only: True = collateral, False = loan token
)

Perpetuals

Intent.perp_open - Open a perpetual futures position

Intent.perp_open(
    market="ETH/USD",
    collateral_token="USDC",
    collateral_amount=Decimal("1000"),
    size_usd=Decimal("5000"),
    is_long=True,
    leverage=Decimal("5"),
    max_slippage=Decimal("0.01"),
    protocol="gmx_v2",
)

Intent.perp_close - Close a perpetual futures position

Intent.perp_close(
    market="ETH/USD",
    collateral_token="USDC",
    is_long=True,
    size_usd=None,               # None = close full position
    max_slippage=Decimal("0.01"),
    protocol="gmx_v2",
    position_id=None,            # Required for venues keyed on bytes32 (e.g. pancakeswap_perps)
)

Bridging

Intent.bridge - Cross-chain token transfer

Intent.bridge(
    token="USDC",
    amount=Decimal("1000"),
    from_chain="arbitrum",
    to_chain="base",
    max_slippage=Decimal("0.005"),
    preferred_bridge=None,       # Optional: specific bridge protocol
)

Staking

Intent.stake - Liquid staking deposit

Intent.stake(
    protocol="lido",
    token_in="ETH",
    amount=Decimal("10"),
    receive_wrapped=True,    # Receive wrapped token (e.g., wstETH)
)

Intent.unstake - Withdraw from liquid staking

Intent.unstake(
    protocol="lido",
    token_in="wstETH",
    amount=Decimal("10"),
    protocol_params=None,    # Optional: e.g. {"phase": "cooldown"} for Ethena
)

Flash Loans

Intent.flash_loan - Borrow and repay in a single transaction

Intent.flash_loan(
    provider="aave",         # "aave", "balancer", "morpho", or "auto"
    token="USDC",
    amount=Decimal("100000"),
    callback_intents=[...],  # Intents to execute with the borrowed funds
)

Vaults (ERC-4626)

Intent.vault_deposit - Deposit into an ERC-4626 vault

Intent.vault_deposit(
    protocol="metamorpho",           # Vault protocol
    vault_address="0x...",           # Vault contract address
    amount=Decimal("1000"),          # Amount of underlying to deposit (or "all")
    deposit_token="USDC",            # Underlying token symbol (for backtesting)
    chain="ethereum",                # Optional: override chain
)

Intent.vault_redeem - Redeem shares from an ERC-4626 vault

Intent.vault_redeem(
    protocol="metamorpho",           # Vault protocol
    vault_address="0x...",           # Vault contract address
    shares=Decimal("1000"),          # Shares to redeem (or "all")
    deposit_token="USDC",            # Underlying token symbol (for backtesting)
    chain="ethereum",                # Optional: override chain
)

Prediction Markets

Intent.prediction_buy(
    market_id="will-bitcoin-exceed-100000",  # Polymarket market ID or slug
    outcome="YES",                            # "YES" or "NO"
    amount_usd=Decimal("100"),                # USDC to spend (or use shares=)
    protocol="polymarket",
)
Intent.prediction_sell(
    market_id="will-bitcoin-exceed-100000",
    outcome="YES",
    shares=Decimal("50"),                     # Shares to sell (or "all")
    protocol="polymarket",
)
Intent.prediction_redeem(
    market_id="will-bitcoin-exceed-100000",   # Redeem after market resolves
    protocol="polymarket",
)

Cross-Chain

Intent.ensure_balance - Meta-intent that resolves to a BridgeIntent (if balance is insufficient) or HoldIntent (if already met). Call .resolve(market) before returning from decide().

intent = Intent.ensure_balance(
    token="USDC",
    min_amount=Decimal("1000"),
    target_chain="arbitrum",
    max_slippage=Decimal("0.005"),
    preferred_bridge=None,
)
# Must resolve before returning - returns BridgeIntent or HoldIntent
resolved = intent.resolve(market)
return resolved

Token Utilities

Intent.wrap (WrapNative) - Wrap native tokens to ERC-20 (ETH -> WETH, MATIC -> WMATIC, etc.)

Intent.wrap(
    token="WETH",              # Wrapped token symbol to receive
    amount=Decimal("0.5"),     # Amount of native token to wrap (or "all")
    chain="arbitrum",          # Target chain
)

Intent.unwrap (UnwrapNative) - Unwrap wrapped native tokens (WETH -> ETH, WMATIC -> MATIC, etc.)

Intent.unwrap(
    token="WETH",              # Wrapped token symbol
    amount=Decimal("0.5"),     # Amount to unwrap (or "all")
    chain="arbitrum",          # Target chain
)

Control Flow

Intent.hold - Do nothing this iteration

Intent.hold(reason="RSI in neutral zone")

Intent.sequence - Execute multiple intents in order

Intent.sequence(
    intents=[
        Intent.swap(from_token="USDC", to_token="WETH", amount_usd=Decimal("1000")),
        Intent.supply(protocol="aave_v3", token="WETH", amount=Decimal("0.5")),
    ],
    description="Buy WETH then supply to Aave",
)

Chained Amounts

Use "all" to reference the full output of a prior intent:

Intent.sequence(intents=[
    Intent.swap(from_token="USDC", to_token="WETH", amount_usd=Decimal("1000")),
    Intent.supply(protocol="aave_v3", token="WETH", amount="all"),  # Uses swap output
])

Market Data API

The MarketSnapshot passed to decide() provides these methods:

Prices

price = market.price("WETH")                    # Decimal, USD price
price = market.price("WETH", quote="USDC")      # Price in USDC terms

pd = market.price_data("WETH")                  # PriceData object
pd.price             # Decimal - current price
pd.price_24h_ago     # Decimal
pd.change_24h_pct    # Decimal
pd.high_24h          # Decimal
pd.low_24h           # Decimal
pd.timestamp         # datetime

Balances

bal = market.balance("USDC")
bal.balance       # Decimal - token amount
bal.balance_usd   # Decimal - USD value
bal.symbol        # str
bal.address       # str - token contract address

TokenBalance supports numeric comparisons: bal > Decimal("100").

Technical Indicators

All indicators accept token, period (int), and timeframe (str, default "4h").

rsi = market.rsi("WETH", period=14, timeframe="4h")
rsi.value          # Decimal (0-100)
rsi.is_oversold    # bool (value < 30)
rsi.is_overbought  # bool (value > 70)
rsi.signal         # "BUY" | "SELL" | "HOLD"

macd = market.macd("WETH", fast_period=12, slow_period=26, signal_period=9)
macd.macd_line     # Decimal
macd.signal_line   # Decimal
macd.histogram     # Decimal
macd.is_bullish_crossover  # bool
macd.is_bearish_crossover  # bool

bb = market.bollinger_bands("WETH", period=20, std_dev=2.0)
bb.upper_band      # Decimal
bb.middle_band     # Decimal
bb.lower_band      # Decimal
bb.bandwidth        # Decimal
bb.percent_b        # Decimal (0.0 = at lower band, 1.0 = at upper band)
bb.is_squeeze       # bool

stoch = market.stochastic("WETH", k_period=14, d_period=3)
stoch.k_value       # Decimal
stoch.d_value       # Decimal
stoch.is_oversold   # bool
stoch.is_overbought # bool

atr_val = market.atr("WETH", period=14)
atr_val.value       # Decimal (absolute)
atr_val.value_percent  # Decimal, percentage points (2.62 means 2.62%, not 0.0262)
atr_val.is_high_volatility  # bool

sma = market.sma("WETH", period=20)
ema = market.ema("WETH", period=12)
# Both return MAData with: .value, .is_price_above, .is_price_below, .signal

adx = market.adx("WETH", period=14)
adx.value           # Decimal
adx.plus_di         # Decimal
adx.minus_di        # Decimal
adx.is_trending     # bool
adx.is_uptrend      # bool

obv = market.obv("WETH", signal_period=21)
obv.value           # Decimal
obv.signal          # Decimal
obv.is_bullish      # bool

cci = market.cci("WETH", period=20)
cci.value           # Decimal
cci.is_overbought   # bool
cci.is_oversold     # bool

ich = market.ichimoku("WETH", tenkan_period=9, kijun_period=26, senkou_b_period=52)
ich.tenkan_sen      # Decimal (conversion line)
ich.kijun_sen       # Decimal (base line)
ich.senkou_span_a   # Decimal (leading span A)
ich.senkou_span_b   # Decimal (leading span B)
ich.is_bullish_crossover  # bool
ich.is_above_cloud  # bool

Multi-Token Queries

# Per-token reads work today on every deployment surface.
weth_price = market.price("WETH")                   # Decimal
wbtc_price = market.price("WBTC")                   # Decimal
usdc_bal = market.balance("USDC")                   # TokenBalance
weth_bal = market.balance("WETH")                   # TokenBalance
usd_val = market.balance_usd("WETH")                # Decimal - USD value of holdings
total = market.total_portfolio_usd()                # Decimal

Batch helpers are Phase 2. The deprecated data-layer class exposes market.prices([...]) / market.balances([...]) batch fetchers. The canonical strategy-facing class deliberately does NOT lift these names in the ALM-2696 fix because legacy callers (runner_state.py, trust tests) historically used hasattr(market, "prices") / market.prices.get(...) patterns whose absence was load-bearing. Phase 2 (VIB-4065 / GH#2126) migrates those callers in lockstep before lifting these batch names. Use the per-token form above until then.

# USD value of an arbitrary collateral amount (for perp position sizing)
col_usd = market.collateral_value_usd("WETH", Decimal("2"))  # Decimal - amount * price

OHLCV Data

df = market.ohlcv("WETH", timeframe="1h", limit=100)  # pd.DataFrame
# Columns: open, high, low, close, volume

Pool and DEX Data

pool = market.pool_price("0x...")                   # DataEnvelope[PoolPrice]
pool = market.pool_price_by_pair("WETH", "USDC")   # DataEnvelope[PoolPrice]
reserves = market.pool_reserves("0x...")            # PoolReserves
history = market.pool_history("0x...", resolution="1h")  # DataEnvelope[list[PoolSnapshot]]
analytics = market.pool_analytics("0x...")          # DataEnvelope[PoolAnalytics]
best = market.best_pool("WETH", "USDC", metric="fee_apr")  # DataEnvelope[PoolAnalyticsResult]

Provider availability: pool_*, twap / lwap, liquidity_depth, estimate_slippage, pool_analytics / best_pool, il_exposure / projected_il, realized_vol / vol_cone, portfolio_risk / rolling_sharpe, yield_opportunities, lst_*, prediction-market methods, and the rate-history methods are all provider-driven. The runner wires the corresponding provider (pool reader registry, price aggregator, IL calculator, …); when a provider is not wired the method raises ValueError("No <X> configured for MarketSnapshot") rather than returning silently. Do not guard these calls with hasattr(market, ...) — the methods always exist; catch ValueError (or one of the typed *UnavailableError subclasses defined in almanak.framework.data.market_snapshot) if you need to degrade gracefully.

Carve-out — prediction_price(): unlike the other prediction-market methods (prediction(), prediction_positions(), prediction_orders(), all of which raise ValueError when no provider is wired), prediction_price() returns None as a soft-signal fallback. Strategies that use it as a side-channel signal can therefore branch on if (p := market.prediction_price(...)) is not None: instead of wrapping the call in try / except ValueError. This matches the existing convention preserved by ALM-2696 and is pinned by the regression suite.

Price Aggregation and Slippage

twap = market.twap("WETH/USDC", window_seconds=300)       # DataEnvelope[AggregatedPrice]
# Explicit-pool form: when you pass `pool_address` directly, you must also
# pass token decimals (or have a `pool_reader_registry` wired so the snapshot
# can resolve them automatically). There is no "WETH/USDC default" — the
# decimals are required for the tick-to-price conversion.
twap = market.twap(
    "WBTC/WETH",
    pool_address="0x...",
    token0_decimals=8, token1_decimals=18,
)
lwap = market.lwap("WETH/USDC")                           # DataEnvelope[AggregatedPrice]
depth = market.liquidity_depth("0x...")                    # DataEnvelope[LiquidityDepth]
slip = market.estimate_slippage("WETH", "USDC", Decimal("10000"))  # DataEnvelope[SlippageEstimate]
prices = market.price_across_dexs("WETH", "USDC", Decimal("1"))   # list[DexQuote]
best_dex = market.best_dex_price("WETH", "USDC", Decimal("1"))    # BestDexResult

Explicit-pool decimals contract (twap): any call that supplies pool_address directly must either pass token0_decimals / token1_decimals explicitly OR have a pool_reader_registry wired on the snapshot so the decimals can be resolved from pool metadata. There is no "WETH/USDC fallback" — the tick-to-price conversion needs the real decimals. Without either path, the call raises ValueError rather than returning a price that can be off by powers of ten for pools like WBTC/WETH (8/18) or USDC/USDT (6/6). lwap does not accept pool_address and is unaffected (it scans pools internally via the registry).

Lending and Funding Rates

rate = market.lending_rate("aave_v3", "USDC", side="supply")   # LendingRate
best = market.best_lending_rate("USDC", side="supply")         # BestRateResult
fr = market.funding_rate("binance", "ETH-PERP")               # FundingRate
spread = market.funding_rate_spread("ETH-PERP", "binance", "hyperliquid")  # FundingRateSpread

Impermanent Loss

il = market.il_exposure("position_id", fees_earned=Decimal("50"))  # ILExposure
proj = market.projected_il("WETH", "USDC", price_change_pct=Decimal("0.1"))  # ProjectedILResult

Prediction Markets

mkt = market.prediction("market_id")                    # PredictionMarket
price = market.prediction_price("market_id", "YES")     # Decimal
positions = market.prediction_positions("market_id")     # list[PredictionPosition]
orders = market.prediction_orders("market_id")           # list[PredictionOrder]

Rate History (Backtesting)

hist = market.lending_rate_history("aave_v3", "USDC", days=90)  # DataEnvelope[list[LendingRateSnapshot]]
for snap in hist.value:
    print(f"Supply: {snap.supply_apy}%, Borrow: {snap.borrow_apy}%")

fh = market.funding_rate_history("binance", "ETH-PERP", hours=168)  # DataEnvelope[list[FundingRateSnapshot]]

Position Health

ph = market.position_health("morpho_blue", market_id="0x...")  # PositionHealth
ph.health_factor     # Decimal
ph.ltv               # Decimal

pt = market.pt_position_health("0x...", pendle_market_address="0x...")  # PTPositionHealth

LST Exchange Rates (Solana)

rate = market.lst_exchange_rate("jitoSOL")   # LSTExchangeRate
rate.rate            # Decimal - rate vs SOL
rate.apy             # Decimal

all_rates = market.lst_all_rates()           # dict[str, LSTExchangeRate]

Risk Metrics

vol = market.realized_vol("WETH", window_days=30)    # RealizedVol
cone = market.vol_cone("WETH")                       # VolCone
# portfolio_risk / rolling_sharpe consume a periodic PnL return series
# (each element is a fractional period return — e.g. 0.01 = 1% gain).
risk = market.portfolio_risk(pnl_series)                          # PortfolioRisk
sharpe = market.rolling_sharpe(pnl_series, window_days=30)        # RollingSharpe

Yield and Analytics

yields = market.yield_opportunities("USDC", min_tvl=100_000, sort_by="apy")  # DataEnvelope[list[YieldOpportunity]]
gas = market.gas_price()                                # GasPrice
health = market.health()                                # HealthReport
signals = market.wallet_activity(action_types=["SWAP", "LP_OPEN"])  # list

Context Properties

market.chain            # str - current chain name
market.wallet_address   # str - wallet address
market.timestamp        # datetime - snapshot timestamp
market.fork_rpc_url     # str | None - Local Anvil fork RPC URL (paper trading only; bypasses the gateway and is None in production)
market.fork_block       # int | None - current fork block number (paper trading only)

Critical Data Failure Tracking

The runner uses these methods to detect when a strategy returns HOLD while market-data lookups were failing (e.g. price oracle timeouts, unknown tokens), and escalates those cycles into IterationStatus.DATA_ERROR so the consecutive-error circuit breaker fires correctly.

market.has_critical_data_failures()          # bool - True if any data lookup failed this cycle
market.critical_data_failure_count()         # int - number of tracked failures
market.classify_critical_data_failures()     # str - "transient", "permanent", "mixed", or "none"
market.summarize_critical_data_failures()    # str - human-readable summary (for logs)
market.clear_critical_data_failures()        # None - reset all failures (called by runner after pre-warm)

State Management

The framework automatically persists runner-level metadata (iteration counts, error counters, multi-step execution progress) after each iteration. However, strategy-specific state -- position IDs, trade counts, phase tracking, cooldown timers -- is only persisted if you implement two hooks: get_persistent_state() and load_persistent_state().

Without these hooks, all instance variables are lost on restart. This is especially dangerous for LP and lending strategies where losing a position ID means the strategy cannot close its own positions.

Required for any stateful strategy:

def __init__(self, **kwargs):
    super().__init__(**kwargs)
    self._position_id: int | None = None
    self._phase: str = "idle"
    self._entry_price: Decimal = Decimal("0")

def get_persistent_state(self) -> dict:
    """Called by framework after each iteration to serialize state for persistence."""
    return {
        "position_id": self._position_id,
        "phase": self._phase,
        "entry_price": str(self._entry_price),  # Decimal -> str for JSON
    }

def load_persistent_state(self, saved: dict) -> None:
    """Called by framework on startup to restore state from previous run."""
    self._position_id = saved.get("position_id")
    self._phase = saved.get("phase", "idle")
    self._entry_price = Decimal(saved.get("entry_price", "0"))

Guidelines:

• Use defensive .get() with defaults in load_persistent_state() so older saved state doesn't crash when you add new fields.
• Store Decimal values as strings (str(amount)) and parse back (Decimal(state["amount"])) for safe JSON round-tripping. All values must be JSON-serializable.
• The on_intent_executed() callback is the natural place to update state after a trade (e.g., storing a new position ID), and get_persistent_state() then picks it up for saving.

Use --fresh to clear saved state when starting over: almanak strat run --fresh --once.

on_intent_executed Callback

After execution, access results (position IDs, swap amounts) via the callback. The framework automatically enriches result with protocol-specific data - no manual receipt parsing needed.

# In your strategy file, import logging at the top:
# import logging
# logger = logging.getLogger(__name__)

def on_intent_executed(self, intent, success: bool, result):

    if not success:
        logger.warning(f"Intent failed: {intent.intent_type}")
        return

    # Capture LP position ID (enriched automatically by ResultEnricher)
    # Store in instance variables -- persisted via get_persistent_state()
    if result.position_id is not None:
        self._lp_position_id = result.position_id
        logger.info(f"Opened LP position {result.position_id}")

        # Store range bounds for rebalancing strategies (keep as Decimal)
        if (
            hasattr(intent, "range_lower") and intent.range_lower is not None
            and hasattr(intent, "range_upper") and intent.range_upper is not None
        ):
            self._range_lower = intent.range_lower
            self._range_upper = intent.range_upper

    # Capture swap amounts
    if result.swap_amounts:
        self._last_swap = {
            "amount_in": str(result.swap_amounts.amount_in),
            "amount_out": str(result.swap_amounts.amount_out),
        }
        logger.info(
            f"Swapped {result.swap_amounts.amount_in} -> {result.swap_amounts.amount_out}"
        )

Configuration

config.json

Contains the target chain and tunable runtime parameters. name, description, and supported_chains still live in the @almanak_strategy decorator on your strategy class; the config.json chain field acts as an explicit override of the decorator's default_chain and lets tooling (sdk-planner, operators, deployment UIs) read the target chain without importing the strategy module.

Single-chain:

{
    "chain": "arbitrum",
    "base_token": "WETH",
    "quote_token": "USDC",
    "rsi_period": 14,
    "rsi_oversold": 30,
    "rsi_overbought": 70,
    "trade_size_usd": 1000,
    "max_slippage_bps": 50,
    "anvil_funding": {
        "USDC": "10000",
        "WETH": "5"
    }
}

Multi-chain:

{
    "chains": ["base", "arbitrum"],
    "swap_amount_usdc": "100",
    "max_slippage_bps": 100,
    "anvil_funding": {
        "USDC": 500
    }
}

The chains field lists the chains the strategy operates on and is read by the platform at deployment time. It should match supported_chains from the @almanak_strategy decorator. For single-chain strategies, chain (singular) is also accepted. anvil_funding is flat -- the same tokens are funded on all chains. All other fields are strategy-specific and accessed via self.config.get(key, default).

.env (local development only)

Security note: The .env file is for local development and Anvil fork testing only. In production, secrets are managed by the platform and injected into the gateway sidecar - they never reach the strategy container. See Security Model.

# Required for local development
ALMANAK_PRIVATE_KEY=<your-private-key>

# RPC access (set at least one)
ALCHEMY_API_KEY=<your-alchemy-key>
# RPC_URL=https://...

# Optional
# ENSO_API_KEY=<key>
# COINGECKO_API_KEY=<key>
# ALMANAK_API_KEY=<key>

token_funding (recommended, will be required)

Structured list declaring exactly which tokens the strategy needs to be funded before the first tick. Each entry specifies the token symbol, on-chain address, amount, and how to interpret the amount. strat new generates this automatically when the template includes token fields.

"token_funding": [
    {"symbol": "WETH", "address": "0x82aF49447D8a07e3bd95BD0d56f35241523fBab1", "chain": "arbitrum", "amount": "1", "amount_type": "token"},
    {"symbol": "USDC", "address": "0xaf88d065e77c8cC2239327C5EDb3A432268e5831", "amount": "5000", "amount_type": "usd"}
]

Field	Required	Description
symbol	yes	Token symbol (e.g. "WETH")
address	yes	ERC-20 contract address
chain	no	Defaults to strategy chain
amount	yes	Quantity (string to preserve precision)
amount_type	yes	"token" (native units), "usd" (dollar value), or "percentage" (of held balance)

anvil_funding

When running on Anvil (--network anvil), the framework auto-funds the wallet with tokens specified in anvil_funding. Values are in token units (not USD).

Token Resolution

Use get_token_resolver() for all token lookups. Never hardcode addresses.

from almanak.framework.data.tokens import get_token_resolver

resolver = get_token_resolver()

# Resolve by symbol
token = resolver.resolve("USDC", "arbitrum")
# -> ResolvedToken(symbol="USDC", address="0xaf88...", decimals=6, chain="arbitrum")

# Resolve by address
token = resolver.resolve("0xaf88d065e77c8cC2239327C5EDb3A432268e5831", "arbitrum")

# Convenience
decimals = resolver.get_decimals("arbitrum", "USDC")  # -> 6
address = resolver.get_address("arbitrum", "USDC")     # -> "0xaf88..."

# For DEX swaps (auto-wraps native tokens: ETH->WETH, MATIC->WMATIC)
token = resolver.resolve_for_swap("ETH", "arbitrum")   # -> WETH

# Resolve trading pair
usdc, weth = resolver.resolve_pair("USDC", "WETH", "arbitrum")

Resolution order: memory cache -> disk cache -> static registry -> gateway on-chain lookup.

Never default to 18 decimals. If the token is unknown, TokenNotFoundError is raised.

Backtesting

PnL Backtest (historical prices, no on-chain execution)

almanak strat backtest pnl -s my_strategy \
    --start 2024-01-01 --end 2024-06-01 \
    --initial-capital 10000

Paper Trading (Anvil fork with real execution, PnL tracking)

almanak strat backtest paper -s my_strategy \
    --duration 3600 --interval 60 \
    --initial-capital 10000

Paper trading runs the full strategy loop on an Anvil fork with real transaction execution, equity curve tracking, and JSON result logs.

Parameter Sweep

almanak strat backtest sweep -s my_strategy \
    --start 2024-01-01 --end 2024-06-01 \
    --param "rsi_oversold:20,25,30" \
    --param "rsi_overbought:70,75,80"

Runs the PnL backtest across all parameter combinations and ranks by Sharpe ratio.

Programmatic Backtesting

from almanak.framework.backtesting import BacktestEngine

engine = BacktestEngine(
    strategy_class=MyStrategy,
    config={...},
    start_date="2024-01-01",
    end_date="2024-06-01",
    initial_capital=10000,
)
results = engine.run()
results.sharpe_ratio
results.max_drawdown
results.total_return
results.plot()  # Matplotlib equity curve

Backtesting Limitations

• OHLCV data: The PnL backtester uses historical close prices from CoinGecko. Indicators that require OHLCV data (ATR, Stochastic, Ichimoku) need a paid CoinGecko tier or an external data source.
• RPC for paper trading: Paper trading requires an RPC endpoint. Alchemy free tier is recommended for performance; public RPCs work but are slow.
• No CWD auto-discovery: Backtest CLI commands (backtest pnl, backtest paper, backtest sweep) require an explicit -s strategy_name flag. They do not auto-discover strategies from the current directory like strat run does.
• Percentage fields: total_return_pct and annualized_return_pct are actual percentages (33 = 33%) after VIB-2915. Other _pct fields like max_drawdown_pct and win_rate are still decimal fractions (0.33 = 33%).

CLI Commands

Strategy Management

almanak strat new                     # Interactive scaffolding (creates pyproject.toml, .venv/, uv.lock)
almanak strat new -t mean_reversion -n my_rsi -c arbitrum  # Non-interactive
almanak strat demo                    # Browse and copy a working demo strategy

Templates: blank, dynamic_lp, mean_reversion, bollinger, basis_trade, lending_loop, copy_trader

Each scaffolded strategy is a self-contained Python project. After scaffolding, uv sync runs automatically to create .venv/ and uv.lock. Add dependencies with uv add <package>.

Running Strategies

almanak strat run --once              # Single iteration (from strategy dir)
almanak strat run -d path/to/strat --once  # Explicit directory
almanak strat run --network anvil --once   # Local Anvil fork
almanak strat run --interval 30       # Continuous (30s between iterations)
almanak strat run --dry-run --once    # No transactions submitted
almanak strat run --fresh --once      # Clear state before running
almanak strat run --id abc123 --once  # Resume previous run
almanak strat run --dashboard         # Launch live monitoring dashboard

Backtesting

almanak strat backtest pnl -s my_strategy            # Historical PnL simulation
almanak strat backtest paper -s my_strategy            # Paper trading on Anvil fork
almanak strat backtest sweep -s my_strategy           # Parameter sweep optimization

Teardown

almanak strat teardown plan           # Preview teardown intents
almanak strat teardown execute        # Execute teardown

Permissions

almanak strat permissions                          # Zodiac Roles Target[] format (default)
almanak strat permissions -o permissions.json      # Write to file
almanak strat permissions -d path/to/strat          # Explicit directory
almanak strat permissions --chain base              # Override chain

Generates a JSON manifest of minimum-privilege contract permissions needed for Safe wallet deployments with Zodiac Roles. Reads supported_protocols and intent_types from @almanak_strategy metadata and compiles synthetic intents to discover required contract addresses and function selectors. Non-EVM chains are automatically skipped. The default output format is Zodiac Roles Target[].

Gateway

almanak gateway                       # Start standalone gateway
almanak gateway --network anvil       # Gateway for local Anvil testing
almanak gateway --port 50052          # Custom port

Agent Skill Management

almanak agent install                 # Auto-detect platforms and install
almanak agent install -p claude       # Install for specific platform
almanak agent install -p all          # Install for all 10 platforms
almanak agent update                  # Update installed skill files
almanak agent status                  # Check installation status

Strategy Operations

almanak strat list                    # List deployed strategies
almanak strat status                  # Show strategy status
almanak strat logs                    # View strategy logs
almanak strat pause                   # Pause a running strategy
almanak strat resume                  # Resume a paused strategy

Copy Trading

almanak copy validate                 # Validate a copy trading config
almanak copy replay                   # Replay copy trades
almanak copy report                   # Generate copy trading report

Services & Tools

almanak ax                            # Almanak agentic execution
almanak backtest-service              # Start backtest service
almanak dashboard                     # Launch strategy dashboard
almanak mcp serve                     # Start MCP server
almanak info matrix                   # Show chain/protocol support matrix

Documentation

almanak docs path                     # Path to bundled LLM docs
almanak docs dump                     # Print full LLM docs
almanak docs agent-skill              # Path to bundled agent skill
almanak docs agent-skill --dump       # Print agent skill content

Zodiac Permissions

Every strategy deployed on a Safe wallet uses Zodiac Roles to enforce minimum-privilege access. The permissions system automatically discovers which contracts and function selectors the strategy needs by compiling synthetic intents.

When to Generate

Regenerate permissions whenever you:

• Create a new strategy
• Add or remove protocols in @almanak_strategy(supported_protocols=[...])
• Add or remove intent types in @almanak_strategy(intent_types=[...])
• Change tokens in config.json (base_token, quote_token, collateral_token, etc.)
• Add or remove chains in @almanak_strategy(supported_chains=[...])

How It Works

1. Reads supported_protocols and intent_types from the @almanak_strategy() decorator
2. Auto-expands teardown complements (e.g. SUPPLY adds WITHDRAW) so teardown permissions are always included
3. Creates synthetic intents for each (protocol, intent_type) pair
4. Compiles them through the real IntentCompiler to extract target contracts and selectors
5. Adds ERC-20 approve permissions for tokens found in config.json
6. Adds infrastructure permissions (MultiSend for atomic execution)
7. Merges, deduplicates, and outputs as Zodiac Roles Target[] format

Usage

# Generate Zodiac permissions and write to file (recommended)
almanak strat permissions -o permissions.json

# Preview on stdout
almanak strat permissions

# Single chain override
almanak strat permissions --chain arbitrum -o permissions.json

Output Format

The Zodiac Roles Target[] format is a JSON array ready for Safe wallet configuration:

[
  {
    "address": "0x68b3465833fb72A70ecDF485E0e4C7bD8665Fc45",
    "clearance": 2,
    "executionOptions": 0,
    "functions": [
      { "selector": "0x04e45aaf", "wildcarded": true }
    ]
  }
]

• clearance: 2 = function-level (specific selectors), 1 = target-level (all functions)
• executionOptions: 0 = None, 1 = Send, 2 = DelegateCall, 3 = Both
• wildcarded: true means the selector applies regardless of input arguments

Strategy Decorator Requirements

For permissions to generate correctly, ensure your @almanak_strategy decorator declares all protocols and intent types:

@almanak_strategy(
    name="my_strategy",
    default_chain="arbitrum",
    supported_chains=["arbitrum", "base"],
    supported_protocols=["uniswap_v3", "aave_v3"],
    intent_types=["SWAP", "SUPPLY", "WITHDRAW", "BORROW", "REPAY"],
)
class MyStrategy(IntentStrategy):
    ...

Supported Chains and Protocols

Chains

Chain	Enum Value	Config Name
Ethereum	ETHEREUM	ethereum
Arbitrum	ARBITRUM	arbitrum
Optimism	OPTIMISM	optimism
Base	BASE	base
Avalanche	AVALANCHE	avalanche
Polygon	POLYGON	polygon
BSC	BSC	bsc
Sonic	SONIC	sonic
Plasma	PLASMA	plasma
Blast	BLAST	blast
Linea	LINEA	linea
Mantle	MANTLE	mantle
Berachain	BERACHAIN	berachain
Monad	MONAD	monad
X-Layer	XLAYER	xlayer
0G Chain	ZEROG	zerog
Solana	SOLANA	solana

Protocols

Protocol	Enum Value	Type	Config Name
Uniswap V3	UNISWAP_V3	DEX / LP	uniswap_v3
Uniswap V4	UNISWAP_V4	DEX / LP	uniswap_v4
PancakeSwap V3	PANCAKESWAP_V3	DEX / LP	pancakeswap_v3
SushiSwap V3	SUSHISWAP_V3	DEX / LP	sushiswap_v3
TraderJoe V2	TRADERJOE_V2	DEX / LP	traderjoe_v2
Aerodrome	AERODROME	DEX / LP	aerodrome
Agni Finance	AGNI_FINANCE	DEX / LP	agni_finance
Enso	ENSO	Aggregator	enso
Pendle	PENDLE	Yield	pendle
MetaMorpho	METAMORPHO	Lending	metamorpho
Radiant V2	RADIANT_V2	Lending	radiant_v2
LiFi	LIFI	Bridge	lifi
BenQi	BENQI	Lending	benqi
Joe Lend (DORMANT)	JOE_LEND	Lending — wound down on-chain (VIB-3960); compiler short-circuits. Do NOT use.	joelend
Silo V2	SILO_V2	Lending	silo_v2
Euler V2	EULER_V2	Lending	euler_v2
Vault	VAULT	ERC-4626	vault
Curve	CURVE	DEX / LP	curve
Balancer	BALANCER	DEX / LP	balancer
Aave V3	*	Lending	aave_v3
Morpho Blue	*	Lending	morpho_blue
Compound V3	*	Lending	compound_v3
GMX V2	*	Perps	gmx_v2
Hyperliquid	*	Perps	hyperliquid
Polymarket	*	Prediction	polymarket
Kraken	*	CEX	kraken
Lido	*	Staking	lido
Lagoon	*	Vault	lagoon

* These protocols do not have a Protocol enum value. Use the string config name (e.g., protocol="aave_v3") in intents. They are resolved by the intent compiler and transaction builder directly.

Networks

Network	Enum Value	Description
Mainnet	MAINNET	Production chains
Anvil	ANVIL	Local fork for testing
Sepolia	SEPOLIA	Testnet

Protocol-Specific Notes

GMX V2 (Perpetuals)

• Market format: Use slash separator: "BTC/USD", "ETH/USD", "LINK/USD" (not dash).
• Two-step execution: GMX V2 uses a keeper-based execution model. When you call Intent.perp_open(), the SDK submits an order creation transaction. A GMX keeper then executes the actual position change in a separate transaction. on_intent_executed(success=True) fires when the order creation TX confirms, not when the keeper executes the position. Strategies should poll position state before relying on it.
• Minimum position size: GMX V2 enforces a minimum position size of approximately $11 net of fees. Orders below this threshold are silently rejected by the keeper with no on-chain error.
• Collateral approvals: Handled automatically by the intent compiler (same as LP opens).
• Position monitoring: get_all_positions() may not return positions immediately after opening due to keeper delay. Allow a few seconds before querying.
• Supported chains: Arbitrum, Avalanche.
• Collateral tokens: USDC, USDT (chain-dependent).

Common Patterns

RSI Mean Reversion (Trading)

def decide(self, market):
    rsi = market.rsi(self.base_token, period=self.rsi_period)
    quote_bal = market.balance(self.quote_token)
    base_bal = market.balance(self.base_token)

    if rsi.is_oversold and quote_bal.balance_usd >= self.trade_size:
        return Intent.swap(
            from_token=self.quote_token, to_token=self.base_token,
            amount_usd=self.trade_size, max_slippage=Decimal("0.005"),
        )
    if rsi.is_overbought and base_bal.balance_usd >= self.trade_size:
        return Intent.swap(
            from_token=self.base_token, to_token=self.quote_token,
            amount_usd=self.trade_size, max_slippage=Decimal("0.005"),
        )
    return Intent.hold(reason=f"RSI={rsi.value:.1f} in neutral zone")

LP Rebalancing

def decide(self, market):
    price = market.price(self.base_token)
    position_id = self._lp_position_id

    if position_id:
        # Check if price is out of range - close and reopen
        if price < self._range_lower or price > self._range_upper:
            return Intent.lp_close(position_id=position_id, protocol="uniswap_v3")

    # Open new position centered on current price
    atr = market.atr(self.base_token)
    half_range = price * (atr.value_percent / Decimal("100")) * 2  # value_percent is percentage points
    return Intent.lp_open(
        pool="WETH/USDC",
        amount0=Decimal("1"), amount1=Decimal("2000"),
        range_lower=price - half_range,
        range_upper=price + half_range,
    )

Multi-Step with IntentSequence

def decide(self, market):
    return Intent.sequence(
        intents=[
            Intent.swap(from_token="USDC", to_token="WETH", amount_usd=Decimal("5000")),
            Intent.supply(protocol="aave_v3", token="WETH", amount="all"),
            Intent.borrow(
                protocol="aave_v3",
                collateral_token="WETH", collateral_amount=Decimal("0"),
                borrow_token="USDC", borrow_amount=Decimal("3000"),
            ),
        ],
        description="Leverage loop: buy WETH, supply, borrow USDC",
    )

Multi-Chain Strategies

Strategies can operate across multiple chains with per-chain wallet addresses. The primary chain is supported_chains[0]. Intents without an explicit chain= parameter run on the primary chain.

Decorator:

@almanak_strategy(
    name="cross_chain_arb",
    supported_chains=["base", "arbitrum"],       # base is primary (first in list)
    supported_protocols=["uniswap_v3", "across"],
    intent_types=["SWAP", "BRIDGE", "HOLD"],
)
class CrossChainArbStrategy(IntentStrategy):
    ...

config.json:

{
    "chains": ["base", "arbitrum"],
    "swap_amount_usdc": "100",
    "anvil_funding": {
        "USDC": 500
    }
}

Note: anvil_funding is flat (not per-chain) -- the same tokens are funded on all chains.

Strategy properties:

self.chain                          # "base" (primary chain = supported_chains[0])
self.chains                         # ["base", "arbitrum"]
self.wallet_address                 # default wallet
self.get_wallet_for_chain("arbitrum")  # per-chain wallet (if wallet registry configured)

When a gateway wallet registry is configured (ALMANAK_GATEWAY_WALLETS), each chain can use a different Safe wallet. The framework resolves destination wallets automatically for bridge intents.

decide() with cross-chain intents:

def decide(self, market: MarketSnapshot):
    return Intent.sequence([
        # Bridge USDC from Base to Arbitrum
        Intent.bridge(
            token="USDC",
            amount=Decimal("100"),
            from_chain="base",
            to_chain="arbitrum",
            preferred_bridge="across",
            max_slippage=Decimal("0.01"),
        ),
        # Swap on Arbitrum (explicit chain= required for non-primary chain)
        Intent.swap(
            from_token="USDC",
            to_token="WETH",
            amount=Decimal("50"),
            protocol="uniswap_v3",
            chain="arbitrum",
        ),
        # Bridge back to primary chain
        Intent.bridge(
            token="USDC",
            amount=Decimal("50"),
            from_chain="arbitrum",
            to_chain="base",
            preferred_bridge="across",
        ),
    ], description="Arb USDC across chains")

Multi-chain market data:

For multi-chain strategies, market is a MultiChainMarketSnapshot with chain-aware queries:

def decide(self, market):
    # Chain-specific prices and balances
    arb_price = market.price("WETH", chain="arbitrum")
    base_price = market.price("WETH", chain="base")
    usdc_on_base = market.balance("USDC", chain="base")

    # Chain health monitoring
    market.healthy_chains       # ["base", "arbitrum"]
    market.stale_chains         # [] (empty if all healthy)
    market.all_chains_healthy   # True

Key rules:

• Intents on the primary chain can omit chain= -- it's implicit
• Intents on non-primary chains must include chain="arbitrum" etc.
• Bridge intents always require explicit from_chain and to_chain
• Use Intent.sequence() to order cross-chain operations
• amount="all" chaining does not work after bridge intents (bridge receipt parsers don't extract output amounts) -- use explicit amounts instead

Alerting

from almanak.framework.alerting import AlertManager

class MyStrategy(IntentStrategy):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.alerts = AlertManager.from_config(self.config.get("alerting", {}))

    def decide(self, market):
        rsi = market.rsi("WETH")
        if rsi.value < 20:
            self.alerts.send("Extreme oversold: RSI={:.1f}".format(rsi.value), level="warning")
        # ... trading logic

Safe Teardown

All IntentStrategy subclasses must implement two abstract teardown methods: get_open_positions() and generate_teardown_intents(). Without these, the strategy class cannot be instantiated.

For strategies that never hold positions, extend StatelessStrategy instead of IntentStrategy — it provides empty default implementations.

get_open_positions()

Returns a TeardownPositionSummary describing all current positions. Must query on-chain state (not cached) for safety:

def get_open_positions(self):
    from datetime import UTC, datetime
    from almanak.framework.teardown import PositionInfo, PositionType, TeardownPositionSummary

    positions = []
    try:
        market = self.create_market_snapshot()
        base_bal = market.balance(self.base_token)
        if base_bal.balance > 0:
            positions.append(
                PositionInfo(
                    position_type=PositionType.TOKEN,
                    position_id=f"{self.base_token}-holding",
                    chain=self.chain,
                    protocol="uniswap_v3",
                    value_usd=base_bal.balance_usd,
                    details={"asset": self.base_token, "amount": str(base_bal.balance)},
                )
            )
    except Exception:
        logger.warning("Unable to fetch balances for teardown position summary")

    return TeardownPositionSummary(
        strategy_id=getattr(self, "strategy_id", "my_strategy"),
        timestamp=datetime.now(UTC),
        positions=positions,
    )

PositionType values (close in this priority order): PERP > BORROW > SUPPLY > LP > STAKE > PREDICTION > CEX > TOKEN

For strategies with no positions, return TeardownPositionSummary.empty(self.strategy_id).

generate_teardown_intents()

Returns intents to close all positions, respecting priority order and teardown mode:

def generate_teardown_intents(self, mode, market=None) -> list[Intent]:
    from almanak.framework.teardown import TeardownMode

    max_slippage = Decimal("0.03") if mode == TeardownMode.HARD else Decimal("0.01")
    intents = []
    # Close LP positions first (if any)
    position_id = self._lp_position_id
    if position_id:
        intents.append(Intent.lp_close(position_id=position_id))
    # Swap all base token back to quote
    intents.append(Intent.swap(
        from_token=self.base_token, to_token=self.quote_token,
        amount="all", max_slippage=max_slippage,
    ))
    return intents

TeardownMode.SOFT = graceful exit (minimize costs), TeardownMode.HARD = emergency (speed over cost).

Lending strategy teardown example (Aave V3)

def get_open_positions(self):
    from datetime import UTC, datetime
    from almanak.framework.teardown import PositionInfo, PositionType, TeardownPositionSummary

    positions = []
    if self._borrowed_amount > 0:
        positions.append(PositionInfo(
            position_type=PositionType.BORROW,
            position_id=f"aave-borrow-{self.borrow_token}",
            chain=self.chain, protocol="aave_v3",
            value_usd=self._borrowed_amount * self._borrow_price,
            details={"asset": self.borrow_token, "amount": str(self._borrowed_amount)},
        ))
    if self._supplied_amount > 0:
        positions.append(PositionInfo(
            position_type=PositionType.SUPPLY,
            position_id=f"aave-supply-{self.collateral_token}",
            chain=self.chain, protocol="aave_v3",
            value_usd=self._supplied_amount,
            details={"asset": self.collateral_token, "amount": str(self._supplied_amount)},
        ))
    return TeardownPositionSummary(
        strategy_id=self.strategy_id, timestamp=datetime.now(UTC), positions=positions,
    )

def generate_teardown_intents(self, mode, market=None) -> list[Intent]:
    intents = []
    if self._borrowed_amount > 0:
        intents.append(Intent.repay(
            protocol="aave_v3", token=self.borrow_token,
            amount=self._borrowed_amount, repay_full=True, chain=self.chain,
        ))
    if self._supplied_amount > 0:
        intents.append(Intent.withdraw(
            protocol="aave_v3", token=self.collateral_token,
            amount=self._supplied_amount, withdraw_all=True, chain=self.chain,
        ))
    return intents

Error Handling

Let exceptions propagate from decide(). The framework catches them and feeds them into its built-in circuit breaker, which tracks consecutive failures and stops the strategy after a threshold is reached.

def decide(self, market):
    rsi = market.rsi("WETH", period=14)
    # ... strategy logic — no try/except needed

Execution Failure Tracking (Circuit Breaker)

The framework retries each failed intent up to max_retries (default: 3) with exponential backoff. However, after all retries are exhausted the strategy continues running and will attempt the same trade on the next iteration. Without a circuit breaker, this creates an infinite loop of reverted transactions that burn gas without any hope of success.

Always track consecutive execution failures in persistent state and stop trading (or enter an extended cooldown) after a threshold is reached:

MAX_CONSECUTIVE_FAILURES = 3     # Stop after 3 rounds of failed intents
FAILURE_COOLDOWN_SECONDS = 1800  # 30-min cooldown before retrying

def __init__(self, *args, **kwargs):
    super().__init__(*args, **kwargs)
    self.consecutive_failures = 0
    self.failure_cooldown_until = 0.0

def decide(self, market):
    try:
        now = time.time()

        # Circuit breaker: skip trading while in cooldown
        if now < self.failure_cooldown_until:
            remaining = int(self.failure_cooldown_until - now)
            return Intent.hold(
                reason=f"Circuit breaker active, cooldown {remaining}s remaining"
            )

        # Circuit breaker: enter cooldown after too many failures
        if self.consecutive_failures >= MAX_CONSECUTIVE_FAILURES:
            self.failure_cooldown_until = now + FAILURE_COOLDOWN_SECONDS
            self.consecutive_failures = 0
            logger.warning(
                f"Circuit breaker tripped after {MAX_CONSECUTIVE_FAILURES} "
                f"consecutive failures, cooling down {FAILURE_COOLDOWN_SECONDS}s"
            )
            return Intent.hold(reason="Circuit breaker tripped")

        # ... normal strategy logic ...

    except Exception as e:
        logger.exception(f"Error in decide(): {e}")
        return Intent.hold(reason=f"Error: {e}")

def on_intent_executed(self, intent, success: bool, result):
    if success:
        self.consecutive_failures = 0   # Reset on success
    else:
        self.consecutive_failures += 1
        logger.warning(
            f"Intent failed ({self.consecutive_failures}/{MAX_CONSECUTIVE_FAILURES})"
        )

def get_persistent_state(self) -> dict:
    return {
        "consecutive_failures": self.consecutive_failures,
        "failure_cooldown_until": self.failure_cooldown_until,
    }

def load_persistent_state(self, state: dict) -> None:
    self.consecutive_failures = int(state.get("consecutive_failures", 0))
    self.failure_cooldown_until = float(state.get("failure_cooldown_until", 0))

Important: Only update trade-timing state (e.g. last_trade_ts) inside on_intent_executed when success=True, not when the intent is created. Setting it at creation time means a failed trade still resets the interval timer, causing the strategy to wait before retrying — or worse, to keep retrying on a fixed schedule with no failure awareness.

Handling Gas and Slippage Errors (Sadflow Hook)

Override on_sadflow_enter to react to specific error types during intent retries. This hook is called before each retry attempt and lets you modify the transaction (e.g. increase gas or slippage) or abort early:

from almanak.framework.intents.state_machine import SadflowAction

class MyStrategy(IntentStrategy):
    def on_sadflow_enter(self, error_type, attempt, context):
        # Abort immediately on insufficient funds — retrying won't help
        if error_type == "INSUFFICIENT_FUNDS":
            return SadflowAction.abort("Insufficient funds, stopping retries")

        # Increase gas limit for gas-related errors
        if error_type == "GAS_ERROR" and context.action_bundle:
            modified = self._increase_gas(context.action_bundle)
            return SadflowAction.modify(modified, reason="Increased gas limit")

        # For slippage errors ("Too little received"), abort after 1 attempt
        # since retrying with the same parameters will produce the same result
        if error_type == "SLIPPAGE" and attempt >= 1:
            return SadflowAction.abort("Slippage error persists, aborting")

        # Default: let the framework retry with backoff
        return None

Error types passed to on_sadflow_enter (from _categorize_error in state_machine.py):

• GAS_ERROR — gas estimation failed or gas limit exceeded
• INSUFFICIENT_FUNDS — wallet balance too low
• SLIPPAGE — "Too little received" or similar DEX revert
• TIMEOUT — transaction confirmation timed out
• NONCE_ERROR — nonce mismatch or conflict
• REVERT — generic transaction revert
• RATE_LIMIT — RPC or API rate limit hit
• NETWORK_ERROR — connection or network failure
• COMPILATION_PERMANENT — unsupported protocol/chain (non-retriable)
• None — unclassified error

Going Live Checklist

Before deploying to mainnet:

• Test on Anvil with --network anvil --once until decide() works correctly
• Run --dry-run --once on mainnet to verify compilation without submitting transactions
• Use amount= (token units) for swaps if amount_usd= causes reverts (see swap reference above)
• Override get_persistent_state() / load_persistent_state() if your strategy tracks positions or phase state
• Generate Zodiac permissions: almanak strat permissions -o permissions.json
• Verify token approvals for all protocols used (auto-handled for most, but verify on first run)
• Fund wallet on the correct chain with sufficient tokens plus gas (ETH/AVAX/MATIC)
• Note your instance ID after first successful iteration (needed for --id resume)
• Start with small amounts and monitor the first few iterations

Troubleshooting

Error	Cause	Fix
TokenNotFoundError	Token symbol not in registry	Use exact symbol (e.g., "WETH" not "ETH" for swaps). Check resolver.resolve("TOKEN", "chain").
Gateway not available	Gateway not running	Use almanak strat run (auto-starts gateway) or start manually with almanak gateway.
ALMANAK_PRIVATE_KEY not set	Missing .env	Set your private key in .env (see Configuration section).
Anvil not found	Foundry not installed	Install Foundry: see getfoundry.sh for instructions.
RSI data unavailable	Insufficient price history	The gateway needs time to accumulate data. Try a longer timeframe or wait.
Insufficient balance	Wallet doesn't have enough tokens	For Anvil: add anvil_funding to config.json. For mainnet: fund the wallet.
Slippage exceeded	Trade too large or pool illiquid	Increase max_slippage or reduce trade size.
Too little received (repeated reverts)	Placeholder prices used for slippage calculation, or stale price data	Ensure real price feeds are active (not placeholder). Implement on_sadflow_enter to abort on persistent slippage errors. Add a circuit breaker to stop retrying the same failing trade.
Transactions keep reverting after max retries	Strategy re-emits the same failing intent on subsequent iterations	Track consecutive_failures in persistent state and enter cooldown after a threshold. See the "Execution Failure Tracking" pattern.
Gas wasted on reverted transactions	No circuit breaker; framework retries 3x per intent, then strategy retries next iteration indefinitely	Implement on_intent_executed callback to count failures and on_sadflow_enter to abort non-recoverable errors early.
Intent compilation fails	Wrong parameter types	Ensure amounts are Decimal, not float. Use Decimal(str(value)).

Debugging Tips

• Use --verbose flag for detailed logging: almanak strat run --once --verbose
• Use --dry-run to test decide() without submitting transactions
• Use --log-file out.json for machine-readable JSON logs
• Check strategy state: self.state persists between iterations
• Paper trade first: almanak strat backtest paper -s my_strategy runs real execution on Anvil