GITNUXSOFTWARE ADVICE
Supply Chain In IndustryTop 10 Best Automated Trade Software of 2026
Ranked comparison of automated trade software for inventory and workflow automation, covering TradeGecko, Cin7 Core, TradeCloud plus key alternatives.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Option Alpha is the best fit if your team runs rule-based options screening and needs unattended order handling with guardrails, whereas TrendSpider suits when chart-driven signals must be automated and monitored before you delegate execution.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Option Alpha
Configurable pre-trade constraints apply to automated order intents before broker submission, which helps control execution mistakes during live trading.
Built for fits when teams run rule-based strategies and need unattended order handling plus guardrails..
TrendSpider
Editor pickStrategy alerts built on chart rules that keep signal logic visually inspectable during iteration.
Built for fits when chart signals need automation and monitoring before delegating execution..
Trade Ideas
Editor pickAlert-to-order automation built directly on scanner events, keeping rule triggers and execution logic in one workflow.
Built for fits when systematic traders want scanner-triggered automation with rule-based execution and simulation validation..
Comparison Table
Option Alpha
vertical specialistProvides no-code automation for options screening, strategy construction, and trade management.
Configurable pre-trade constraints apply to automated order intents before broker submission, which helps control execution mistakes during live trading.
Option Alpha is built around automated execution for systematic trading, where strategy rules produce orders and the system manages order states through placement and updates. It includes execution safeguards such as pre-trade risk checks and configurable constraints that help prevent oversized or out-of-bounds orders. The product also supports broker integration patterns that fit unattended live trading workflows, which matters for teams that need operational continuity.
A key tradeoff is that deeper automation requires disciplined configuration of strategy rules, symbol mappings, and order parameters before going live. It fits best when a team already has a defined rule-based strategy and needs reliable execution management rather than manual order entry or basic alerting. It is also a fit when broker connectivity and order state handling must be consistent across trading days.
- +Execution lifecycle management reduces manual follow-ups after order placement
- +Pre-trade risk limits help block invalid order intents before submission
- +Rule-to-order automation supports repeatable systematic workflows
- +Broker connectivity is designed for unattended live trading operations
- –Order routing and parameters need careful setup for each strategy
- –Advanced monitoring requires additional operational review of order states
- –Complex multi-leg workflows can add configuration overhead
- –Integration depth depends on the selected broker and data availability
Quant ops teams
Run live rules with managed order states
Fewer manual order corrections
Systematic traders
Apply size limits to rule orders
Controlled exposure per rule
Show 2 more scenarios
Broker integration engineers
Connect execution to a chosen broker
More reliable unattended execution
Broker connectivity supports a live workflow where order intent and lifecycle events stay consistent.
Trading managers
Standardize automation across strategies
Lower operational variability
Shared configuration patterns help keep order handling consistent across multiple automated strategies.
Best for: Fits when teams run rule-based strategies and need unattended order handling plus guardrails.
TrendSpider
specialistCombines automated technical analysis, strategy testing, alerts, and broker integrations.
Strategy alerts built on chart rules that keep signal logic visually inspectable during iteration.
TrendSpider provides strategy alerts that trigger off defined indicator conditions, and it keeps those rules tied to the chart context. The product’s workflow favors iterative tuning through visual setup and rapid signal review, which fits quantitative strategy testing routines more than discretionary-only charting. Its automation surface is strongest around signal generation and ongoing monitoring rather than full order management.
A key tradeoff is that TrendSpider does not replace an order management system or an execution management system, so order routing and risk checks need broker-side or external execution logic. It fits teams running systematic trading pilots where the main goal is to validate signals and coordinate execution using broker APIs or broker integration steps.
- +Chart-native alerts make rule changes easy to review
- +Strategy logic stays attached to chart context for fast iteration
- +Backtesting-style workflows support continuous signal validation
- +Works well for systematic trading pilots needing monitoring
- –Execution and pre-trade risk checks require external automation
- –Custom automation depends on broker connectivity paths
- –Complex multi-asset portfolio rules can take extra workflow design
- –Limited depth for order lifecycle tracking compared with OMS tools
Algorithmic traders
Automate entry alerts from indicator rules
Fewer missed setups
Quant teams
Iterate rule parameters using chart review
Faster strategy tuning
Show 2 more scenarios
Trading ops
Coordinate execution with broker automation
Cleaner handoff to execution
TrendSpider can feed decision timing while broker-side automation handles order placement steps.
Swing traders
Monitor systematic entries across symbols
More disciplined monitoring
Ongoing alerts support consistent tracking of long and short candidates based on set conditions.
Best for: Fits when chart signals need automation and monitoring before delegating execution.
Trade Ideas
specialistProvides automated stock scanning, strategy testing, and broker-connected trade execution.
Alert-to-order automation built directly on scanner events, keeping rule triggers and execution logic in one workflow.
Trade Ideas centers on rule-based trading triggered by scanner output and chart-based conditions, so the automation starts from specific market events rather than from a blank strategy canvas. The execution workflow is tied to brokerage connectivity so trades can be sent from the alert engine to live accounts after simulation validation. In practice, traders use its alert-to-order logic to automate repeatable entries, exits, and trade management rules while monitoring outcomes inside the same workflow.
A key tradeoff is that the automation model is more tightly aligned to Trade Ideas signal generation than to fully custom quantitative pipelines. Teams that need deep control over portfolio-level risk math or bespoke feature engineering can find the constraints limiting compared with custom strategy engines. Trade Ideas fits best when the main requirement is fast conversion of scanner-driven signals into automated execution rules with consistent monitoring and trade gating.
- +Scanner-driven automation reduces time between signal detection and order intent
- +Built-in simulation supports validating the same rule triggers before live routing
- +Rule configuration covers common entry and trade management patterns
- +Alert-based workflow keeps trading logic tied to concrete market events
- –Customization for non-standard quantitative feature pipelines is limited
- –Brokerage connectivity can constrain execution behaviors and order types
- –Complex multi-strategy allocation requires careful rule orchestration
- –Workflow depth favors Trade Ideas signal sources over fully external data
Independent systematic traders
Automate scanner entries with controlled exits
Repeatable execution with fewer manual steps
Quant teams on small budgets
Prototype systematic strategies quickly
Faster iteration than custom backtest stacks
Show 2 more scenarios
Brokerage-focused automation operators
Standardize execution across accounts
Consistent order behavior across accounts
Automation logic stays consistent while execution is routed through connected brokerage endpoints.
Trading desks with discretionary overlay
Gate automation under manual supervision
Controlled automation during volatile periods
Operational rules manage when automated actions are permitted while discretionary decisions can intervene.
Best for: Fits when systematic traders want scanner-triggered automation with rule-based execution and simulation validation.
MetaTrader 5
enterpriseSupports automated trading robots, custom indicators, backtesting, and broker connectivity.
MQL5 EA execution uses a fine-grained event model with trade request objects and runtime lifecycle controls inside the terminal.
MetaTrader 5 is a widely deployed automated execution environment that pairs an MQL5 strategy runtime with broker connections for live trading and simulation. It supports backtesting on historical data and paper trading workflows, which lets rule-based strategies be validated before capital deployment.
MetaTrader 5 also includes built-in technical indicator and EA tooling, plus configurable trade requests for multiple order types. Automation control is handled through EA lifecycle management and terminal-side settings that gate when and how strategies submit orders.
- +MQL5 event-driven EA model supports deterministic order logic
- +Strategy Tester runs repeatable backtests and paper trading sessions
- +Built-in trade execution supports market, limit, and stop orders
- +Terminal integrations reduce custom gateway build for many brokers
- –Strategy Tester data quality depends on the broker’s history feeds
- –Complex governance requires disciplined EA permissions and operational review
- –Cross-broker deployment can be constrained by account and symbol mapping
- –Advanced OMS behavior often requires custom code or external tooling
Best for: Fits when teams need rule-based strategy execution with MQL5 and repeatable backtests in a single terminal flow.
Alpaca
API-firstProvides trading APIs, market data, paper trading, and automated brokerage execution.
Order lifecycle event handling that lets strategies react to fills and status transitions in code.
Alpaca automates systematic trading by connecting strategy logic to broker execution through an API-first workflow. It provides order management functions for live trading, plus account and position endpoints that enable rule-based execution and ongoing reconciliation.
Alpaca’s automation surface also includes market data feeds that support building execution conditions around price and order-book signals. The overall design centers on programmatic control of order lifecycle events rather than a dashboard-only approach.
- +API-driven order lifecycle management supports automated execution control
- +Market data endpoints support building conditions from trading and order-book signals
- +Consistent account and position endpoints simplify reconciliation after fills
- +Workflow-friendly environment separation supports paper trading to validate logic
- –Advanced strategy execution requires non-trivial implementation and monitoring work
- –Automation coverage depends on broker integration limits for specific order behaviors
- –Latency-sensitive tactics require careful infrastructure and request timing discipline
- –Operational governance requires the team to implement its own change controls
Best for: Fits when engineering teams need programmatic rule-based strategy execution and execution-state reconciliation.
Interactive Brokers
enterpriseProvides APIs and brokerage infrastructure for automated trading across global markets.
Broker execution feedback model with granular order and trade state events that external rule engines can consume.
Interactive Brokers targets systematic and automated execution by pairing a broker execution environment with an API-first workflow. Trade automation can be driven through their broker API for order placement, account and position handling, and event-driven order and trade status updates.
For strategy development, paper trading supports test cycles that mirror live order handling, and monitoring is built around statement and execution records. Automation depth is strongest when custom logic runs externally and connects back for order management and execution feedback.
- +Broker-side API supports event-driven order and execution state updates
- +Paper trading can mirror live order workflows for safer strategy iteration
- +Institutional-grade market access supports many order and routing variants
- +Execution and account history provide a traceable audit trail for fills
- –Automation requires external strategy code and robust state management
- –Rule management and risk gates need careful implementation beyond basic limits
- –Market data subscription choices add operational overhead for scripts
- –Large strategy libraries can become complex without standardized deployment patterns
Best for: Fits when systematic traders need broker-integrated automation with external strategy control and detailed execution feedback.
Capitalise.ai
API-firstTurns plain-language trading rules into automated strategies connected to supported brokers.
Run-mode switching between simulated and live execution within the strategy workflow for safer operational validation.
Capitalise.ai is an automated trade software solution focused on taking rule-based trading ideas from configuration to execution with broker connectivity. The core capability is workflow-driven strategy automation that can translate conditions and sizing rules into orders through an integration layer.
It supports operational controls around running strategies and managing live versus simulated execution flows so users can validate behavior before exposure. Automation depth depends on how brokers and execution endpoints are wired into its integration surface.
- +Rule-based strategy configuration can be operationalized without building custom trading code
- +Strategy run modes help separate simulated execution from live trading
- +Broker integration layer reduces manual order handling during automated execution
- +Centralized strategy workflow design limits the number of manual steps per trade cycle
- –Advanced execution features like smart order routing may require specific broker coverage
- –Complex portfolio-level risk controls can be constrained by what the integration exposes
- –Backtesting workflow depth depends on available historical data connectors and formats
- –Rule governance needs careful configuration discipline to prevent unintended live behavior
Best for: Fits when small teams need configurable, rule-based automation with broker connectivity and clear run-mode separation.
3Commas
vertical specialistProvides automated cryptocurrency bots, portfolio tools, and exchange-connected trading rules.
3Commas bot editor uses structured strategy configuration to manage coordinated entry and exit behaviors across exchange accounts.
3Commas positions as an automated trade management layer that connects exchange accounts to rule-based trading routines without building custom execution logic. Its core capabilities include bot configuration for market entries and exits, strategy templates built around common order flows, and automation controls that govern when bots are allowed to place orders.
The product adds portfolio-style orchestration across multiple exchanges through account linking, trading parameters, and safety settings that help constrain behavior during live trading. For governance, it provides an audit trail of bot actions and a configurable automation workflow that supports discretionary override through manual order actions outside the bot loop.
- +Exchange account linking with centralized bot management across multiple venues
- +Order flow templates with configurable entry and exit logic
- +Safety controls for limiting trade behavior and reducing unintended order placement
- +Action history provides an audit trail of bot-driven decisions
- –Advanced risk customization is limited compared with dedicated order management systems
- –Rules and bot settings require careful setup to avoid conflicting triggers
- –Execution transparency is less granular than FIX or direct broker integration
- –Complex multi-strategy coordination often depends on manual intervention
Best for: Fits when traders want rule-based bot orchestration across exchanges with audit trail visibility.
MultiCharts
specialistSupports strategy development, backtesting, optimization, and automated broker execution.
Chart-linked strategy scripting drives automated order generation with consistent behavior across backtest, paper, and live.
MultiCharts runs rule-based trading strategies with chart-based development and scheduled automated execution. It supports a full workflow around backtesting, paper trading, and live trading so strategies can move from testing to execution within the same system.
The automation surface is centered on its strategy engine, broker connectivity, and its ability to generate orders from strategy signals. MultiCharts adds extensibility through built-in scripting for strategy logic and the surrounding trading automation lifecycle.
- +Single chart-centric workflow ties strategy coding, testing, and execution together
- +Strong strategy scripting controls order generation directly from signal logic
- +Backtesting and paper trading workflows support iterative strategy refinement
- +Broker connectivity enables live trading without reworking strategy logic
- –Governance controls like RBAC and audit log are not as explicit as in enterprise EMS tools
- –Automation tuning often requires careful platform configuration and event handling
- –Advanced execution behavior can depend on broker adapters and order routing specifics
- –Scaling to many strategies can increase operational overhead for monitoring
Best for: Fits when trading teams need automated rule logic from the same chart workspace across backtests and live execution.
QuantConnect
API-firstOffers cloud research, backtesting, and live algorithmic trading across multiple asset classes.
Lean engine execution lifecycle links backtesting, paper trading, and brokerage live trading using the same algorithm code model.
QuantConnect is an algorithmic trading platform built for rule-based strategy development and automation from backtest to live trading. It centers on a Lean engine workflow that supports strategy research, historical backtesting, paper trading, and broker-connected live order routing.
Its automation and integration surface includes a programmatic algorithm API, event-driven market data handling, and project-based deployments across environments. QuantConnect is distinct among automated trade software by combining a code-first research workflow with brokerage execution through a managed brokerage interface.
- +Code-first Lean engine workflow connects research, backtests, and live trading
- +Event-driven algorithm API simplifies order submission and portfolio state handling
- +Broker-connected live trading reduces custom OMS plumbing effort
- +Integrated paper trading supports pre-live validation of strategy logic
- –Lean-based development can slow teams that want low-code strategy tooling
- –Broker connectivity and execution behavior vary by supported venue and setup
- –Debugging production issues requires familiarity with logs and algorithm runtime model
- –Advanced execution controls depend on specific order and brokerage feature coverage
Best for: Fits when quantitative teams can code strategies and want an end-to-end backtest-to-live workflow.
Conclusion
After evaluating 10 supply chain in industry, Option Alpha stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right automated trade software
Automated trade software connects signal logic to execution workflows by managing order intents, order state transitions, and broker feedback so strategies can run without manual order entry. This guide covers Option Alpha, TradeGecko, Cin7 Core, TradeCloud, TrendSpider, Trade Ideas, MetaTrader 5, Alpaca, Interactive Brokers, Capitalise.ai, 3Commas, MultiCharts, and QuantConnect using the specific capabilities shown in each tool review.
The emphasis is on integration depth and operational control, including pre-trade constraints before broker submission and how execution lifecycle events feed back into strategy logic. It also compares how chart-native alert systems, scanner-triggered automation, and code-first execution models handle iteration from simulation to live trading.
Automated trade software that turns strategy rules into broker-ready order execution
Automated trade software is a system that converts rule-based strategy logic into broker-facing order instructions while tracking execution lifecycle states and applying guardrails before orders are sent. Option Alpha focuses on configurable pre-trade constraints that block invalid order intents prior to broker submission and uses execution lifecycle management to reduce manual follow-ups after order placement.
Trade Ideas supports alert-to-order automation built directly on scanner events, then ties the same rule triggers to built-in simulation so traders can validate behavior before live routing. Across these tools, the practical difference is whether automation is anchored in chart workflows, scanner workflows, or code execution models that handle fill and status transitions in the strategy runtime.
Execution governance and automation surfaces that reduce live-trading mistakes
Automated trade software matters most when it turns strategy outputs into broker-ready order intents while enforcing guardrails before broker submission. Option Alpha blocks invalid order intents with configurable pre-trade constraints, so the system can stop execution mistakes before they reach the broker.
Execution lifecycle handling also determines whether strategies can safely react to fills and status transitions in real time. Alpaca focuses on order lifecycle event handling that lets code react to fills and status changes, while Interactive Brokers provides granular broker order and trade state events that external rule engines can consume.
Pre-trade constraints before broker submission
Option Alpha applies configurable pre-trade constraints to automated order intents before broker submission. This guardrail layer is designed to reduce execution mistakes during live trading.
Signal-to-order workflow anchored to the signal surface
Trade Ideas builds alert-to-order automation directly on scanner events so rule triggers and execution logic stay in one workflow. TrendSpider keeps strategy logic visually inspectable through chart-native strategy alerts before execution.
Execution lifecycle event model for reconciliation and closed-loop logic
Alpaca provides order lifecycle event handling so strategies can react to fills and status transitions in code. Interactive Brokers adds a broker execution feedback model with granular order and trade state events that external rule engines can ingest.
Backtest, paper trading, and live trading run model consistency
MetaTrader 5 ties MQL5 EA execution to a runtime lifecycle inside the terminal and uses Strategy Tester for repeatable backtests and paper trading sessions. QuantConnect connects the Lean execution lifecycle across backtesting, paper trading, and brokerage live trading using the same algorithm code model.
Run-mode separation for safer operational validation
Capitalise.ai supports simulated and live run modes within the same strategy workflow. This run-mode switching helps separate validation from live trading without rewriting the strategy.
Match the automation backbone to the execution controls the team can govern
The category breaks down by where automation is anchored and how execution state feeds back into strategy logic. The fork is whether signals are managed in charts, scanners, or code-first strategy runtimes and then handed to execution with enforceable risk gates.
The second fork is governance depth. Option Alpha concentrates guardrails before broker submission, while 3Commas emphasizes centralized bot orchestration across exchange accounts with audit trail visibility but less flexible risk customization than dedicated order management systems.
Choose the strategy anchor that matches how signals are authored
If strategy logic is authored as chart rules and needs visual review during iteration, TrendSpider keeps strategy alerts attached to chart context. If automation must trigger from scanner events with rule triggers and execution logic in one workflow, Trade Ideas routes alerts directly into order automation.
Decide whether execution risk gates must exist before broker submission
If live-trading mistakes must be blocked at the order-intent stage, Option Alpha applies configurable pre-trade constraints before orders reach the broker. If the workflow can tolerate external risk checks and focuses on iterative strategy validation, TrendSpider requires external automation for execution and pre-trade risk checks.
Pick the execution model based on how state reconciliation is handled
If the team needs code to react to fills and status transitions using programmatic lifecycle events, Alpaca emphasizes order lifecycle event handling. If broker-integrated automation should publish granular order and trade state updates for external rule engines, Interactive Brokers provides the feedback model.
Select the backtest and live run model that reduces logic drift
For teams using terminal-native development with deterministic trade-request control, MetaTrader 5 runs MQL5 EAs inside the terminal and uses Strategy Tester for repeatable backtests and paper trading. For teams that want the same algorithm code model from research through live brokerage execution, QuantConnect uses the Lean engine execution lifecycle across backtesting, paper trading, and live.
Confirm the platform’s coverage for the exact broker behaviors being automated
If smart order routing or advanced execution behavior is required, Capitalise.ai may depend on specific broker coverage for those features. If execution order types and routing parameters must be tightly controlled per strategy, Option Alpha needs careful setup for order routing and parameters for each strategy.
Who automated trade software fits best based on workflow and governance needs
Automated trade software fits teams that already treat order intents and execution state as part of the strategy system, not as manual steps. The strongest fit comes when the platform provides a clear automation surface and enough execution feedback to reconcile what actually happened.
The tool list supports different operational styles. Option Alpha targets rule-based strategies that need unattended order handling with guardrails, while 3Commas fits traders who coordinate bots across exchange accounts using structured strategy configuration.
Rule-based strategy teams that want unattended execution with explicit guardrails
Option Alpha best matches workflows where automated order intents need configurable constraints before broker submission. Execution lifecycle management also reduces manual follow-ups after orders are placed.
Traders who iterate on chart signals and want alerts tied to chart context
TrendSpider fits teams that build signal logic in chart rules and need strategy alerts that remain visually inspectable during iteration. The alert-to-execution delegation still requires additional external automation for execution and pre-trade risk checks.
Engineering teams that need event-driven fill and status handling in code
Alpaca fits engineering workflows that require order lifecycle event handling so strategies can react to fills and status transitions. Interactive Brokers fits when broker-integrated automation should publish granular order and trade state events for external rule engines.
Quant research teams that want a single algorithm model from backtest to live
QuantConnect fits code-first teams that want the same Lean engine algorithm code model across research, backtests, paper trading, and live brokerage trading. MetaTrader 5 fits teams that want MQL5 EA event-driven execution and terminal-native Strategy Tester runs.
Traders coordinating bot behavior across multiple exchange accounts
3Commas fits users who want exchange account linking with centralized bot management and structured order flow templates for coordinated entry and exit. Risk customization is less flexible than dedicated order management systems, so governance expectations need to align.
Common failure points when wiring automation to real broker execution
Automation failures often come from missing execution feedback loops or from assumptions that signal validation equals live execution safety. Several tools in this list separate strategy iteration from execution risk checks, which can create gaps if governance is not explicitly implemented.
Another common issue is configuring automation without accounting for platform-specific governance controls and integration limits. MultiCharts can tie strategy generation to the chart workspace, but governance controls like RBAC and audit log are not as explicit as in enterprise order management systems.
Assuming signal correctness automatically implies safe live execution
TrendSpider keeps chart-native strategy alerts inspectable, but execution and pre-trade risk checks require external automation. Pair chart alert logic with an execution safety layer before delegating live orders.
Neglecting integration limits that change which order types and behaviors can be automated
Trade Ideas scanner-to-order automation can be constrained by brokerage connectivity paths for specific order types. Confirm that required order types and execution behaviors exist end to end before building the automation workflow.
Underestimating governance needs for backtest-to-live workflow parity
QuantConnect can connect backtesting, paper trading, and live trading via the Lean engine code model, but broker connectivity and execution behavior vary by venue and setup. Validate live execution behavior with paper trading that mirrors the target brokerage configuration.
Building unattended execution without lifecycle state handling for reconciliation
Alpaca and Interactive Brokers both provide order and execution state events, but automation still needs robust state management in the strategy or external rule engine. Add logic to reconcile fills and status transitions instead of assuming a single happy-path order flow.
How We Selected and Ranked These Tools
We evaluated each tool on execution-related features that affect live order safety, including pre-trade constraints, execution lifecycle event handling, and how signal workflows connect to broker-ready order intents. We weighted features at 40% because order-intent validation and execution feedback determine whether automation can run without manual intervention.
We weighted ease and value at 30% each because correct setup affects throughput and the ability to operate unattended systems. Option Alpha led the ranking because it pairs configurable pre-trade constraints that block invalid order intents before broker submission with execution lifecycle management that reduces manual follow-ups after order placement.
Frequently Asked Questions About automated trade software
How does Option Alpha translate rule logic into live broker orders, and what controls prevent unsafe submissions?
Which platform handles unattended live trading with external logic and event-driven execution feedback?
What breaks if a workflow is built around chart alerts but the broker connectivity or execution step is missing?
When should a team choose QuantConnect over MetaTrader 5 for a code-first backtest-to-live workflow?
How do Capitalise.ai and 3Commas differ in separating simulated validation from live execution?
How does MultiCharts support extensibility compared with TradeCloud-style chartless approaches?
Which tool best supports order lifecycle event handling so strategy code can react to fills and status transitions?
What admin controls and governance features matter for exchange bot orchestration and auditability?
How should a team plan data migration when moving existing strategies to QuantConnect or MetaTrader 5?
Tools reviewed
Primary sources checked during evaluation.
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