{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_talus-network","slug":"talus-network","name":"Talus Network","type":"agent","url":"https://talus.network","page_url":"https://unfragile.ai/talus-network","categories":["ai-agents"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_talus-network__cap_0","uri":"capability://automation.workflow.autonomous.smart.agent.execution.on.chain","name":"autonomous-smart-agent-execution-on-chain","description":"Deploys AI agents that execute complex multi-step blockchain transactions autonomously without human intervention. Agents operate through a runtime that translates natural language or programmatic intent into signed transactions, managing state across multiple on-chain interactions, gas optimization, and transaction ordering. The system likely uses an agentic loop (perception → planning → action) where agents observe blockchain state, reason about optimal execution paths, and submit transactions directly to the network.","intents":["I want an AI agent to automatically execute DeFi arbitrage opportunities across multiple protocols without manual intervention","I need autonomous agents to manage protocol governance tasks like voting, parameter adjustments, and treasury rebalancing","I want to eliminate the need for expensive oracle keepers by having agents autonomously trigger smart contract functions based on off-chain conditions"],"best_for":["DeFi protocol teams managing complex multi-step operations","Blockchain developers building autonomous trading or market-making systems","Protocol DAOs seeking decentralized execution without relying on centralized keepers"],"limitations":["Agent decision-making latency introduces execution risk in fast-moving markets; no guarantees on transaction ordering or MEV protection","Autonomous financial execution creates novel liability and regulatory exposure not yet tested in courts","Agent behavior is difficult to audit and predict at scale; edge cases in complex market conditions may cause unintended transactions","Requires agents to hold private keys or have delegated signing authority, expanding attack surface for key compromise"],"requires":["Blockchain RPC endpoint (Ethereum, Polygon, or other EVM-compatible chain)","Agent wallet with sufficient gas funds for transaction execution","Integration with Talus Network runtime (SDK/API details not publicly documented)"],"input_types":["natural language task descriptions","structured intent definitions (JSON/YAML)","blockchain state queries"],"output_types":["signed transactions","execution logs with transaction hashes","agent decision traces"],"categories":["automation-workflow","planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_1","uri":"capability://tool.use.integration.agent.to.smart.contract.function.calling","name":"agent-to-smart-contract-function-calling","description":"Enables AI agents to discover, validate, and invoke smart contract functions through a schema-based interface that maps contract ABIs to agent-callable tools. The system parses contract function signatures, generates type-safe wrappers, and handles parameter encoding/decoding, allowing agents to call any EVM smart contract function as part of their execution flow. This likely includes gas estimation, transaction simulation, and revert handling.","intents":["I want my agent to call arbitrary smart contract functions across multiple protocols in a single execution plan","I need agents to automatically estimate gas costs and optimize transaction batching when calling multiple contracts","I want agents to simulate transactions before execution to avoid failed transactions and wasted gas"],"best_for":["DeFi developers building cross-protocol agents","Teams integrating with multiple smart contract ecosystems","Developers who want to avoid manual ABI parsing and function encoding"],"limitations":["Requires contract ABIs to be publicly available or manually provided; no built-in contract source verification","Type safety depends on ABI accuracy; malformed or outdated ABIs will cause silent failures or incorrect parameter encoding","No built-in protection against calling dangerous functions (e.g., self-destruct, pause mechanisms); agents can execute any function they have permission to call","Transaction simulation adds latency (~500ms-2s per simulation) and may not catch all edge cases (e.g., state-dependent reverts)"],"requires":["Smart contract ABI in JSON format","Blockchain RPC endpoint with eth_call and eth_estimateGas support","Agent wallet with appropriate contract permissions (allowances, roles, etc.)"],"input_types":["contract ABI (JSON)","function name and parameters","contract address"],"output_types":["encoded transaction calldata","gas estimates","simulation results (success/revert with reason)"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_10","uri":"capability://automation.workflow.cross.chain.agent.coordination.and.settlement","name":"cross-chain-agent-coordination-and-settlement","description":"Enables agents to coordinate execution across multiple blockchains, managing cross-chain state consistency and settlement. The system handles cross-chain messaging, bridges token transfers, and ensures atomic or eventual consistency of multi-chain transactions. This likely includes integration with cross-chain protocols (Wormhole, LayerZero, or similar) and cross-chain state verification.","intents":["I want my agent to execute arbitrage opportunities across multiple chains simultaneously","I need my agent to move assets between chains and execute strategies on each chain","I want to ensure my agent's state remains consistent across multiple chains"],"best_for":["Multi-chain DeFi protocols and arbitrage systems","Teams building cross-chain autonomous strategies","Developers managing agents across multiple blockchain ecosystems"],"limitations":["Cross-chain messaging introduces latency and potential for message loss or ordering issues","No atomic execution across chains; if execution fails on one chain, other chains may already be committed","Cross-chain bridges introduce additional security risks and potential for bridge exploits","State consistency is difficult to maintain; eventual consistency may be the only option for complex multi-chain scenarios"],"requires":["Cross-chain messaging protocol integration (Wormhole, LayerZero, etc.)","RPC endpoints for all chains where agent operates","Cross-chain bridge contracts or protocols"],"input_types":["cross-chain strategy definition","source and destination chain identifiers","cross-chain message data"],"output_types":["cross-chain transaction hashes","settlement confirmation","cross-chain state verification results"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_11","uri":"capability://automation.workflow.agent.governance.and.parameter.management","name":"agent-governance-and-parameter-management","description":"Allows protocols to govern agent behavior through on-chain governance mechanisms, enabling DAOs or protocol teams to update agent parameters, strategies, and permissions without redeploying agents. The system integrates with governance contracts (Compound Governor, OpenZeppelin Governor, or custom governance) and applies governance decisions to agent configuration.","intents":["I want my DAO to vote on and update agent strategies without requiring technical deployment","I need to adjust agent parameters (risk limits, strategy weights) through governance","I want to enable/disable agents or change their permissions through on-chain voting"],"best_for":["Protocol DAOs managing autonomous systems","Teams implementing decentralized governance of autonomous agents","Protocols seeking to reduce centralized control over agent behavior"],"limitations":["Governance delays introduce latency; agents cannot respond immediately to market conditions if parameter changes require voting","Governance is vulnerable to voter apathy, whale voting, and governance attacks; malicious governance decisions could compromise agent behavior","Complex parameter updates may be difficult to express through governance proposals; limited expressiveness for sophisticated strategy changes","No built-in rollback mechanism; bad governance decisions may require another governance vote to fix"],"requires":["Governance contract integration (Compound Governor, OpenZeppelin Governor, or custom)","Governance token and voting mechanism","Agent parameter schema and validation"],"input_types":["governance proposal","parameter updates","voting results"],"output_types":["governance decision execution","agent configuration updates","governance audit logs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_2","uri":"capability://automation.workflow.multi.step.transaction.orchestration.with.state.management","name":"multi-step-transaction-orchestration-with-state-management","description":"Coordinates execution of complex multi-transaction workflows where later transactions depend on outputs of earlier ones. The system manages transaction sequencing, captures on-chain state changes between steps, and handles conditional branching based on transaction results. Agents can define workflows like 'swap token A for B, then deposit proceeds into lending protocol, then borrow against collateral' with automatic state threading and error recovery.","intents":["I want to execute a complex DeFi strategy that requires multiple dependent transactions in the correct order","I need my agent to handle transaction failures gracefully and retry or execute alternative paths","I want to capture intermediate state (e.g., token balances after a swap) and use it in subsequent transactions"],"best_for":["DeFi protocol developers building complex yield strategies","Teams implementing cross-protocol arbitrage or liquidation bots","Developers who need reliable multi-step execution without writing custom orchestration logic"],"limitations":["No atomic execution across multiple transactions; if step N fails, steps 1 to N-1 are already committed on-chain and cannot be rolled back","State captured between transactions may become stale if network conditions change; no built-in optimistic rollup or L2 batching","Workflow definition and error handling logic must be specified upfront; dynamic branching based on complex conditions is limited","Each transaction incurs separate gas costs; no native support for transaction batching or flashbots bundling"],"requires":["Workflow definition format (likely JSON/YAML, exact schema unknown)","Blockchain RPC endpoint","Agent wallet with sufficient gas for all transactions in the workflow"],"input_types":["workflow definition (structured format)","transaction parameters","conditional logic rules"],"output_types":["transaction hashes for each step","captured state between steps","workflow execution log with success/failure status"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_3","uri":"capability://planning.reasoning.agent.decision.tracing.and.explainability","name":"agent-decision-tracing-and-explainability","description":"Records and exposes the reasoning chain behind agent decisions, including what data the agent observed, what options it considered, and why it chose a particular action. The system logs intermediate reasoning steps, constraint evaluations, and risk assessments, allowing developers and auditors to understand why an agent executed a specific transaction. This likely includes structured logging of agent prompts, model outputs, and decision weights.","intents":["I need to audit why my agent executed a particular transaction or strategy to ensure it's behaving as intended","I want to debug agent behavior when it makes unexpected decisions or fails to execute expected strategies","I need to provide compliance evidence showing the reasoning behind autonomous financial transactions"],"best_for":["DeFi protocol teams operating autonomous systems in production","Compliance and risk teams needing audit trails for autonomous execution","Developers debugging agent behavior and optimizing decision-making"],"limitations":["Tracing adds computational overhead and storage costs; full decision traces for every transaction may be prohibitively expensive at scale","Explainability is limited to what the agent's reasoning model exposes; black-box LLM decisions may not be fully interpretable even with tracing","Traces are post-hoc explanations and do not guarantee the agent's reasoning was sound; a well-reasoned decision can still lead to poor outcomes in adversarial markets","No standardized format for decision traces; integration with external audit tools or compliance systems may require custom parsing"],"requires":["Agent runtime with tracing instrumentation enabled","Storage backend for decision logs (database, file system, or blockchain)","Access to agent execution environment (logs not available for third-party agents)"],"input_types":["agent execution context","decision checkpoints"],"output_types":["structured decision traces (JSON/YAML)","reasoning logs with timestamps","constraint evaluation results"],"categories":["planning-reasoning","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_4","uri":"capability://data.processing.analysis.gas.optimization.and.transaction.cost.estimation","name":"gas-optimization-and-transaction-cost-estimation","description":"Analyzes transaction execution paths and recommends or automatically applies gas optimizations such as batching, function selector optimization, or storage layout improvements. The system estimates gas costs before execution, compares alternative execution strategies, and selects the most cost-efficient path. This includes integration with gas price oracles and dynamic fee estimation for EIP-1559 networks.","intents":["I want my agent to automatically choose the cheapest execution path among multiple strategies","I need accurate gas cost estimates before executing transactions so I can assess profitability","I want to optimize transaction batching to reduce per-transaction overhead"],"best_for":["High-frequency DeFi bots where gas costs directly impact profitability","Protocol teams managing large-scale autonomous operations","Developers building cost-sensitive autonomous systems"],"limitations":["Gas estimates are based on current network state and may be inaccurate if conditions change between estimation and execution (mempool volatility, state changes)","Optimization recommendations are heuristic-based; no guarantee that selected path is globally optimal","Dynamic fee estimation (EIP-1559) is reactive and may lag during network congestion; agents may overpay or underpay for gas","Batching optimization requires contract support for batch operations; not all protocols support efficient batching"],"requires":["Blockchain RPC endpoint with eth_estimateGas and eth_gasPrice support","Gas price oracle (Chainlink, MEV-Inspect, or similar)","Access to mempool data for accurate fee estimation (optional but recommended)"],"input_types":["transaction calldata","contract address","network state snapshot"],"output_types":["gas cost estimates (wei)","optimization recommendations","cost comparison across alternative paths"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_5","uri":"capability://safety.moderation.agent.permission.and.access.control.management","name":"agent-permission-and-access-control-management","description":"Manages granular permissions for agents to interact with smart contracts, including allowances, role-based access, and delegation of signing authority. The system enforces least-privilege principles by limiting what functions agents can call, what tokens they can transfer, and what amounts they can spend. This includes integration with contract-level access control (OpenZeppelin AccessControl, custom RBAC) and ERC-20 allowance management.","intents":["I want to limit my agent to only call specific functions on specific contracts to reduce attack surface","I need to set spending limits on tokens so my agent can't drain my entire balance in case of compromise","I want to revoke agent permissions without redeploying contracts or changing agent code"],"best_for":["Protocol teams deploying agents with significant financial authority","Risk-conscious teams implementing defense-in-depth for autonomous systems","Developers managing multiple agents with different permission levels"],"limitations":["Permission enforcement is only as strong as the underlying smart contracts; poorly designed contracts may have permission bypass vulnerabilities","Revoking permissions requires on-chain transactions which incur gas costs and introduce latency; no instant revocation","Complex permission hierarchies are difficult to reason about and audit; unintended permission grants may occur","No built-in support for time-locked permissions or gradual permission escalation; all permissions are static once granted"],"requires":["Smart contracts with permission management (ERC-20 approve/allowance, AccessControl, or custom RBAC)","Agent wallet or contract with delegated signing authority","Permission configuration format (likely JSON/YAML, exact schema unknown)"],"input_types":["permission rules (contract address, function selector, amount limits)","agent identity","access control list (ACL)"],"output_types":["permission validation results","transaction approval/rejection decisions","permission audit logs"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_6","uri":"capability://automation.workflow.real.time.blockchain.state.monitoring.and.triggers","name":"real-time-blockchain-state-monitoring-and-triggers","description":"Continuously monitors blockchain state (token balances, contract events, price feeds, protocol parameters) and triggers agent execution when predefined conditions are met. The system subscribes to relevant state changes, evaluates trigger conditions, and initiates agent workflows automatically. This includes integration with blockchain event logs, oracle feeds, and custom state queries.","intents":["I want my agent to automatically execute when a price reaches a certain threshold or a liquidation opportunity appears","I need my agent to monitor multiple protocols and react to state changes across all of them","I want to trigger agent execution based on complex conditions (e.g., when TVL drops below threshold AND price is above X)"],"best_for":["DeFi bots and arbitrage systems that need to react to market conditions","Protocol teams implementing automated liquidation or rebalancing","Developers building reactive autonomous systems"],"limitations":["Monitoring latency introduces execution delay; agents may miss opportunities if state changes faster than monitoring can detect","Trigger conditions are evaluated off-chain; no guarantee that conditions are still true when agent execution begins (race conditions)","Monitoring multiple state sources increases complexity and potential for missed events; no built-in deduplication or event ordering","Oracle feeds may be stale or manipulated; agents relying on oracle data are vulnerable to oracle attacks"],"requires":["Blockchain RPC endpoint with event filtering (eth_getLogs, eth_subscribe if using WebSocket)","Oracle feed integration (Chainlink, Pyth, or custom oracles)","Trigger condition definition format"],"input_types":["trigger conditions (state predicates)","monitored contracts and events","oracle feed identifiers"],"output_types":["trigger events with context data","agent execution initiation signals","monitoring logs"],"categories":["automation-workflow","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_7","uri":"capability://data.processing.analysis.agent.portfolio.and.position.tracking","name":"agent-portfolio-and-position-tracking","description":"Maintains real-time tracking of agent-controlled assets across multiple protocols and chains, including token balances, LP positions, borrowed amounts, and collateral ratios. The system aggregates position data from multiple sources, calculates portfolio metrics (total value, risk exposure, liquidation risk), and provides visibility into agent financial state. This likely includes integration with DeFi protocol subgraphs and on-chain position tracking.","intents":["I want to see a real-time dashboard of all assets my agent controls across multiple protocols","I need to monitor my agent's liquidation risk and get alerts when collateral ratios drop below safe thresholds","I want to calculate my agent's total portfolio value and performance metrics"],"best_for":["Protocol teams operating agents with significant financial positions","Risk managers monitoring autonomous systems","Developers building agent dashboards and monitoring tools"],"limitations":["Position tracking is only as accurate as the underlying data sources; subgraph delays or RPC inconsistencies can cause stale data","Calculating portfolio value requires price feeds; stale or manipulated prices lead to inaccurate valuations","Cross-chain position tracking requires monitoring multiple blockchains; no single source of truth for multi-chain positions","LP position valuation is complex and depends on impermanent loss calculations; different valuation methods may give different results"],"requires":["Integration with DeFi protocol subgraphs (The Graph, custom indexers)","Price feed integration (Chainlink, Pyth, DEX prices)","Blockchain RPC endpoints for all chains where agent operates"],"input_types":["agent wallet address","list of protocols to track","chain identifiers"],"output_types":["position data (token balances, LP shares, borrowed amounts)","portfolio metrics (total value, risk ratios)","position history and changes"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_8","uri":"capability://safety.moderation.agent.risk.assessment.and.constraint.enforcement","name":"agent-risk-assessment-and-constraint-enforcement","description":"Evaluates transaction proposals against predefined risk constraints before execution, including slippage limits, price impact thresholds, counterparty risk, and protocol-specific risks. The system calculates risk metrics, compares against configured limits, and blocks or modifies transactions that exceed risk tolerance. This includes integration with risk models, price impact simulators, and protocol risk scoring.","intents":["I want to prevent my agent from executing trades with excessive slippage that would be unprofitable","I need to enforce maximum price impact limits to avoid moving markets too much","I want to block transactions to high-risk protocols or counterparties"],"best_for":["Risk-conscious teams deploying agents with significant capital","Protocol teams implementing safety guardrails for autonomous systems","Developers building production-grade autonomous trading systems"],"limitations":["Risk constraints are static and cannot adapt to changing market conditions; overly conservative limits may prevent profitable execution","Risk assessment is based on models and estimates; actual risk may differ from calculated risk","Enforcing constraints adds latency and may cause agents to miss time-sensitive opportunities","No built-in support for dynamic risk adjustment based on agent performance or market volatility"],"requires":["Risk constraint definitions (slippage limits, price impact thresholds, etc.)","Price impact simulator or model","Protocol risk scoring data"],"input_types":["transaction proposal","risk constraint configuration","market data (prices, liquidity)"],"output_types":["risk assessment results","constraint violation alerts","transaction approval/rejection decisions"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_talus-network__cap_9","uri":"capability://data.processing.analysis.agent.performance.analytics.and.backtesting","name":"agent-performance-analytics-and-backtesting","description":"Analyzes agent execution history to calculate performance metrics (returns, Sharpe ratio, win rate, drawdown) and enables backtesting of agent strategies against historical data. The system logs all agent transactions, calculates PnL, and provides analytics dashboards. Backtesting allows developers to evaluate strategy performance before deploying agents with real capital.","intents":["I want to backtest my agent's strategy against historical market data to see if it would have been profitable","I need to calculate my agent's actual returns and compare them against benchmarks","I want to analyze my agent's performance to identify what strategies are working and what need improvement"],"best_for":["Developers optimizing agent strategies before production deployment","Protocol teams evaluating agent performance and ROI","Quantitative teams building sophisticated autonomous trading systems"],"limitations":["Backtesting assumes historical conditions will repeat; past performance does not guarantee future results","Backtesting does not account for slippage, gas costs, or market impact that would occur in live execution","Performance metrics are sensitive to time period selection; different periods may show very different results","No built-in support for multi-agent backtesting or competitive scenarios"],"requires":["Historical market data (prices, volumes, events)","Agent transaction logs","Performance calculation framework"],"input_types":["agent strategy definition","historical market data","transaction logs"],"output_types":["performance metrics (returns, Sharpe ratio, drawdown)","backtest results","performance analytics dashboards"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["Blockchain RPC endpoint (Ethereum, Polygon, or other EVM-compatible chain)","Agent wallet with sufficient gas funds for transaction execution","Integration with Talus Network runtime (SDK/API details not publicly documented)","Smart contract ABI in JSON format","Blockchain RPC endpoint with eth_call and eth_estimateGas support","Agent wallet with appropriate contract permissions (allowances, roles, etc.)","Cross-chain messaging protocol integration (Wormhole, LayerZero, etc.)","RPC endpoints for all chains where agent operates","Cross-chain bridge contracts or protocols","Governance contract integration (Compound Governor, OpenZeppelin Governor, or custom)"],"failure_modes":["Agent decision-making latency introduces execution risk in fast-moving markets; no guarantees on transaction ordering or MEV protection","Autonomous financial execution creates novel liability and regulatory exposure not yet tested in courts","Agent behavior is difficult to audit and predict at scale; edge cases in complex market conditions may cause unintended transactions","Requires agents to hold private keys or have delegated signing authority, expanding attack surface for key compromise","Requires contract ABIs to be publicly available or manually provided; no built-in contract source verification","Type safety depends on ABI accuracy; malformed or outdated ABIs will cause silent failures or incorrect parameter encoding","No built-in protection against calling dangerous functions (e.g., self-destruct, pause mechanisms); agents can execute any function they have permission to call","Transaction simulation adds latency (~500ms-2s per simulation) and may not catch all edge cases (e.g., state-dependent reverts)","Cross-chain messaging introduces latency and potential for message loss or ordering issues","No atomic execution across chains; if execution fails on one chain, other chains may already be committed","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:33.648Z","last_scraped_at":"2026-04-05T13:23:42.559Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=talus-network","compare_url":"https://unfragile.ai/compare?artifact=talus-network"}},"signature":"Nl39DK3QG5TSpsb+arP4457t2uTMpTkzufqSxbKr/SdSUpDbfdW66Z/P1BG57n+WEeQJmiyJFDMHflDu7B4GBw==","signedAt":"2026-06-21T10:27:51.205Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/talus-network","artifact":"https://unfragile.ai/talus-network","verify":"https://unfragile.ai/api/v1/verify?slug=talus-network","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}