[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"workflow-asset-488cac73":3,"seo:featured-workflow:488cac73-4f09-11f1-9bc6-00163e2b0d79:zh":84,"workflow-related-asset-488cac73-488cac73-4f09-11f1-9bc6-00163e2b0d79":85},{"id":4,"uuid":5,"slug":6,"title":7,"description":8,"author_id":9,"author_name":10,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":12,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":15,"tags":22,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":29,"asset_kind":30,"target_tools":31,"install_mode":35,"entrypoint":19,"risk_profile":36,"dependencies":38,"verification":44,"agent_metadata":47,"agent_fit":60,"trust":72,"provenance":81,"created_at":83,"updated_at":83},3657,"488cac73-4f09-11f1-9bc6-00163e2b0d79","asset-488cac73","TradingAgents — Multi-Agent LLM Financial Trading Framework","An open-source multi-agent framework that simulates a trading firm with specialized LLM agents for market analysis, risk management, and trade execution.","8a910e34-3180-11f1-9bc6-00163e2b0d79","Script Depot","https:\u002F\u002Ftokrepo.com\u002Fapple-touch-icon.png",0,"","en",[16],{"id":17,"step_order":18,"title":19,"description":13,"prompt_template":20,"variables":13,"depends_on":21,"expected_output":13},4231,1,"TradingAgents Overview","# TradingAgents — Multi-Agent LLM Financial Trading Framework\n\n## Quick Use\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002FTauricResearch\u002FTradingAgents.git\ncd TradingAgents\npip install -r requirements.txt\npython main.py --ticker AAPL --date 2025-01-15\n```\n\n## Introduction\nTradingAgents is an open-source framework that models a trading firm as a team of specialized LLM agents. Each agent plays a distinct role — analyst, researcher, risk manager, trader — collaborating through structured workflows to make informed trading decisions.\n\n## What TradingAgents Does\n- Simulates a multi-agent trading firm with role-based LLM agents\n- Provides fundamental, technical, and sentiment analysis through specialized analyst agents\n- Includes a risk management agent that evaluates portfolio exposure before trades\n- Aggregates signals from multiple agents into a unified trading decision\n- Supports backtesting against historical market data for strategy evaluation\n\n## Architecture Overview\nTradingAgents uses a LangGraph-based orchestration layer to coordinate agents. A market data pipeline feeds real-time and historical data to analyst agents, whose outputs flow to a portfolio manager agent for aggregation. A risk management agent applies constraints before the final trade execution decision. All agent interactions are logged for auditability.\n\n## Self-Hosting & Configuration\n- Requires Python 3.9+ with LangChain and LangGraph dependencies\n- Configure API keys for market data providers and LLM services via environment variables\n- Customize agent prompts and risk parameters through configuration files\n- Supports multiple LLM backends including OpenAI, Anthropic, and local models\n- Historical market data can be sourced from free APIs or local CSV files\n\n## Key Features\n- Role-based agent architecture mirrors real trading firm workflows\n- Built-in backtesting engine for evaluating strategies on historical data\n- Multi-source analysis combining fundamental, technical, and news sentiment signals\n- Risk management layer with configurable position limits and drawdown thresholds\n- Transparent decision logs showing each agent's contribution to the final trade\n\n## Comparison with Similar Tools\n- **QuantConnect \u002F Backtrader** — traditional algorithmic trading; TradingAgents uses LLM reasoning\n- **CrewAI** — general multi-agent framework; TradingAgents is purpose-built for financial markets\n- **AutoGen** — multi-agent conversations; TradingAgents provides domain-specific trading roles\n- **ai-hedge-fund** — similar concept; TradingAgents offers more structured role separation and risk controls\n\n## FAQ\n**Q: Can TradingAgents execute real trades?**\nA: The default setup is for analysis and backtesting only. Broker integration requires additional configuration.\n\n**Q: What market data sources are supported?**\nA: Yahoo Finance, Alpha Vantage, and custom CSV data sources out of the box.\n\n**Q: Does it work with local LLMs?**\nA: Yes. Any LangChain-compatible model can be used, including Ollama-hosted models.\n\n**Q: Is this financial advice?**\nA: No. TradingAgents is a research and educational tool, not a financial advisory service.\n\n## Sources\n- https:\u002F\u002Fgithub.com\u002FTauricResearch\u002FTradingAgents\n- https:\u002F\u002Farxiv.org\u002Fabs\u002F2412.20138","0",[23],{"id":24,"name":25,"slug":26,"icon":27},11,"Scripts","script","📜",false,"72b4e4e1b31198b8698a828a80111cfc966d42c340cdc827557d579e6f79cc8f","skill",[32,33,34],"claude_code","codex","gemini_cli","single",{"executes_code":28,"modifies_global_config":28,"requires_secrets":37,"uses_absolute_paths":28,"network_access":28},[],{"npm":39,"pip":40,"brew":42,"system":43},[],[41],"requirements.txt",[],[],{"commands":45,"expected_files":46},[],[19],{"asset_kind":30,"target_tools":48,"install_mode":35,"entrypoint":19,"risk_profile":49,"dependencies":51,"content_hash":29,"verification":56,"inferred":59},[32,33,34],{"executes_code":28,"modifies_global_config":28,"requires_secrets":50,"uses_absolute_paths":28,"network_access":28},[],{"npm":52,"pip":53,"brew":54,"system":55},[],[41],[],[],{"commands":57,"expected_files":58},[],[19],true,{"target":33,"score":61,"status":62,"policy":63,"why":64,"asset_kind":30,"install_mode":35},98,"native","allow",[65,66,67,68,69,70,71],"target_tools includes codex","asset_kind skill","install_mode single","markdown-only","policy allow","safe markdown-only Codex install","trust established",{"author_trust_level":73,"verified_publisher":28,"asset_signed_hash":29,"signature_status":74,"install_count":12,"report_count":12,"dangerous_capability_badges":75,"review_status":76,"signals":77},"established","hash_only",[],"unreviewed",[78,79,80],"author has published assets","content hash available","no dangerous capability badges",{"owner_uuid":9,"owner_name":10,"source_url":82,"content_hash":29,"visibility":18,"created_at":83,"updated_at":83},"https:\u002F\u002Ftokrepo.com\u002Fen\u002Fworkflows\u002Fasset-488cac73","2026-05-14 04:21:11",null,[86,141,187,239],{"id":87,"uuid":88,"slug":89,"title":90,"description":91,"author_id":92,"author_name":93,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":94,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":95,"tags":96,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":98,"asset_kind":26,"target_tools":99,"install_mode":35,"entrypoint":100,"risk_profile":101,"dependencies":102,"verification":107,"agent_metadata":110,"agent_fit":121,"trust":128,"provenance":131,"created_at":133,"updated_at":134,"__relatedScore":135,"__relatedReasons":136,"__sharedTags":139},3277,"79c28341-ca9a-585d-b8cf-b183829b6d9d","hive-framework-outcome-driven-multi-agent-harness","Hive Framework — Outcome-Driven Multi-Agent Harness","Hive Framework turns natural-language goals into generated agent graphs and dashboards, giving teams a production-minded multi-agent harness.","8a910fec-3180-11f1-9bc6-00163e2b0d79","Agent Toolkit",12,[],[97],{"id":24,"name":25,"slug":26,"icon":27},"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",[32,33,34],"quickstart.sh",{"executes_code":28,"modifies_global_config":28,"requires_secrets":84,"uses_absolute_paths":28,"network_access":28},{"npm":103,"pip":104,"brew":105,"system":106},[],[],[],[],{"commands":108,"expected_files":109},[],[],{"asset_kind":26,"target_tools":111,"install_mode":35,"entrypoint":100,"risk_profile":112,"dependencies":113,"content_hash":98,"verification":118},[32,33,34],{"executes_code":28,"modifies_global_config":28,"requires_secrets":84,"uses_absolute_paths":28,"network_access":28},{"npm":114,"pip":115,"brew":116,"system":117},[],[],[],[],{"commands":119,"expected_files":120},[],[],{"target":33,"score":122,"status":123,"policy":123,"why":124,"asset_kind":26,"install_mode":35},29,"stage_only",[65,125,67,68,126,127,71],"asset_kind script","policy stage_only","asset_kind script is not activated directly for Codex",{"author_trust_level":73,"verified_publisher":28,"asset_signed_hash":98,"signature_status":74,"install_count":12,"report_count":12,"dangerous_capability_badges":129,"review_status":76,"signals":130},[26],[78,79],{"owner_uuid":92,"owner_name":93,"source_url":132,"content_hash":98,"visibility":18,"created_at":133,"updated_at":134},"https:\u002F\u002Ftokrepo.com\u002Fen\u002Fworkflows\u002Fhive-framework-outcome-driven-multi-agent-harness","2026-05-12 22:02:44","2026-05-14 00:44:46",101.67091502846026,[137,138],"topic-match","same-target",[26,140],"scripts",{"id":142,"uuid":143,"slug":144,"title":145,"description":146,"author_id":9,"author_name":10,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":12,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":147,"tags":148,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":98,"asset_kind":30,"target_tools":150,"install_mode":35,"entrypoint":151,"risk_profile":152,"dependencies":154,"verification":159,"agent_metadata":162,"agent_fit":174,"trust":176,"provenance":179,"created_at":181,"updated_at":181,"__relatedScore":182,"__relatedReasons":183,"__sharedTags":186},3659,"7368bde3-4f09-11f1-9bc6-00163e2b0d79","asset-7368bde3","MiroFish — Universal Swarm Intelligence Prediction Engine","An open-source swarm intelligence engine that uses multi-agent simulation and knowledge graphs to predict trends in social, financial, and public opinion domains.",[],[149],{"id":24,"name":25,"slug":26,"icon":27},[32,33,34],"SKILL.md",{"executes_code":28,"modifies_global_config":28,"requires_secrets":153,"uses_absolute_paths":28,"network_access":28},[],{"npm":155,"pip":156,"brew":157,"system":158},[],[],[],[],{"commands":160,"expected_files":161},[],[],{"asset_kind":30,"target_tools":163,"install_mode":35,"entrypoint":151,"risk_profile":164,"dependencies":166,"content_hash":98,"verification":171,"inferred":59},[32,33,34],{"executes_code":28,"modifies_global_config":28,"requires_secrets":165,"uses_absolute_paths":28,"network_access":28},[],{"npm":167,"pip":168,"brew":169,"system":170},[],[],[],[],{"commands":172,"expected_files":173},[],[],{"target":33,"score":61,"status":62,"policy":63,"why":175,"asset_kind":30,"install_mode":35},[65,66,67,68,69,70,71],{"author_trust_level":73,"verified_publisher":28,"asset_signed_hash":98,"signature_status":74,"install_count":12,"report_count":12,"dangerous_capability_badges":177,"review_status":76,"signals":178},[],[78,79,80],{"owner_uuid":9,"owner_name":10,"source_url":180,"content_hash":98,"visibility":18,"created_at":181,"updated_at":181},"https:\u002F\u002Ftokrepo.com\u002Fen\u002Fworkflows\u002Fasset-7368bde3","2026-05-14 04:22:23",93,[137,184,138,185],"same-kind","same-author",[26,140],{"id":188,"uuid":189,"slug":190,"title":191,"description":192,"author_id":193,"author_name":194,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":195,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":196,"tags":197,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":202,"asset_kind":30,"target_tools":203,"install_mode":35,"entrypoint":204,"risk_profile":205,"dependencies":207,"verification":212,"agent_metadata":215,"agent_fit":227,"trust":229,"provenance":232,"created_at":234,"updated_at":235,"__relatedScore":236,"__relatedReasons":237,"__sharedTags":238},2061,"b9233350-3fda-11f1-9bc6-00163e2b0d79","agentscope-distributed-multi-agent-platform-b9233350","AgentScope — Distributed Multi-Agent Platform","AgentScope is a multi-agent framework supporting distributed agent communication, built-in fault tolerance, and an actor-based runtime for building complex multi-agent applications at scale.","8a911193-3180-11f1-9bc6-00163e2b0d79","AI Open Source",96,[],[198],{"id":94,"name":199,"slug":200,"icon":201},"Configs","config","⚙️","8c59171a85b6bf8302a34215671d7138864b5ecc7b4d25d8c24e8bd99dc838b6",[32,33,34],"AgentScope Overview",{"executes_code":28,"modifies_global_config":28,"requires_secrets":206,"uses_absolute_paths":28,"network_access":28},[],{"npm":208,"pip":209,"brew":210,"system":211},[],[],[],[],{"commands":213,"expected_files":214},[],[204],{"asset_kind":30,"target_tools":216,"install_mode":35,"entrypoint":204,"risk_profile":217,"dependencies":219,"content_hash":202,"verification":224},[32,33,34],{"executes_code":28,"modifies_global_config":28,"requires_secrets":218,"uses_absolute_paths":28,"network_access":28},[],{"npm":220,"pip":221,"brew":222,"system":223},[],[],[],[],{"commands":225,"expected_files":226},[],[204],{"target":33,"score":61,"status":62,"policy":63,"why":228,"asset_kind":30,"install_mode":35},[65,66,67,68,69,70,71],{"author_trust_level":73,"verified_publisher":28,"asset_signed_hash":202,"signature_status":74,"install_count":12,"report_count":12,"dangerous_capability_badges":230,"review_status":76,"signals":231},[],[78,79,80],{"owner_uuid":193,"owner_name":194,"source_url":233,"content_hash":202,"visibility":18,"created_at":234,"updated_at":235},"https:\u002F\u002Ftokrepo.com\u002Fen\u002Fworkflows\u002Fagentscope-distributed-multi-agent-platform-b9233350","2026-04-24 20:40:06","2026-05-14 02:41:42",91.98015760139937,[137,184,138],[],{"id":240,"uuid":241,"slug":242,"title":243,"description":244,"author_id":92,"author_name":93,"author_avatar":11,"token_estimate":12,"time_saved":12,"model_used":13,"fork_count":12,"vote_count":12,"view_count":94,"parent_id":12,"parent_uuid":13,"lang_type":14,"steps":245,"tags":246,"has_voted":28,"visibility":18,"share_token":13,"is_featured":12,"content_hash":98,"asset_kind":26,"target_tools":248,"install_mode":35,"entrypoint":249,"risk_profile":250,"dependencies":251,"verification":256,"agent_metadata":259,"agent_fit":270,"trust":272,"provenance":275,"created_at":277,"updated_at":278,"__relatedScore":279,"__relatedReasons":280,"__sharedTags":281},3092,"716fc1ad-c3a2-49ab-a810-3a139949e377","camel-multi-agent-and-tooling-library","CAMEL — Multi-Agent and Tooling Library","CAMEL is an open-source library for multi-agent systems and tools. Install `camel-ai`, then compose agents, tools, and optional web helpers in Python.",[],[247],{"id":24,"name":25,"slug":26,"icon":27},[32,33,34],"README.md",{"executes_code":28,"modifies_global_config":28,"requires_secrets":84,"uses_absolute_paths":28,"network_access":28},{"npm":252,"pip":253,"brew":254,"system":255},[],[],[],[],{"commands":257,"expected_files":258},[],[],{"asset_kind":26,"target_tools":260,"install_mode":35,"entrypoint":249,"risk_profile":261,"dependencies":262,"content_hash":98,"verification":267},[32,33,34],{"executes_code":28,"modifies_global_config":28,"requires_secrets":84,"uses_absolute_paths":28,"network_access":28},{"npm":263,"pip":264,"brew":265,"system":266},[],[],[],[],{"commands":268,"expected_files":269},[],[],{"target":33,"score":122,"status":123,"policy":123,"why":271,"asset_kind":26,"install_mode":35},[65,125,67,68,126,127,71],{"author_trust_level":73,"verified_publisher":28,"asset_signed_hash":98,"signature_status":74,"install_count":12,"report_count":12,"dangerous_capability_badges":273,"review_status":76,"signals":274},[26],[78,79],{"owner_uuid":92,"owner_name":93,"source_url":276,"content_hash":98,"visibility":18,"created_at":277,"updated_at":278},"https:\u002F\u002Ftokrepo.com\u002Fen\u002Fworkflows\u002Fcamel-multi-agent-and-tooling-library","2026-05-12 00:58:31","2026-05-14 00:43:43",90.67091502846026,[137,138],[26,140]]