{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-mergisi--awesome-openclaw-agents","slug":"mergisi--awesome-openclaw-agents","name":"awesome-openclaw-agents","type":"repo","url":"https://crewclaw.com","page_url":"https://unfragile.ai/mergisi--awesome-openclaw-agents","categories":["ai-agents","deployment-infra"],"tags":["ai-agent-templates","ai-agents","ai-automation","anthropic","automation","awesome","awesome-list","claude","community-agents","crewclaw","docker","llm","mcp","multi-agent","no-code","openclaw","productivity","soul-md","submit-your-agent","telegram-bot"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-mergisi--awesome-openclaw-agents__cap_0","uri":"capability://automation.workflow.soul.md.based.agent.configuration.definition","name":"soul.md-based agent configuration definition","description":"Defines AI agent behavior, identity, and operational rules entirely through markdown configuration files rather than code. The SOUL.md format specifies agent personality, system prompts, capabilities, constraints, and decision-making rules in a declarative, version-controllable format that maps directly to agent runtime behavior without requiring compilation or code generation.","intents":["Define agent behavior and personality without writing code","Version control agent configurations alongside infrastructure","Port agent definitions between local and cloud deployments identically","Rapidly iterate on agent prompts and rules without redeployment"],"best_for":["Teams building no-code AI agent workflows","Organizations standardizing agent definitions across teams","Developers prototyping agents before production deployment"],"limitations":["SOUL.md syntax is OpenClaw-specific; not portable to other agent frameworks without conversion","Complex conditional logic or dynamic behavior requires AGENTS.md extensions; pure markdown has limited expressiveness","No built-in version conflict resolution for concurrent agent edits"],"requires":["OpenClaw runtime or CrewClaw platform access","Basic markdown authoring capability","Understanding of agent role, constraints, and system prompt structure"],"input_types":["markdown text","structured configuration blocks"],"output_types":["agent runtime configuration","behavioral specification"],"categories":["automation-workflow","configuration-as-code"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_1","uri":"capability://data.processing.analysis.machine.readable.agent.registry.with.programmatic.discovery","name":"machine-readable agent registry with programmatic discovery","description":"Maintains agents.json as a centralized, machine-readable registry indexing all 177+ agent templates across 24 categories with metadata including ID, role, path, tier, and capabilities. This enables programmatic discovery, filtering, and automated deployment without manual catalog searches, supporting tools and platforms that need to query available agents by category, capability, or deployment target.","intents":["Programmatically discover agents matching specific use cases or categories","Filter agents by tier (Basic, Standard, Full) or required capabilities","Automate agent deployment selection based on infrastructure constraints","Build dashboards or CLIs that surface available agent templates"],"best_for":["Platform builders integrating OpenClaw agents into larger systems","DevOps teams automating agent deployment pipelines","Teams building internal agent discovery tools or marketplaces"],"limitations":["agents.json is static and requires manual updates when new agents are added; no real-time sync with filesystem","Registry schema is OpenClaw-specific; integration with non-OpenClaw systems requires custom mapping","No built-in versioning or deprecation tracking for agent templates"],"requires":["JSON parsing capability in deployment tooling","agents.json file accessible in repository or via API","Understanding of registry schema (id, category, name, role, path, tier fields)"],"input_types":["JSON registry file","query filters (category, tier, capability)"],"output_types":["filtered agent metadata","agent paths for deployment","structured agent catalog"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_10","uri":"capability://planning.reasoning.agent.tier.classification.basic.standard.full","name":"agent tier classification (basic, standard, full)","description":"Classifies agents into three tiers (Basic, Standard, Full) based on complexity, capabilities, and production-readiness. This tiering system helps developers understand agent maturity and select appropriate templates for their use cases, with Basic agents suitable for simple tasks, Standard agents for common workflows, and Full agents for complex multi-step processes with advanced features.","intents":["Understand agent complexity and production-readiness at a glance","Select agents appropriate for specific use case complexity","Identify which agents require additional configuration or customization","Plan agent deployment based on tier requirements"],"best_for":["Teams evaluating agents for adoption","Developers selecting templates based on complexity requirements","Organizations planning agent rollout by maturity level"],"limitations":["Tier classification is subjective; no formal criteria for tier assignment","Tier does not indicate performance characteristics or scalability; a Full agent may not be more performant than a Standard agent","Tier classification is static; agents do not automatically upgrade tiers as they mature","No guidance on tier migration; upgrading from Basic to Standard requires manual reconfiguration"],"requires":["Understanding of agent tier definitions (Basic, Standard, Full)","agents.json registry with tier metadata","Assessment of use case complexity to select appropriate tier"],"input_types":["agent metadata with tier classification","use case requirements"],"output_types":["tier classification","agent recommendations by tier","complexity assessment"],"categories":["planning-reasoning","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_11","uri":"capability://automation.workflow.community.agent.submission.and.curation.workflow","name":"community agent submission and curation workflow","description":"Provides a structured submission process for community members to contribute new agent templates to the repository. Submissions go through quality review, documentation validation, and testing before being merged, ensuring all agents in the repository meet production-ready standards. This enables the community to expand the template library while maintaining quality and consistency.","intents":["Submit custom agents to the community repository","Get feedback on agent design and implementation","Share agents with other developers","Contribute to the OpenClaw ecosystem"],"best_for":["Developers with production-ready agents to share","Teams contributing domain-specific agent templates","Community members improving the template library"],"limitations":["Submission review process is manual; no automated quality checks or CI/CD validation","Acceptance criteria are not formally documented; submissions may be rejected without clear feedback","No incentive structure for contributions; community relies on voluntary participation","Submitted agents may become outdated if maintainers do not update them for API changes"],"requires":["GitHub account and familiarity with pull requests","Production-ready agent with SOUL.md, README.md, and optional AGENTS.md/HEARTBEAT.md/WORKING.md","Compliance with repository structure and naming conventions","Willingness to respond to review feedback and make changes"],"input_types":["agent template files (SOUL.md, README.md, etc.)","pull request with submission","documentation and examples"],"output_types":["merged agent template","entry in agents.json registry","published agent in repository"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_12","uri":"capability://planning.reasoning.moltbook.agent.social.networking.and.discovery","name":"moltbook agent social networking and discovery","description":"Provides Moltbook as a social networking platform for agents, enabling agents to discover, interact with, and collaborate with other agents in a shared ecosystem. Agents can publish profiles, advertise capabilities, and establish connections with complementary agents, facilitating organic agent composition and multi-agent collaboration without manual orchestration.","intents":["Enable agents to discover other agents with complementary capabilities","Facilitate agent-to-agent collaboration and communication","Build agent networks and communities around shared domains","Enable agents to advertise capabilities and find partners"],"best_for":["Organizations building large multi-agent ecosystems","Developers exploring emergent agent collaboration patterns","Teams building agent marketplaces or networks"],"limitations":["Moltbook is a novel concept with limited real-world deployment data; reliability and scalability are unproven","Agent discovery is social-network based; no formal capability matching or compatibility checking","Agent-to-agent communication protocols are not standardized; agents must implement custom communication logic","No built-in governance or trust mechanisms; agents may be malicious or unreliable"],"requires":["Moltbook platform access and account","Agent configured to publish profile and capabilities","Agent communication protocols implemented for agent-to-agent interaction","Understanding of agent networking and discovery patterns"],"input_types":["agent profile and capabilities","agent discovery queries","agent-to-agent communication messages"],"output_types":["agent profiles and connections","agent discovery results","agent collaboration opportunities"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_13","uri":"capability://planning.reasoning.agents.md.operating.rules.and.conditional.logic","name":"agents.md operating rules and conditional logic","description":"Extends agent behavior beyond SOUL.md by defining operating rules, conditional logic, and decision-making frameworks in AGENTS.md files. This enables agents to implement complex workflows, conditional branching, error handling, and adaptive behavior without requiring code changes, keeping agent logic declarative and version-controllable.","intents":["Define complex conditional logic and decision trees for agents","Implement error handling and fallback strategies","Create adaptive agent behavior based on context or state","Specify operating rules and constraints for agent execution"],"best_for":["Agents with complex decision logic or workflows","Teams implementing conditional agent behavior","Developers building adaptive agents that change behavior based on context"],"limitations":["AGENTS.md syntax is OpenClaw-specific; complex logic may be difficult to express in markdown format","No built-in support for loops or recursion; complex iterative logic requires custom implementation","Conditional logic is evaluated at runtime; no static analysis or validation of logic correctness","AGENTS.md is optional; agents without AGENTS.md cannot implement complex conditional behavior"],"requires":["AGENTS.md file with operating rules and conditional logic","Understanding of agent decision-making and workflow patterns","OpenClaw runtime that interprets AGENTS.md"],"input_types":["AGENTS.md configuration","conditional rules and logic","decision tree definitions"],"output_types":["agent behavior based on rules","conditional execution paths","adaptive agent responses"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_14","uri":"capability://text.generation.language.agent.readme.documentation.generation.and.validation","name":"agent readme documentation generation and validation","description":"Requires each agent template to include a README.md file documenting the agent's purpose, capabilities, configuration, and usage examples. The repository enforces documentation standards through submission review, ensuring all agents are well-documented and discoverable. This enables developers to understand agent functionality without reading source code or configuration files.","intents":["Understand agent purpose and capabilities from documentation","Learn how to configure and deploy agents","Find usage examples and best practices","Evaluate agents before adoption"],"best_for":["Developers evaluating agents for adoption","Teams onboarding new agents","Organizations building internal agent catalogs"],"limitations":["Documentation quality varies; some README files may be incomplete or outdated","No automated documentation validation; README files may not match actual agent behavior","Documentation is static; it does not update automatically when agent configuration changes","No standardized documentation format; README files may have inconsistent structure"],"requires":["README.md file in agent template directory","Documentation covering agent purpose, capabilities, configuration, and usage","Compliance with repository documentation standards"],"input_types":["agent template","documentation requirements"],"output_types":["README.md file","agent documentation","usage examples"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_15","uri":"capability://data.processing.analysis.hierarchical.agent.template.organization.and.file.structure","name":"hierarchical agent template organization and file structure","description":"Implements a strict hierarchical directory structure (agents/{category}/{agent-name}/) that maps directly to agent categorization and enables consistent file organization. This structure ensures all agents follow the same layout pattern, making it easy to navigate the repository, discover agents by category, and enforce consistent naming conventions and file requirements.","intents":["Navigate agent templates by category and name","Enforce consistent file structure across all agents","Enable programmatic discovery of agents by category","Simplify agent submission by providing clear directory structure"],"best_for":["Large template repositories with many agents","Teams enforcing consistent agent organization","Developers building tools that parse agent directories"],"limitations":["Hierarchical structure is rigid; agents cannot belong to multiple categories without duplication","Deep directory nesting may make file paths long and difficult to navigate","Renaming categories or agents requires updating all references in agents.json and documentation","No support for agent inheritance or composition; each agent is independent"],"requires":["Compliance with agents/{category}/{agent-name}/ directory structure","Consistent file naming (SOUL.md, README.md, etc.)","Understanding of agent categorization and naming conventions"],"input_types":["agent template files","category and agent name"],"output_types":["organized agent directory structure","consistent file layout"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_2","uri":"capability://automation.workflow.local.agent.deployment.via.openclaw.cli","name":"local agent deployment via openclaw cli","description":"Provides command-line interface for deploying agent templates locally by parsing SOUL.md configurations and initializing the agent runtime environment. The openclaw CLI reads agent definitions, resolves dependencies, configures environment variables, and starts the agent process, enabling developers to run production-ready agents on their machines without cloud infrastructure or manual setup.","intents":["Deploy agents locally for testing and development","Run agents without cloud platform dependencies","Integrate agents into local development workflows","Debug agent behavior before cloud deployment"],"best_for":["Solo developers prototyping agent workflows","Teams testing agents in isolated environments","Organizations with on-premise deployment requirements"],"limitations":["No built-in persistence layer; agents require external state store (database, file system) for long-term memory","Local deployment lacks the scaling and monitoring capabilities of CrewClaw platform","CLI abstractions add ~200ms latency per agent initialization compared to direct runtime invocation","No native support for multi-agent orchestration; requires manual coordination between locally-deployed agents"],"requires":["openclaw CLI installed and in system PATH","Python 3.9+ or Node.js 18+ (depending on agent runtime)","Agent template directory with valid SOUL.md file","Environment variables for API keys (OpenAI, Anthropic, etc.) if agent uses external LLMs"],"input_types":["SOUL.md configuration file","environment variables","command-line arguments"],"output_types":["running agent process","agent logs and output","agent state (if persistence configured)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_3","uri":"capability://automation.workflow.crewclaw.platform.managed.agent.deployment","name":"crewclaw platform-managed agent deployment","description":"Provides managed deployment infrastructure for agents via the CrewClaw platform, handling scaling, monitoring, persistence, and multi-agent orchestration. Agents defined in SOUL.md are deployed to CrewClaw's hosted environment where they gain automatic state management via WORKING.md, scheduled execution via HEARTBEAT.md, and integration with messaging platforms and MCP servers without manual infrastructure setup.","intents":["Deploy agents to production without managing servers","Enable autonomous agent scheduling and wake-up behavior","Persist agent state across executions","Monitor agent performance and logs in managed environment","Integrate agents with external platforms (Telegram, Slack, etc.)"],"best_for":["Teams deploying agents to production without DevOps resources","Organizations requiring agent persistence and scheduling","Builders integrating agents with messaging platforms or external APIs"],"limitations":["CrewClaw platform lock-in; agents deployed to CrewClaw cannot be easily migrated to other platforms without reconfiguration","Managed platform adds latency (typically 500ms-2s per agent invocation) compared to local deployment","Pricing model not specified; potential cost scaling issues for high-frequency agent executions","Limited visibility into underlying infrastructure; debugging requires platform-provided logs and monitoring"],"requires":["CrewClaw account and API credentials","Valid SOUL.md agent configuration","Internet connectivity for platform communication","Optional: WORKING.md for state persistence, HEARTBEAT.md for scheduled execution"],"input_types":["SOUL.md configuration","WORKING.md state schema (optional)","HEARTBEAT.md schedule definition (optional)","environment variables for API keys"],"output_types":["deployed agent endpoint","agent execution logs","persisted agent state","monitoring metrics"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_4","uri":"capability://memory.knowledge.agent.state.persistence.via.working.md.specification","name":"agent state persistence via working.md specification","description":"Defines a schema-based state persistence mechanism where agents declare their persistent state structure in WORKING.md files. The CrewClaw platform automatically manages agent state across executions, enabling agents to maintain context, memory, and decision history without requiring developers to implement custom database logic or state serialization.","intents":["Persist agent memory and context across multiple executions","Enable agents to maintain decision history and learned patterns","Share state between multi-agent systems without manual coordination","Recover agent state after failures or platform restarts"],"best_for":["Long-running agents that need to remember past interactions","Multi-agent systems where agents must share context","Agents that learn or adapt based on historical data"],"limitations":["WORKING.md schema is declarative only; complex state transformations require custom logic outside the specification","No built-in versioning or migration system for state schema changes; breaking changes require manual data migration","State persistence is platform-dependent; agents using WORKING.md cannot easily migrate to local deployment without external state store","No transaction guarantees; concurrent agent executions may cause state conflicts"],"requires":["CrewClaw platform deployment (local deployment does not support WORKING.md persistence)","WORKING.md file defining state schema in OpenClaw format","Understanding of agent state requirements and schema design"],"input_types":["WORKING.md schema definition","agent execution context","state update operations"],"output_types":["persisted agent state","state retrieval for agent access","state history (if tracked)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_5","uri":"capability://automation.workflow.autonomous.agent.scheduling.via.heartbeat.md","name":"autonomous agent scheduling via heartbeat.md","description":"Enables agents to execute autonomously on defined schedules by specifying wake-up conditions and execution intervals in HEARTBEAT.md files. The CrewClaw platform interprets HEARTBEAT.md to trigger agent execution at specified times or conditions without requiring external schedulers, enabling agents to perform periodic tasks, monitoring, or proactive actions automatically.","intents":["Schedule agents to run at specific times or intervals","Enable agents to monitor systems and trigger actions proactively","Implement periodic tasks (reports, cleanup, health checks) without external schedulers","Define conditional wake-up logic based on external events or state changes"],"best_for":["Agents performing periodic monitoring or reporting","Automation workflows that need scheduled execution","DevOps agents that check system health at intervals"],"limitations":["HEARTBEAT.md scheduling is platform-dependent; agents using HEARTBEAT.md cannot run locally without custom scheduler implementation","No built-in support for complex scheduling logic (e.g., conditional scheduling based on external data); requires AGENTS.md extensions","Scheduling precision depends on CrewClaw platform infrastructure; no SLA guarantees for execution timing","No native support for distributed scheduling across multiple agent instances"],"requires":["CrewClaw platform deployment","HEARTBEAT.md file defining schedule and wake-up conditions","Agent configured to handle autonomous execution without user input"],"input_types":["HEARTBEAT.md schedule specification","cron expressions or interval definitions","conditional wake-up rules"],"output_types":["scheduled agent execution","execution logs and results","state updates from autonomous runs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_6","uri":"capability://planning.reasoning.multi.agent.orchestration.and.coordination.patterns","name":"multi-agent orchestration and coordination patterns","description":"Provides architectural patterns and templates for coordinating multiple agents to work together on complex tasks. The repository includes pre-built multi-agent templates that demonstrate agent-to-agent communication, task delegation, result aggregation, and conflict resolution, enabling developers to compose agents without building custom orchestration logic.","intents":["Coordinate multiple agents on a single complex task","Implement agent-to-agent communication and result passing","Delegate subtasks from one agent to another","Aggregate results from parallel agent executions"],"best_for":["Teams building complex automation workflows requiring multiple specialized agents","Organizations implementing multi-agent systems for business processes","Developers prototyping agent collaboration patterns"],"limitations":["Multi-agent orchestration patterns are template-based; complex custom coordination logic requires extending AGENTS.md or SOUL.md","No built-in distributed transaction support; agent failures during multi-agent workflows may leave partial state","Agent communication is synchronous by default; asynchronous patterns require custom implementation","Limited visibility into agent-to-agent communication; debugging multi-agent workflows requires platform-provided tracing"],"requires":["Multiple agent templates deployed to same platform (local or CrewClaw)","Understanding of agent communication patterns (direct calls, message passing, shared state)","Orchestration logic defined in AGENTS.md or custom coordination agent"],"input_types":["agent template definitions","task specifications","agent communication protocols"],"output_types":["coordinated agent execution results","aggregated outputs from multiple agents","execution logs showing agent interactions"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_7","uri":"capability://tool.use.integration.mcp.server.integration.and.extension","name":"mcp server integration and extension","description":"Enables agents to integrate with Model Context Protocol (MCP) servers, extending agent capabilities beyond built-in functions. Agents can declare MCP server dependencies in SOUL.md or AGENTS.md, and the platform automatically connects agents to MCP servers for tool use, data access, and external system integration without requiring agents to implement custom API clients.","intents":["Extend agent capabilities by connecting to MCP servers","Enable agents to access external tools and data sources","Integrate agents with third-party services via MCP","Compose agents with specialized tool providers"],"best_for":["Teams building agents that need access to specialized tools or data","Organizations with existing MCP server infrastructure","Developers extending agents with custom capabilities"],"limitations":["MCP server integration requires MCP server to be running and accessible; no built-in MCP server provisioning","Agent-to-MCP communication adds latency (typically 100-500ms per tool call) depending on network and server performance","Error handling for MCP server failures is agent-dependent; no built-in retry or fallback logic","MCP schema validation is minimal; malformed tool definitions may cause agent failures at runtime"],"requires":["MCP server running and accessible to agent","MCP server definition or endpoint URL","Agent configured to declare MCP dependencies in SOUL.md or AGENTS.md","Understanding of MCP tool schema and invocation patterns"],"input_types":["MCP server endpoint or definition","tool schema declarations","agent configuration with MCP references"],"output_types":["tool invocation results","extended agent capabilities","MCP server responses"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_8","uri":"capability://tool.use.integration.messaging.platform.integration.telegram.slack.etc","name":"messaging platform integration (telegram, slack, etc.)","description":"Provides pre-built integrations enabling agents to receive messages from and send responses to messaging platforms like Telegram and Slack. Agents deployed to CrewClaw can be configured to listen for messages on these platforms, process them through agent logic, and respond directly in the messaging interface without requiring developers to build custom message handlers or webhooks.","intents":["Deploy agents as chatbots on Telegram or Slack","Enable users to interact with agents through familiar messaging apps","Automate responses to messages using agent logic","Build conversational workflows integrated with messaging platforms"],"best_for":["Teams building chatbots for internal or external users","Organizations automating customer support via messaging platforms","Developers creating conversational AI workflows"],"limitations":["Messaging platform integrations are platform-specific; agents must be reconfigured for each platform","Message rate limiting depends on platform API quotas; high-volume messaging may require custom rate limiting logic","Conversation context is limited to message history; agents cannot access full conversation context without custom state management","Platform-specific features (buttons, rich formatting) require custom agent logic; not abstracted by framework"],"requires":["CrewClaw platform deployment","Messaging platform account and API credentials (Telegram bot token, Slack app token)","Agent configured to handle message input and generate text responses","Webhook or polling mechanism configured for message delivery"],"input_types":["messages from messaging platform","user IDs and conversation context","platform-specific metadata"],"output_types":["agent responses sent to messaging platform","conversation logs","platform-specific message formats"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-mergisi--awesome-openclaw-agents__cap_9","uri":"capability://search.retrieval.agent.template.categorization.and.discovery.across.24.domains","name":"agent template categorization and discovery across 24 domains","description":"Organizes 177+ production-ready agent templates across 24 specialized categories (marketing, business, DevOps, healthcare, finance, etc.), enabling developers to discover agents relevant to their domain. Each category contains templates demonstrating domain-specific patterns, best practices, and integrations, reducing the need to build agents from scratch for common use cases.","intents":["Find pre-built agents for specific business domains","Discover best practices for domain-specific agent design","Reduce time to value by starting with production-ready templates","Learn agent patterns through example implementations"],"best_for":["Teams new to AI agents seeking domain-specific examples","Organizations building agents for specific industries (finance, healthcare, marketing)","Developers learning agent design patterns through templates"],"limitations":["Template quality varies; not all templates are equally production-ready or well-documented","Templates are static snapshots; they may not reflect latest best practices or API changes","Customization required for most templates; copy-paste usage without modification may not suit specific use cases","No built-in template versioning; updates to templates may break existing deployments"],"requires":["Access to awesome-openclaw-agents repository","Understanding of agent configuration and SOUL.md format","Domain knowledge to customize templates for specific use cases"],"input_types":["category filter","search query","agent metadata"],"output_types":["filtered agent templates","agent documentation","SOUL.md configurations"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":49,"verified":false,"data_access_risk":"high","permissions":["OpenClaw runtime or CrewClaw platform access","Basic markdown authoring capability","Understanding of agent role, constraints, and system prompt structure","JSON parsing capability in deployment tooling","agents.json file accessible in repository or via API","Understanding of registry schema (id, category, name, role, path, tier fields)","Understanding of agent tier definitions (Basic, Standard, Full)","agents.json registry with tier metadata","Assessment of use case complexity to select appropriate tier","GitHub account and familiarity with pull requests"],"failure_modes":["SOUL.md syntax is OpenClaw-specific; not portable to other agent frameworks without conversion","Complex conditional logic or dynamic behavior requires AGENTS.md extensions; pure markdown has limited expressiveness","No built-in version conflict resolution for concurrent agent edits","agents.json is static and requires manual updates when new agents are added; no real-time sync with filesystem","Registry schema is OpenClaw-specific; integration with non-OpenClaw systems requires custom mapping","No built-in versioning or deprecation tracking for agent templates","Tier classification is subjective; no formal criteria for tier assignment","Tier does not indicate performance characteristics or scalability; a Full agent may not be more performant than a Standard agent","Tier classification is static; agents do not automatically upgrade tiers as they mature","No guidance on tier migration; upgrading from Basic to Standard requires manual reconfiguration","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5598050015567767,"quality":0.5,"ecosystem":0.7000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.062Z","last_scraped_at":"2026-05-03T13:59:57.742Z","last_commit":"2026-05-01T08:31:26Z"},"community":{"stars":3217,"forks":527,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mergisi--awesome-openclaw-agents","compare_url":"https://unfragile.ai/compare?artifact=mergisi--awesome-openclaw-agents"}},"signature":"1b1SOrWpDfKH8Gjl6XxRR72zWM/xZITVIVg+et+rxA/H4376V8JdhQHrG2HHdaxPabTQE3iU836m+iWnR9EADQ==","signedAt":"2026-06-20T02:24:55.095Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mergisi--awesome-openclaw-agents","artifact":"https://unfragile.ai/mergisi--awesome-openclaw-agents","verify":"https://unfragile.ai/api/v1/verify?slug=mergisi--awesome-openclaw-agents","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"}}