{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_promptleo","slug":"promptleo","name":"PromptLeo","type":"product","url":"https://promptleo.com","page_url":"https://unfragile.ai/promptleo","categories":["prompt-engineering"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_promptleo__cap_0","uri":"capability://memory.knowledge.business.context.aware.agent.creation.with.knowledge.base.indexing","name":"business-context-aware agent creation with knowledge base indexing","description":"Enables users to define custom AI agents trained on organization-specific data sources (documents, databases, APIs) through a three-step workflow: define agent parameters, connect data sources, and deploy for team access. The system indexes and retrieves from ingested knowledge bases using an unspecified retrieval mechanism (likely RAG-based) to ground agent responses in business context rather than relying solely on foundation model training. Agents are stored as reusable templates that can be shared across departments and accessed via chat interface or API endpoints.","intents":["Create department-specific AI assistants that answer questions using our internal documentation and processes","Build customer-facing chatbots that reference our knowledge base without exposing proprietary data","Enable non-technical team members to deploy AI agents without writing code or managing infrastructure","Standardize AI interactions across teams by creating shared agent templates with consistent behavior"],"best_for":["Enterprise teams with GDPR/privacy requirements seeking on-premises or EU-hosted AI infrastructure","Organizations with siloed departments needing department-specific agents that can coordinate via shared knowledge","Business users without technical backgrounds who need to deploy AI without coding"],"limitations":["Knowledge base size limits unknown — no documentation of maximum ingestion capacity or indexing performance degradation","Retrieval mechanism unspecified — unclear whether RAG, fine-tuning, or hybrid approach is used, affecting accuracy and hallucination rates","Underlying LLM model(s) not disclosed — users cannot assess model capabilities, biases, or token limits before deployment","No multi-modal support mentioned — agents appear limited to text-based knowledge bases and queries","Data source format support unclear — specific file types (PDF, DOCX, CSV) and database protocols not documented"],"requires":["Free or paid PromptLeo account (freemium model available)","Access to data sources to be indexed (files, databases, APIs, or business systems)","For self-hosted deployment: infrastructure requirements unspecified in documentation","For API-based integration: API authentication method and rate limits not documented"],"input_types":["text documents (format support unspecified)","database connections (protocol/type unspecified)","API endpoints (authentication method unspecified)","file uploads (formats unspecified)"],"output_types":["conversational responses grounded in knowledge base","structured API responses (format unspecified)","chat widget embeddable on customer-facing websites"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_1","uri":"capability://automation.workflow.workflow.automation.from.conversational.interactions","name":"workflow automation from conversational interactions","description":"Converts one-time conversational interactions with AI agents into repeatable, reusable workflows that can be triggered by team members without re-prompting. The system captures the logic, data dependencies, and decision points from a conversation and abstracts them into a workflow template that can be parameterized and executed at scale. This enables teams to convert ad-hoc ChatGPT usage patterns into standardized, auditable processes with governance tracking.","intents":["Turn a successful customer support conversation into a repeatable workflow that support agents can trigger for similar issues","Capture the logic of a one-time data analysis task and make it executable by non-technical team members","Create standardized content generation workflows that maintain brand voice and quality standards across teams","Build approval workflows where AI-generated outputs are reviewed and refined before deployment"],"best_for":["Teams with repetitive AI-assisted tasks (content generation, customer support, data processing) seeking to standardize workflows","Organizations wanting to move beyond ad-hoc ChatGPT usage to auditable, governance-tracked AI processes","Non-technical business users who need to create automation without coding"],"limitations":["Workflow abstraction mechanism unspecified — unclear how conversational logic is extracted and parameterized into reusable templates","No mention of conditional branching, loops, or error handling — workflow complexity limits unknown","Trigger mechanisms not documented — unclear what events can initiate workflows (API calls, scheduled, manual, webhook)","State persistence unspecified — no documentation of how workflow state is managed across multi-step executions","Integration with external systems for workflow execution unclear — may require custom API development"],"requires":["PromptLeo account with workflow creation permissions","At least one configured agent with knowledge base or API connections","For complex workflows: understanding of workflow parameters and data mapping (technical knowledge may be required despite 'no-code' claims)"],"input_types":["conversational interaction logs from agent chats","parameterized inputs (variables, data fields)","trigger events (unspecified types)"],"output_types":["workflow execution results","audit logs tracking workflow runs and outputs","structured data outputs (format unspecified)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_10","uri":"capability://automation.workflow.freemium.onboarding.with.no.credit.card.required","name":"freemium onboarding with no credit card required","description":"Offers a free tier accessible without credit card, enabling individual users and small teams to experiment with agent creation, knowledge base indexing, and prompt testing before committing to paid plans. The free tier includes core features (agent creation, basic knowledge base, limited API calls) with usage limits. Upgrade to paid tiers is self-service with transparent pricing progression (though specific tier details are unclear). This lowers the barrier to entry for individual experimenters and small teams.","intents":["Try PromptLeo without financial commitment to evaluate if it meets our needs","Experiment with AI agents and prompt engineering without signing up for a paid plan","Build proof-of-concept agents before requesting budget approval for paid tiers","Enable individual team members to explore AI capabilities without organizational procurement"],"best_for":["Individual developers and prompt engineers evaluating the platform","Small teams with limited budgets seeking to experiment with AI agents","Organizations building internal business cases for AI adoption","Non-technical users wanting to learn prompt engineering without financial risk"],"limitations":["Free tier feature limits not documented — unclear what features are available and what usage limits apply","Pricing tier progression unclear — no documentation of what features unlock at each paid tier","Upgrade path not specified — unclear if free tier data/agents transfer to paid plans","Support level for free tier unknown — unclear if free users receive support or documentation access","Rate limits on free tier not documented — unclear what API rate limits or concurrent user limits apply","Data retention on free tier unclear — unknown if free tier data is deleted after inactivity"],"requires":["Email address for account creation (no credit card required)","No payment method required for free tier","For paid tiers: credit card or other payment method (payment methods unspecified)"],"input_types":["account creation information","agent configuration and knowledge base data","prompt testing inputs"],"output_types":["free tier access and features","usage metrics and limits","upgrade recommendations"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_2","uri":"capability://planning.reasoning.multi.model.comparative.prompt.testing.interface","name":"multi-model comparative prompt testing interface","description":"Provides a side-by-side testing interface where users can submit the same prompt to multiple AI models simultaneously and compare outputs, response times, and quality metrics. The platform abstracts away model-specific API authentication and formatting, allowing users to test prompt variations across different providers (OpenAI, Anthropic, etc.) without managing multiple API keys or SDKs. Results are displayed in a comparative dashboard enabling rapid iteration on prompt engineering without context switching between different AI platforms.","intents":["Evaluate which AI model produces the best output for a specific prompt before committing to a production integration","Test prompt variations across models to identify which phrasing works best for each provider's capabilities","Benchmark model performance (latency, cost, quality) for a specific use case before scaling","Optimize prompts for cost-efficiency by comparing token usage across models for the same task"],"best_for":["Product teams evaluating AI models for production deployment","Content creators and prompt engineers optimizing prompts across multiple model providers","Teams with budget constraints needing to compare cost-per-token across models","Organizations standardizing on specific models and needing evidence-based selection criteria"],"limitations":["Supported models not documented — unclear which providers (OpenAI, Anthropic, Cohere, etc.) are available for comparison","Comparison metrics not specified — unclear what quality metrics are displayed beyond response text (latency, token count, cost)","No A/B testing statistical significance — unclear if platform provides confidence intervals or sample size recommendations","Batch testing limitations unknown — maximum number of prompts or model combinations per test not documented","Cost attribution unclear — no documentation of how multi-model testing costs are tracked and attributed to users"],"requires":["PromptLeo account with testing/experimentation permissions","API keys or credentials for models to be tested (authentication method unspecified)","Sufficient account credits or subscription tier to cover multi-model API calls"],"input_types":["text prompts","prompt parameters/variables","model selection (specific models unspecified)"],"output_types":["model responses (text)","latency metrics","token usage counts","cost estimates (currency/format unspecified)","comparative analysis dashboard"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_3","uri":"capability://text.generation.language.prompt.template.library.and.onboarding.acceleration","name":"prompt template library and onboarding acceleration","description":"Provides pre-built prompt templates and libraries organized by use case (customer support, content generation, data analysis, etc.) that users can clone, customize, and deploy without starting from scratch. Templates include best-practice prompt structures, variable placeholders, and example outputs, reducing the learning curve for users unfamiliar with effective prompt engineering. Templates can be shared across teams and versioned, enabling organizations to build internal libraries of proven prompts.","intents":["Get started with AI agents quickly using proven prompt templates instead of writing prompts from scratch","Learn prompt engineering best practices by studying well-structured templates and their outputs","Standardize prompt quality across teams by using shared, vetted templates","Reduce onboarding time for new team members by providing ready-to-use prompt starting points"],"best_for":["Teams new to prompt engineering seeking to accelerate adoption without steep learning curves","Organizations standardizing AI workflows and needing shared prompt libraries","Non-technical users who need guidance on effective prompt structure","Enterprises building internal prompt standards and best practices"],"limitations":["Template coverage unknown — unclear which use cases and industries are covered by built-in templates","Customization depth unclear — templates may be too generic for specialized domains or may require significant modification","No mention of template versioning or change tracking — unclear how template updates are managed across teams","Community contribution mechanism not documented — unclear if users can contribute or share custom templates","Template quality assurance not specified — no documentation of how templates are tested or validated"],"requires":["PromptLeo account (freemium tier available)","Basic understanding of the use case to select appropriate template","For customization: ability to edit prompt text and variables (no technical knowledge required)"],"input_types":["template selection from library","customization parameters (text, variables)","data inputs for template execution"],"output_types":["customized prompt templates","example outputs from templates","template documentation and best practices"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_4","uri":"capability://automation.workflow.team.collaboration.with.role.based.access.control","name":"team collaboration with role-based access control","description":"Enables multiple team members to collaborate on agents, workflows, and knowledge bases with granular role-based permissions (viewer, editor, admin, etc.). The system tracks who created/modified agents and workflows, maintains audit logs of changes, and allows teams to share knowledge bases and agent templates across departments. Collaboration features include shared workspaces, permission inheritance, and team-level governance settings.","intents":["Enable multiple team members to build and refine agents without overwriting each other's work","Maintain audit trails of who changed what in agents and workflows for compliance and governance","Share proven agents and workflows across departments without duplicating effort","Enforce organizational policies on AI usage through role-based access controls"],"best_for":["Enterprise teams with multiple departments needing to collaborate on AI agents","Organizations with compliance requirements (GDPR, SOC 2) needing audit trails and access controls","Teams wanting to prevent unauthorized changes to production agents and workflows","Large organizations building internal AI platforms with governance requirements"],"limitations":["Role definitions not documented — unclear what permissions each role (viewer, editor, admin) has","Audit log retention not specified — unclear how long audit trails are maintained or if they can be exported","Permission inheritance rules unclear — unclear how permissions cascade when agents are shared across departments","Concurrent editing not mentioned — unclear if multiple users can edit the same agent simultaneously or if locking is required","Team size limits unknown — no documentation of maximum team members per workspace or organization"],"requires":["PromptLeo account with team/organization management permissions","Team members with PromptLeo accounts (authentication method unspecified)","Appropriate subscription tier for team collaboration features (tier requirements unclear)"],"input_types":["user invitations and role assignments","permission configurations","agent/workflow sharing requests"],"output_types":["audit logs of changes","access control configurations","shared agent/workflow templates","team member activity reports"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_5","uri":"capability://tool.use.integration.customer.facing.chat.widget.deployment","name":"customer-facing chat widget deployment","description":"Enables deployment of trained agents as embeddable chat widgets on customer-facing websites or applications without requiring custom frontend development. The platform handles widget styling, conversation state management, and integration with the backend agent infrastructure. Widgets can be customized with branding, configured with specific agents/knowledge bases, and tracked for usage analytics. Deployment is handled through a simple embed code or API integration.","intents":["Deploy a customer support chatbot on our website without building custom chat UI","Provide customers with AI-powered product documentation search through an embedded widget","Collect customer feedback and questions through a branded chat interface","Reduce support ticket volume by enabling customers to self-serve through an AI chatbot"],"best_for":["Customer support teams wanting to deploy AI chatbots without frontend development","Product teams adding AI-powered help features to their applications","Marketing teams creating interactive customer engagement experiences","Organizations with limited engineering resources needing quick chatbot deployment"],"limitations":["Widget customization depth unknown — unclear what styling options and branding controls are available","Deployment method unspecified — unclear if deployment is via embed code, iframe, or API integration","Analytics capabilities unclear — unknown what metrics are tracked (conversation count, resolution rate, user satisfaction)","Multi-language support not mentioned — unclear if widgets support localization","Mobile responsiveness not documented — unclear how widgets render on mobile devices","Rate limiting and abuse prevention not specified — no documentation of how to prevent chatbot spam or misuse"],"requires":["PromptLeo account with agent/widget deployment permissions","Configured agent with knowledge base or API connections","Website or application where widget will be embedded (technical requirements unspecified)","For custom styling: CSS knowledge or design resources (may require technical support)"],"input_types":["agent selection for widget","widget configuration (branding, behavior)","conversation inputs from end users"],"output_types":["embeddable widget code","conversation transcripts","usage analytics and metrics","customer feedback and ratings"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_6","uri":"capability://tool.use.integration.api.based.agent.access.and.integration","name":"api-based agent access and integration","description":"Exposes trained agents as API endpoints that can be called from external applications, workflows, or services. The API abstracts away the underlying agent infrastructure, allowing developers to integrate AI capabilities into existing systems without managing model APIs directly. API endpoints support standard HTTP methods, authentication (method unspecified), and structured request/response formats. Rate limiting and usage tracking are built-in for governance.","intents":["Integrate a trained agent into our existing application backend without managing OpenAI/Anthropic APIs directly","Build custom workflows that call multiple agents via API and combine their outputs","Enable third-party applications to access our organization's AI agents through authenticated API endpoints","Track and meter API usage for cost allocation and governance"],"best_for":["Developers integrating AI agents into existing applications or microservices","Teams building custom workflows that orchestrate multiple agents","Organizations exposing AI capabilities to third-party developers or partners","Backend systems needing AI capabilities without direct LLM API management"],"limitations":["API documentation not provided — endpoint structure, authentication method, and response formats unknown","Rate limiting not specified — unclear what request limits apply per user/tier","Error handling not documented — unclear what error codes and messages are returned","Batch request support unknown — unclear if API supports batch processing or only single requests","Response latency not specified — no SLA or performance benchmarks provided","Webhook support not mentioned — unclear if asynchronous callbacks are supported for long-running requests"],"requires":["PromptLeo account with API access permissions","Configured agent deployed and ready for API access","API key or authentication credentials (format unspecified)","Developer environment with HTTP client library (language-agnostic)"],"input_types":["HTTP requests with prompt/query parameters","structured JSON payloads (schema unspecified)","authentication headers (format unspecified)"],"output_types":["JSON responses with agent outputs","structured data (format unspecified)","error responses with status codes"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_7","uri":"capability://data.processing.analysis.usage.analytics.and.governance.tracking","name":"usage analytics and governance tracking","description":"Tracks and reports on agent usage, workflow execution, and API calls across the organization with metrics including conversation count, token usage, cost attribution, and user activity. Analytics dashboard provides visibility into which agents/workflows are being used, by whom, and at what cost. Governance features enable administrators to set usage quotas, monitor compliance, and identify cost optimization opportunities. Data is aggregated at team, department, and organization levels.","intents":["Monitor AI spending across teams and identify cost optimization opportunities","Track which agents and workflows are most valuable based on usage patterns","Enforce usage quotas and prevent runaway costs from over-usage","Generate compliance reports showing who accessed which agents and when"],"best_for":["Finance and operations teams managing AI spending across the organization","Administrators enforcing governance policies and usage quotas","Teams optimizing AI workflows based on usage and cost data","Organizations with compliance requirements needing detailed usage audits"],"limitations":["Metrics available not fully specified — unclear what metrics beyond conversation count and token usage are tracked","Cost attribution method unclear — unclear how multi-model usage costs are calculated and attributed","Quota enforcement mechanism not documented — unclear how quotas are enforced (hard limits, warnings, etc.)","Data retention policy unknown — unclear how long analytics data is retained","Export capabilities not mentioned — unclear if analytics can be exported for external reporting","Real-time vs. batch reporting unclear — unknown if analytics are updated in real-time or on a schedule"],"requires":["PromptLeo account with analytics/admin permissions","Active agents and workflows generating usage data","Appropriate subscription tier for analytics features (tier requirements unclear)"],"input_types":["agent/workflow usage events","API call logs","user activity logs"],"output_types":["usage dashboards and reports","cost attribution reports","compliance audit logs","quota and governance configurations"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_8","uri":"capability://tool.use.integration.model.context.protocol.mcp.tool.integration","name":"model context protocol (mcp) tool integration","description":"Integrates with the Model Context Protocol (MCP) standard to connect agents with external tools and services through a standardized interface. MCP enables agents to call functions, query databases, invoke APIs, and interact with business systems without custom integration code. The platform handles MCP protocol negotiation, tool discovery, and error handling, allowing agents to access a growing ecosystem of MCP-compatible tools.","intents":["Enable agents to query our database or CRM without custom API development","Connect agents to external services (Slack, Salesforce, Jira) through standard MCP protocol","Build agents that can take actions in business systems (create tickets, update records) not just answer questions","Leverage community-built MCP tools without writing integration code"],"best_for":["Developers building agents that need to interact with multiple business systems","Organizations wanting to standardize tool integration through MCP instead of custom APIs","Teams leveraging community-built MCP tools to extend agent capabilities","Enterprises with complex tool ecosystems needing a unified integration layer"],"limitations":["Supported MCP tools not documented — unclear which tools/services have MCP implementations available","MCP version not specified — unclear which version of the MCP standard is supported","Custom MCP tool development not mentioned — unclear if users can build custom MCP tools","Tool discovery mechanism not documented — unclear how agents discover and access available tools","Error handling and fallback behavior not specified — unclear how agents handle tool failures","Tool authentication not documented — unclear how credentials for MCP tools are managed"],"requires":["PromptLeo account with tool integration permissions","Configured agent ready to use tools","MCP-compatible tools or services to integrate (MCP implementations vary by tool)","For custom tools: understanding of MCP protocol (technical knowledge required)"],"input_types":["MCP tool specifications","tool configuration parameters","agent requests for tool invocation"],"output_types":["tool execution results","structured data from tool responses","error messages and fallback responses"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_promptleo__cap_9","uri":"capability://safety.moderation.gdpr.compliant.data.hosting.and.self.hosted.deployment.options","name":"gdpr-compliant data hosting and self-hosted deployment options","description":"Offers data hosting in Germany with claimed GDPR compliance, meeting EU data residency and privacy requirements. Additionally supports self-hosted deployment for organizations requiring complete data control and air-gapped environments. The platform abstracts infrastructure management, allowing organizations to choose between cloud-hosted (EU) or self-hosted deployments without changing application code. Data processing agreements and compliance documentation are available for enterprise customers.","intents":["Deploy AI agents in EU-compliant infrastructure without moving data outside Europe","Maintain complete data control by self-hosting PromptLeo infrastructure","Meet GDPR requirements for data residency and processing agreements","Support air-gapped deployments for highly sensitive or regulated environments"],"best_for":["European organizations with GDPR compliance requirements","Enterprises with strict data residency requirements (financial services, healthcare, government)","Organizations handling sensitive customer data requiring self-hosted infrastructure","Teams in regulated industries needing complete data control and audit trails"],"limitations":["Self-hosted infrastructure requirements not documented — unclear what hardware, OS, and dependencies are needed","Deployment complexity unknown — unclear if self-hosting requires DevOps expertise or if managed deployment is available","Data processing agreement (DPA) availability unclear — unclear if DPAs are available for all tiers or only enterprise","Compliance certifications not specified — unclear if SOC 2, ISO 27001, or other certifications are held","Data deletion and retention policies not documented — unclear how data is handled upon account deletion","Backup and disaster recovery not specified — unclear what RTO/RPO guarantees are provided"],"requires":["PromptLeo account (cloud-hosted or self-hosted)","For cloud-hosted: acceptance of EU data residency terms","For self-hosted: infrastructure (hardware, OS, network) meeting unspecified requirements","For compliance: legal review of data processing agreements (available for enterprise)"],"input_types":["deployment configuration (cloud vs. self-hosted)","infrastructure specifications (for self-hosted)","data processing agreement requirements"],"output_types":["deployed agent infrastructure","compliance documentation","data processing agreements","audit logs and compliance reports"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Free or paid PromptLeo account (freemium model available)","Access to data sources to be indexed (files, databases, APIs, or business systems)","For self-hosted deployment: infrastructure requirements unspecified in documentation","For API-based integration: API authentication method and rate limits not documented","PromptLeo account with workflow creation permissions","At least one configured agent with knowledge base or API connections","For complex workflows: understanding of workflow parameters and data mapping (technical knowledge may be required despite 'no-code' claims)","Email address for account creation (no credit card required)","No payment method required for free tier","For paid tiers: credit card or other payment method (payment methods unspecified)"],"failure_modes":["Knowledge base size limits unknown — no documentation of maximum ingestion capacity or indexing performance degradation","Retrieval mechanism unspecified — unclear whether RAG, fine-tuning, or hybrid approach is used, affecting accuracy and hallucination rates","Underlying LLM model(s) not disclosed — users cannot assess model capabilities, biases, or token limits before deployment","No multi-modal support mentioned — agents appear limited to text-based knowledge bases and queries","Data source format support unclear — specific file types (PDF, DOCX, CSV) and database protocols not documented","Workflow abstraction mechanism unspecified — unclear how conversational logic is extracted and parameterized into reusable templates","No mention of conditional branching, loops, or error handling — workflow complexity limits unknown","Trigger mechanisms not documented — unclear what events can initiate workflows (API calls, scheduled, manual, webhook)","State persistence unspecified — no documentation of how workflow state is managed across multi-step executions","Integration with external systems for workflow execution unclear — may require custom API development","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":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:32.438Z","last_scraped_at":"2026-04-05T13:23:42.560Z","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=promptleo","compare_url":"https://unfragile.ai/compare?artifact=promptleo"}},"signature":"d6V94Q6ce603jP/x4H3BRRAJFZwLk5HIJ/9LBx9eaVLf0EU3NBlbaZhnE3r6CzfSw1vrGDvIl8Sd1W7pi503Bg==","signedAt":"2026-06-22T19:15:10.124Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/promptleo","artifact":"https://unfragile.ai/promptleo","verify":"https://unfragile.ai/api/v1/verify?slug=promptleo","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"}}