{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-devopsgpt","slug":"devopsgpt","name":"DevOpsGPT","type":"agent","url":"https://github.com/kuafuai/DevOpsGPT","page_url":"https://unfragile.ai/devopsgpt","categories":["ai-agents"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-devopsgpt__cap_0","uri":"capability://planning.reasoning.natural.language.to.requirements.clarification.with.iterative.refinement","name":"natural language to requirements clarification with iterative refinement","description":"Engages users in a multi-turn dialogue to progressively clarify and refine business requirements before code generation. Uses LLM-driven conversation flows to extract ambiguities, validate assumptions, and produce structured requirement specifications. The system maintains conversation context across turns and generates structured outputs (PRDs, interface specs) from unstructured natural language inputs through prompt-based extraction patterns.","intents":["I want to describe what I need built in plain English and have the system ask clarifying questions","I need to convert vague business requirements into detailed technical specifications automatically","I want to reduce back-and-forth communication with developers by having AI extract all necessary details upfront"],"best_for":["Product managers and non-technical stakeholders defining features","Teams wanting to reduce requirements-gathering overhead","Organizations bridging business and technical communication gaps"],"limitations":["Clarification quality depends on LLM provider capability; may miss domain-specific edge cases","Requires sufficient initial context from user — extremely vague inputs may loop indefinitely","No built-in domain knowledge — generic clarification patterns may not suit specialized industries"],"requires":["LLM API access (OpenAI, Azure OpenAI, or compatible provider)","Backend service running with task processing system","Frontend interface for multi-turn conversation"],"input_types":["natural language text (requirements description)","conversation history (previous clarifications)"],"output_types":["structured requirement documents (PRD format)","interface specifications","clarification questions"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_1","uri":"capability://text.generation.language.automated.prd.and.interface.documentation.generation.from.requirements","name":"automated prd and interface documentation generation from requirements","description":"Transforms clarified requirements into formal Product Requirements Documents (PRDs) and interface specifications using LLM-based document generation. Applies structured prompts to convert natural language requirements into standardized documentation formats with sections for features, acceptance criteria, API contracts, and UI mockups. Integrates with the task processing system to maintain consistency between generated documentation and subsequent code generation.","intents":["I want to automatically generate formal PRD documents from requirements without manual writing","I need interface specifications and API contracts generated from requirements to guide developers","I want to ensure documentation stays synchronized with actual requirements throughout development"],"best_for":["Teams that need formal documentation artifacts for compliance or handoff","Organizations standardizing on documentation formats across projects","Development teams that want documentation to drive code generation"],"limitations":["Generated documentation may require manual review and refinement for accuracy","Template-based generation may not capture domain-specific documentation needs","No version control integration — documentation updates require manual synchronization"],"requires":["LLM API access with sufficient context window (4K+ tokens recommended)","Clarified requirements as structured input","Backend document generation service"],"input_types":["structured requirements (from clarification stage)","project metadata (name, scope, tech stack)"],"output_types":["PRD documents (markdown or structured format)","API specifications (OpenAPI/Swagger format)","UI/UX interface specifications","acceptance criteria documents"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_10","uri":"capability://tool.use.integration.devops.tool.integration.and.infrastructure.automation","name":"devops tool integration and infrastructure automation","description":"Integrates with external DevOps tools and infrastructure platforms to automate deployment, monitoring, and infrastructure provisioning. The DevOps Integration system (per DeepWiki) provides connectors to Git repositories, CI/CD systems, container registries, and cloud platforms. Enables generated code to be deployed to various infrastructure targets (Kubernetes, Docker, cloud VMs) through standardized integration points.","intents":["I want generated code deployed to my Kubernetes cluster automatically","I need Docker containers built and pushed to my registry as part of the deployment","I want infrastructure provisioning (databases, APIs) automated alongside code deployment"],"best_for":["Organizations with complex DevOps pipelines and infrastructure","Teams practicing infrastructure-as-code and GitOps","Cloud-native deployments requiring container and orchestration integration"],"limitations":["DevOps integration details not fully documented; may support limited platforms","Requires pre-configured infrastructure and credentials for each target","No built-in infrastructure provisioning — assumes infrastructure already exists","Error handling for infrastructure failures may be limited"],"requires":["DevOps Integration backend service","Credentials for target platforms (Git, Docker, Kubernetes, cloud providers)","Pre-configured infrastructure (clusters, registries, repositories)","Deployment configuration files (Dockerfile, Kubernetes manifests, etc.)"],"input_types":["generated source code","deployment target specification","infrastructure configuration"],"output_types":["deployment status","container image references","infrastructure provisioning logs","deployment URLs"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_11","uri":"capability://automation.workflow.web.based.interactive.ui.with.real.time.task.monitoring","name":"web-based interactive ui with real-time task monitoring","description":"Provides a responsive web interface for interacting with the DevOpsGPT platform, including requirement input, project management, code review, and real-time task progress monitoring. The Frontend Components (per DeepWiki) include HTML/JavaScript UI with WebSocket or polling-based real-time updates, interactive code editors, and project dashboards. The Core Frontend Logic (coder.js) manages the client-side state and orchestrates interactions with the backend API.","intents":["I want a user-friendly web interface to describe requirements and monitor code generation","I need to see real-time progress updates as the system generates code","I want to review and edit generated code directly in the browser"],"best_for":["Non-technical users wanting to interact with the system without CLI","Teams wanting real-time visibility into development workflows","Organizations deploying DevOpsGPT as a web service"],"limitations":["Web UI may have performance limitations with large codebases or long specifications","Real-time updates require WebSocket support; polling-based fallback may have latency","Code editor is browser-based; lacks advanced IDE features (debugging, profiling)","No offline mode — requires continuous connection to backend"],"requires":["Modern web browser (Chrome, Firefox, Safari, Edge)","Backend API server running","WebSocket support (or HTTP polling fallback)","JavaScript enabled in browser"],"input_types":["text input (requirements, project metadata)","file uploads (existing code, specifications)","user interactions (clicks, form submissions)"],"output_types":["rendered HTML UI","real-time task status updates","code editor content","project dashboard"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_12","uri":"capability://text.generation.language.prompt.engineering.and.structured.output.formatting.for.llm.interactions","name":"prompt engineering and structured output formatting for llm interactions","description":"Manages a library of optimized prompts and structured output formatting templates for consistent LLM interactions across the platform. The Prompt System (per DeepWiki LLM Integration System) structures interactions with LLMs to extract specific outputs (code, specifications, task lists) in consistent formats. Uses prompt templates with variable substitution to adapt prompts to different contexts (languages, domains, requirements).","intents":["I want consistent, high-quality outputs from LLM calls across different stages of the workflow","I need to customize prompts for specific domains or programming languages","I want to optimize prompts for cost and latency without sacrificing quality"],"best_for":["Teams wanting to fine-tune LLM behavior for their specific use cases","Organizations managing multiple LLM-based workflows with different requirements","Projects requiring domain-specific code generation (e.g., financial systems, medical software)"],"limitations":["Prompt quality is manual and requires domain expertise to optimize","Prompt changes require testing and validation; no automated prompt optimization","Structured output formatting may fail with some LLM providers or models","No version control for prompts — difficult to track changes and rollback"],"requires":["Prompt template library (stored in code or database)","LLM API access","Template variable definitions","Output validation logic"],"input_types":["prompt templates (text with variables)","context variables (requirements, code, specifications)","output format specification"],"output_types":["formatted prompts (ready for LLM)","structured LLM outputs (code, JSON, markdown)"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_2","uri":"capability://code.generation.editing.task.decomposition.and.multi.step.code.generation.with.llm.orchestration","name":"task decomposition and multi-step code generation with llm orchestration","description":"Breaks down complex requirements into granular implementation tasks and generates code for each task using an LLM-driven orchestration system. The Task Processing System (per DeepWiki) manages the conversion workflow, using prompts to decompose features into subtasks, assign implementation order, and generate code incrementally. Supports multiple programming languages through provider-agnostic LLM calls and maintains task state across generation steps.","intents":["I want complex features automatically broken down into smaller, manageable coding tasks","I need code generated incrementally with proper dependency ordering","I want to generate code for multiple components (backend, frontend, database) from a single specification"],"best_for":["Teams building full-stack applications from specifications","Projects requiring multi-language code generation (Python backend + React frontend)","Organizations wanting to automate the task breakdown and assignment process"],"limitations":["Generated task decomposition may not match optimal architectural patterns for the domain","Code generation quality varies by language and complexity; generated code requires review","No built-in understanding of existing codebase — cannot refactor or extend legacy code intelligently","Task dependencies are inferred from prompts; complex circular dependencies may not be detected"],"requires":["LLM API access with function calling or structured output support","Task Processing System backend service","Specification documents (PRD, API specs) as input"],"input_types":["structured specifications (PRD, interface specs)","technology stack definition","existing codebase context (optional)"],"output_types":["task list with dependencies","generated source code files (multiple languages)","implementation plan with ordering"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_3","uri":"capability://code.generation.editing.automated.code.verification.and.issue.fixing.with.iterative.refinement","name":"automated code verification and issue fixing with iterative refinement","description":"Validates generated code against specifications and automatically fixes identified issues through iterative LLM-driven refinement cycles. The Verification stage (per DeepWiki workflow) uses prompts to check code against requirements, identify bugs, style violations, and missing implementations, then regenerates problematic sections. Integrates with the LLM Integration System to support multiple provider backends and maintains verification state across iterations.","intents":["I want generated code automatically checked for correctness against the specification","I need bugs and issues in generated code fixed without manual intervention","I want to ensure generated code meets quality standards before deployment"],"best_for":["Teams wanting to reduce manual code review overhead","Projects with strict quality requirements before deployment","Organizations automating the entire development pipeline"],"limitations":["Verification is specification-based; cannot detect logical errors not covered by specs","Iterative fixing may loop indefinitely on complex issues; requires iteration limits","No integration with static analysis tools (linters, type checkers) — relies on LLM judgment","Cannot verify runtime behavior or performance characteristics"],"requires":["LLM API access with code analysis capability","Generated source code files","Specification documents for validation","Backend verification service"],"input_types":["generated source code","original specifications","test cases or acceptance criteria"],"output_types":["verification report (issues found)","corrected source code","fix summary"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_4","uri":"capability://tool.use.integration.multi.provider.llm.integration.with.api.key.rotation.and.fallback","name":"multi-provider llm integration with api key rotation and fallback","description":"Provides a flexible abstraction layer for LLM provider integration supporting OpenAI, Azure OpenAI, and compatible APIs with automatic API key rotation and fallback mechanisms. The LLM Integration System (per DeepWiki) manages provider selection, handles authentication, rotates keys to prevent rate limiting, and switches between real API calls and mock responses for testing. Implements a provider-agnostic prompt interface that works across different LLM backends.","intents":["I want to use multiple LLM providers without rewriting code for each provider's API","I need automatic fallback when one LLM provider is rate-limited or unavailable","I want to test the system with mock LLM responses without incurring API costs"],"best_for":["Teams wanting to avoid vendor lock-in with a single LLM provider","Organizations managing multiple LLM API keys across projects","Development teams needing cost-effective testing without API calls"],"limitations":["Provider abstraction may hide provider-specific capabilities (e.g., vision, function calling differences)","API key rotation adds latency (~50-100ms per rotation) and complexity","Mock mode responses are static and don't reflect actual LLM behavior variations","No built-in cost tracking or quota management across providers"],"requires":["API keys for at least one LLM provider (OpenAI or Azure OpenAI)","Backend service with LLM Integration System","Python 3.8+ runtime"],"input_types":["prompts (text)","provider configuration","API keys"],"output_types":["LLM responses (text or structured)","provider metadata (model used, tokens consumed)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_5","uri":"capability://automation.workflow.automated.code.deployment.with.ci.cd.pipeline.triggering","name":"automated code deployment with ci/cd pipeline triggering","description":"Submits generated code to version control repositories and automatically triggers CI/CD pipelines for testing and deployment. The Deployment stage (per DeepWiki workflow) integrates with Git repositories and CI/CD systems (GitHub Actions, GitLab CI, etc.) to commit code, create pull requests, and initiate automated testing. Maintains deployment state and provides feedback on pipeline execution status.","intents":["I want generated code automatically committed to Git without manual push","I need CI/CD pipelines triggered automatically after code generation","I want to deploy generated code to production through automated pipelines"],"best_for":["Teams with established CI/CD pipelines wanting full automation","Organizations practicing continuous deployment","Projects where code generation is part of the deployment workflow"],"limitations":["Requires pre-configured CI/CD pipelines; cannot create pipelines automatically","No rollback mechanism if deployment fails — relies on CI/CD system's rollback","Git credentials must be securely stored and rotated","Cannot handle complex deployment scenarios (blue-green, canary) — delegates to CI/CD"],"requires":["Git repository access (GitHub, GitLab, Gitea, etc.)","Git credentials (SSH key or personal access token)","Pre-configured CI/CD pipeline in the repository","Backend deployment service"],"input_types":["generated source code","repository configuration","deployment target specification"],"output_types":["Git commit hash","pull request URL","CI/CD pipeline execution status","deployment logs"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_6","uri":"capability://automation.workflow.application.lifecycle.management.with.project.state.persistence","name":"application lifecycle management with project state persistence","description":"Manages the complete lifecycle of generated applications including project creation, state tracking, version history, and application metadata storage. The Application Management Interface (per DeepWiki) provides CRUD operations for applications, persists project state in a database (SQLite backend/app.db), and maintains version history of generated artifacts. Integrates with the user management system to support multi-tenant access control.","intents":["I want to create and manage multiple projects in the system","I need to track the history of generated code and specifications for each project","I want to access previously generated applications and continue development"],"best_for":["Teams managing multiple concurrent development projects","Organizations needing project history and audit trails","Multi-tenant SaaS deployments of DevOpsGPT"],"limitations":["SQLite backend suitable for single-instance deployments; scales poorly for distributed systems","No built-in backup mechanism — requires external database backups","Version history is append-only; no branching or merging of project versions","Metadata storage is limited to application name, description, and timestamps"],"requires":["Backend service with application management controllers","SQLite database (backend/app.db)","User authentication system","Python 3.8+ runtime"],"input_types":["project metadata (name, description, tech stack)","user/tenant context","generated artifacts (code, specs)"],"output_types":["project ID","version history","application metadata","artifact references"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_7","uri":"capability://safety.moderation.multi.tenant.user.and.access.control.management","name":"multi-tenant user and access control management","description":"Manages user authentication, authorization, and multi-tenant isolation with role-based access control (RBAC). The User and Tenant Management system (per DeepWiki) handles user registration, login, tenant creation, and permission enforcement across the platform. Integrates with the application management system to ensure users can only access their own projects and applications.","intents":["I want to set up multiple teams/organizations using the same DevOpsGPT instance","I need to control which users can access which projects","I want to manage user roles and permissions across the platform"],"best_for":["SaaS deployments of DevOpsGPT serving multiple organizations","Enterprise deployments requiring strict access control","Teams wanting to isolate projects by user or organization"],"limitations":["RBAC implementation details not fully documented; may have limited role granularity","No built-in SSO/SAML integration — requires custom implementation","Tenant isolation is logical (database-level) not physical; shared database backend","No audit logging of user actions — cannot track who made what changes"],"requires":["Backend user management service","Database with user and tenant tables","Session management (cookies or JWT tokens)","Frontend authentication UI"],"input_types":["user credentials (username/password)","tenant configuration","role assignments"],"output_types":["authentication tokens","user profile data","access control decisions"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_8","uri":"capability://automation.workflow.task.execution.and.background.job.scheduling.with.state.tracking","name":"task execution and background job scheduling with state tracking","description":"Orchestrates asynchronous execution of long-running development tasks (code generation, verification, deployment) using a background job scheduler with state tracking and progress monitoring. The Background Tasks and Scheduling system (per DeepWiki) manages task queues, tracks execution state (pending, running, completed, failed), and provides progress updates to the frontend. Supports task retries and error handling with detailed execution logs.","intents":["I want long-running code generation tasks to execute asynchronously without blocking the UI","I need to monitor progress of multi-step development workflows","I want failed tasks to retry automatically with exponential backoff"],"best_for":["Web-based deployments where UI responsiveness is critical","Complex workflows with multiple sequential or parallel tasks","Systems requiring detailed execution logs and audit trails"],"limitations":["Background scheduler implementation details not documented; may lack distributed task support","No built-in task persistence across service restarts — in-memory queues may lose tasks","Retry logic may not handle all failure modes (e.g., partial code generation)","Progress tracking is coarse-grained; no per-subtask progress visibility"],"requires":["Backend task scheduling service","Job queue (in-memory or external like Redis)","Database for task state persistence","WebSocket or polling mechanism for frontend updates"],"input_types":["task definition (type, parameters)","user context","specification inputs"],"output_types":["task ID","execution status (pending/running/completed/failed)","progress percentage","execution logs","result artifacts"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-devopsgpt__cap_9","uri":"capability://text.generation.language.internationalization.i18n.with.multi.language.ui.and.backend.support","name":"internationalization (i18n) with multi-language ui and backend support","description":"Provides comprehensive internationalization support for both frontend and backend components, enabling the platform to serve users in multiple languages. The i18n system (per DeepWiki) manages language-specific strings, date/time formatting, and locale-specific behavior across the application. Supports dynamic language switching without page reload and maintains language preferences per user.","intents":["I want to use DevOpsGPT in my native language (Chinese, Japanese, English, etc.)","I need the UI and generated documentation to respect my language preference","I want to deploy DevOpsGPT to international teams with different language requirements"],"best_for":["Global teams with non-English speakers","SaaS deployments targeting international markets","Organizations wanting to localize generated documentation"],"limitations":["i18n implementation is UI-focused; generated code and documentation may not be fully localized","Language support is limited to pre-configured languages (English, Chinese, Japanese documented)","No automatic translation of user-generated content (requirements, specifications)","Date/time and number formatting may not cover all locales"],"requires":["Frontend i18n library (likely i18next or similar)","Backend i18n service","Language resource files (JSON or YAML)","User language preference storage"],"input_types":["language code (en, zh, ja, etc.)","user locale preferences"],"output_types":["localized UI strings","locale-specific formatting","translated documentation"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"high","permissions":["LLM API access (OpenAI, Azure OpenAI, or compatible provider)","Backend service running with task processing system","Frontend interface for multi-turn conversation","LLM API access with sufficient context window (4K+ tokens recommended)","Clarified requirements as structured input","Backend document generation service","DevOps Integration backend service","Credentials for target platforms (Git, Docker, Kubernetes, cloud providers)","Pre-configured infrastructure (clusters, registries, repositories)","Deployment configuration files (Dockerfile, Kubernetes manifests, etc.)"],"failure_modes":["Clarification quality depends on LLM provider capability; may miss domain-specific edge cases","Requires sufficient initial context from user — extremely vague inputs may loop indefinitely","No built-in domain knowledge — generic clarification patterns may not suit specialized industries","Generated documentation may require manual review and refinement for accuracy","Template-based generation may not capture domain-specific documentation needs","No version control integration — documentation updates require manual synchronization","DevOps integration details not fully documented; may support limited platforms","Requires pre-configured infrastructure and credentials for each target","No built-in infrastructure provisioning — assumes infrastructure already exists","Error handling for infrastructure failures may be limited","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.35,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"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":"2026-06-17T09:51:03.038Z","last_scraped_at":"2026-05-03T14:00:10.321Z","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=devopsgpt","compare_url":"https://unfragile.ai/compare?artifact=devopsgpt"}},"signature":"jaB8KkAA59U28reoSsnNfKhYN5M9rMCjCm6jACkonPiFFhUXGZ/bpi3gyerFfv8bS9J4e1LIKj2rZ5uVQUGXBg==","signedAt":"2026-07-08T06:15:49.688Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/devopsgpt","artifact":"https://unfragile.ai/devopsgpt","verify":"https://unfragile.ai/api/v1/verify?slug=devopsgpt","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"}}