{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-taxy-ai","slug":"taxy-ai","name":"Taxy AI","type":"extension","url":"https://github.com/TaxyAI/browser-extension","page_url":"https://unfragile.ai/taxy-ai","categories":["automation"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-taxy-ai__cap_0","uri":"capability://planning.reasoning.natural.language.to.browser.action.interpretation","name":"natural language to browser action interpretation","description":"Converts plain English task descriptions into executable browser actions by sending simplified DOM state and user instructions to OpenAI's GPT models, which determine the next action (click, form fill, navigation) in a multi-step action cycle. The extension maintains a 50-action limit per task and uses the LLM's reasoning to map user intent to specific DOM elements and interactions.","intents":["I want to automate a repetitive web task without writing code","I need to execute a multi-step browser workflow by describing it in English","I want the system to figure out which button to click or form field to fill based on my instructions"],"best_for":["Non-technical users automating personal web workflows","QA testers creating automated test scenarios without Selenium/Playwright knowledge","Business users building RPA workflows for SaaS applications"],"limitations":["Limited to 50 sequential actions per task — complex workflows may exceed this threshold","Requires OpenAI API key and active internet connection for LLM inference","Cannot handle JavaScript-heavy SPAs that require complex state management beyond DOM observation","No built-in error recovery — if an action fails, the task terminates rather than attempting alternatives"],"requires":["Chrome browser (Manifest V3 compatible)","OpenAI API key with GPT-4 or GPT-3.5-turbo access","Active internet connection for API calls to OpenAI"],"input_types":["natural language text (task description)","DOM state (simplified HTML structure)"],"output_types":["structured action objects (click, setValue, navigate)","task completion status with action history"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_1","uri":"capability://data.processing.analysis.dom.extraction.and.simplification.for.token.efficiency","name":"dom extraction and simplification for token efficiency","description":"The content script extracts the full webpage DOM and applies simplification heuristics to reduce token count before sending to the LLM, focusing on interactive elements (buttons, inputs, links) while removing styling, scripts, and non-interactive content. This preprocessing step runs in the page context and communicates results back to the background service worker via Chrome's message passing API.","intents":["I need to reduce API costs by minimizing tokens sent to the LLM per action","I want the system to focus on actionable elements rather than page clutter","I need faster LLM response times by reducing context size"],"best_for":["Developers optimizing browser automation cost per task","Teams running high-volume automation workflows where token efficiency directly impacts budget","Users working with content-heavy websites where full DOM would exceed token limits"],"limitations":["Simplification heuristics may miss interactive elements with non-standard markup or ARIA attributes","Cannot preserve complex layout information — LLM receives flattened element list without spatial relationships","Dynamic content loaded after initial page render is not captured unless explicitly triggered","Simplified DOM loses context about element visibility, disabled state, and CSS-based interactivity"],"requires":["Chrome content script execution permissions on target domain","DOM must be accessible via standard JavaScript APIs (blocked by cross-origin restrictions)"],"input_types":["full webpage DOM (HTML structure)"],"output_types":["simplified DOM representation (JSON or text format with interactive elements only)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_10","uri":"capability://planning.reasoning.task.completion.detection.and.termination.logic","name":"task completion detection and termination logic","description":"The LLM determines when a task is complete by analyzing the current DOM state and action history, returning a 'complete' action type when the goal is achieved. The background service worker monitors for completion signals, task timeout (50-action limit), or explicit user termination via the popup UI. Upon completion, the extension displays a summary of executed actions and results to the user.","intents":["I want the system to automatically stop when the task is done","I need to manually stop a task that's taking too long","I want to see a summary of what was accomplished"],"best_for":["Users running long-running automation tasks who need automatic termination","Teams building production automation workflows requiring reliable task completion detection","Developers debugging automation failures and understanding why tasks terminated"],"limitations":["Completion detection relies on LLM judgment — may incorrectly detect completion if page state is ambiguous","50-action limit is a hard cap — no way to extend for complex workflows without code changes","No built-in error recovery — task terminates on first failure rather than attempting alternatives","User termination is not graceful — running action is not cancelled, only future actions are prevented"],"requires":["LLM integration for completion detection","Background service worker with task state management","Popup UI for user-initiated termination"],"input_types":["LLM response with action type (complete, click, setValue, navigate)","user termination signal from popup UI"],"output_types":["task completion status (success, failed, terminated by user)","summary of executed actions and results"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_11","uri":"capability://automation.workflow.webpack.based.build.system.and.extension.packaging","name":"webpack-based build system and extension packaging","description":"The extension uses Webpack to bundle TypeScript source code, React components, and dependencies into separate bundles for the background worker, content script, popup, and DevTools panel. The build process generates a manifest.json file with correct entry points, applies code splitting to optimize bundle sizes, and outputs a packaged extension ready for Chrome installation. Development mode includes hot reloading for faster iteration.","intents":["I want to build and package the extension for Chrome installation","I need to optimize bundle sizes for faster extension load times","I want to develop with hot reloading for faster iteration"],"best_for":["Developers building or extending Taxy AI from source","Teams deploying custom versions of the extension to internal users","Contributors to the open-source Taxy AI project"],"limitations":["Webpack configuration is complex and requires Node.js expertise to modify","Build process adds overhead to development workflow — requires npm build step before testing","Hot reloading works for popup/DevTools but not for background worker or content script (requires extension reload)","Bundle size optimization requires careful dependency management — unused dependencies increase final package size"],"requires":["Node.js 16+ with npm or yarn","Webpack 5+ (included in package.json)","TypeScript compiler (tsc) for type checking"],"input_types":["TypeScript source files, React components, configuration files"],"output_types":["packaged Chrome extension (dist/ directory with manifest.json and bundled scripts)"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_2","uri":"capability://tool.use.integration.chrome.debugger.api.based.element.interaction","name":"chrome debugger api-based element interaction","description":"Executes browser actions (clicks, form fills, navigation) using Chrome's debugger API rather than standard DOM events, providing more reliable interaction with modern web applications that use event delegation or custom event handlers. The content script receives action instructions from the background worker and translates them into debugger protocol commands for precise element targeting and interaction.","intents":["I need to interact with elements that don't respond to standard JavaScript click events","I want more reliable form submission on sites with complex event handling","I need to automate interactions on shadow DOM or web component-based interfaces"],"best_for":["Automation engineers working with modern React/Vue/Angular SPAs with custom event systems","Teams automating interactions on sites with aggressive event delegation or preventDefault handlers","Users targeting web applications with shadow DOM or custom element implementations"],"limitations":["Debugger API requires extension to have debugger permission — may trigger security warnings on some sites","Cannot interact with elements in iframes from different origins due to cross-origin restrictions","Debugger protocol commands add ~50-100ms latency per action compared to direct DOM manipulation","Some sites explicitly block debugger protocol access for security reasons"],"requires":["Chrome extension with debugger permission in manifest.json","Target page must allow debugger protocol attachment (not blocked by CSP or site configuration)"],"input_types":["action object (type: 'click' | 'setValue', selector: string, value?: string)"],"output_types":["action execution result (success/failure status, error message if applicable)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_3","uri":"capability://memory.knowledge.multi.step.task.execution.with.action.history.tracking","name":"multi-step task execution with action history tracking","description":"Maintains a stateful action history throughout task execution, allowing the LLM to observe results after each action before determining the next step. The background service worker stores action history in memory (via Zustand state management) and includes it in subsequent LLM prompts, enabling the model to adapt based on actual page state changes and detect task completion or failure conditions.","intents":["I want the system to learn from action results and adjust subsequent actions accordingly","I need visibility into what actions were taken and in what order","I want the system to detect when a task is complete or has failed"],"best_for":["Developers building complex multi-step automation workflows requiring adaptive behavior","QA teams needing detailed audit trails of automated test execution","Users automating workflows with conditional logic (e.g., 'if element appears, click it; otherwise continue')"],"limitations":["Action history is stored in memory only — lost on extension reload or browser restart","Limited to 50 actions per task; exceeding this limit terminates execution regardless of task completion","No built-in persistence layer — requires external storage for long-term audit trails","LLM must re-read entire action history for each step, increasing token usage and latency as history grows"],"requires":["Zustand state management library (included in extension dependencies)","Background service worker with persistent state across content script messages"],"input_types":["action results (DOM state after action, error messages, page navigation events)"],"output_types":["action history array (list of executed actions with timestamps and results)","task completion status (success, failed, in-progress)"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_4","uri":"capability://text.generation.language.popup.ui.task.input.and.result.display","name":"popup ui task input and result display","description":"Provides a React-based popup interface (built with Chakra UI) where users enter natural language task descriptions and view real-time execution results. The popup communicates with the background service worker via Chrome's message passing API, displaying action history, current DOM state, and task completion status. State is managed via Zustand, enabling reactive UI updates as the automation progresses.","intents":["I want a simple interface to describe a task and watch it execute","I need to see what actions were taken and their results","I want to stop a running task or modify instructions mid-execution"],"best_for":["Non-technical end users who need a simple task input interface","Developers prototyping automation workflows and debugging LLM behavior","Teams using Taxy AI as a user-facing automation tool in production"],"limitations":["Popup UI is limited to small viewport — action history and DOM state may be truncated or require scrolling","No built-in task scheduling or batch execution — each task must be triggered manually","Cannot persist task definitions or results across browser sessions without external storage","Real-time updates rely on Chrome message passing, which has latency and message size limits"],"requires":["React 18+ (included in extension dependencies)","Chakra UI component library (@chakra-ui/react)","Chrome extension popup context with message passing API"],"input_types":["natural language text (task description from user input)"],"output_types":["rendered UI with action history, current DOM state, task status","messages sent to background worker to start/stop tasks"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_5","uri":"capability://automation.workflow.devtools.panel.integration.for.advanced.debugging","name":"devtools panel integration for advanced debugging","description":"Provides an alternative interface in Chrome DevTools (separate from the popup) for advanced users to inspect DOM state, view LLM prompts and responses, and debug action execution. The DevTools panel has access to the same background worker state via Zustand and can display detailed information about each action cycle, including the simplified DOM sent to the LLM and the model's reasoning.","intents":["I want to debug why the LLM chose a particular action","I need to inspect the simplified DOM being sent to the LLM","I want to see the full LLM prompt and response for troubleshooting"],"best_for":["Developers building or extending Taxy AI automation workflows","QA engineers debugging automation failures and understanding LLM behavior","Researchers studying LLM-based browser automation and prompt engineering"],"limitations":["DevTools panel is only accessible to developers with extension installed — not available to end users","Requires Chrome DevTools to be open, adding overhead to browser performance","Cannot modify LLM prompts or responses in real-time — debugging is read-only","DevTools panel state is not persisted across browser restarts"],"requires":["Chrome DevTools API (chrome.devtools.panels)","Extension manifest with devtools_page configuration"],"input_types":["background worker state (action history, DOM state, LLM prompts/responses)"],"output_types":["rendered DevTools panel with detailed debugging information"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_6","uri":"capability://tool.use.integration.openai.api.integration.with.configurable.model.selection","name":"openai api integration with configurable model selection","description":"Abstracts OpenAI API calls through a configuration layer that allows users to select between GPT-4 and GPT-3.5-turbo models via the Options page. The background service worker sends the simplified DOM and action history to the selected model endpoint, handling API authentication via user-provided API keys stored in Chrome's storage API. Supports streaming responses for real-time feedback.","intents":["I want to choose between GPT-4 (more accurate) and GPT-3.5-turbo (cheaper) based on my needs","I need to use my own OpenAI API key for cost control and privacy","I want to see real-time LLM responses as they stream"],"best_for":["Teams with OpenAI API accounts who want to control LLM model selection and costs","Developers building custom automation workflows with specific accuracy/cost tradeoffs","Organizations with data privacy requirements that mandate direct API calls without intermediaries"],"limitations":["Requires valid OpenAI API key with GPT-4 or GPT-3.5-turbo access — no fallback to free models","API costs scale with action count and DOM complexity — no built-in cost estimation or budgeting","Streaming responses add complexity and may not work reliably on all network conditions","No support for other LLM providers (Anthropic, Ollama, etc.) — locked to OpenAI"],"requires":["OpenAI API key with active billing and model access","Chrome storage API for secure key storage","Network connectivity to OpenAI API endpoints"],"input_types":["simplified DOM (JSON or text format)","action history (array of executed actions)","user task description (natural language text)"],"output_types":["LLM response with next action determination (click, setValue, navigate, complete)","streaming response chunks for real-time feedback"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_7","uri":"capability://automation.workflow.options.page.configuration.for.api.keys.and.settings","name":"options page configuration for api keys and settings","description":"Provides a settings interface where users configure their OpenAI API key, select the LLM model (GPT-4 vs GPT-3.5-turbo), and adjust extension behavior. The Options page uses React and Chakra UI to render form inputs, stores configuration in Chrome's storage API with encryption, and validates API keys before saving. Changes are immediately reflected in the background worker via Zustand state updates.","intents":["I want to securely store my OpenAI API key without exposing it in code","I need to switch between GPT-4 and GPT-3.5-turbo based on my budget","I want to configure extension behavior (e.g., action timeout, max actions per task)"],"best_for":["Individual users setting up Taxy AI for the first time","Teams managing API keys across multiple users or machines","Developers customizing extension behavior for specific use cases"],"limitations":["API key storage relies on Chrome's storage API, which is not encrypted at rest — requires user trust in Chrome's security model","No multi-user support — API key is stored per browser profile, not per user","Configuration changes require page reload to take effect in some cases","No built-in API key validation or testing — users must manually verify keys work"],"requires":["Chrome storage API (chrome.storage.sync or chrome.storage.local)","React and Chakra UI for form rendering","Extension manifest with options_page configuration"],"input_types":["form inputs (API key text, model selection dropdown, configuration toggles)"],"output_types":["stored configuration in Chrome storage API","validation messages (success/error feedback)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_8","uri":"capability://planning.reasoning.action.determination.via.llm.reasoning.with.structured.output","name":"action determination via llm reasoning with structured output","description":"The background service worker sends a carefully crafted prompt to the LLM containing the simplified DOM, action history, and user task description. The LLM responds with a structured action object specifying the next action type (click, setValue, navigate, complete) and target element selector. The determineNextAction.ts module parses the LLM response and validates the action before execution, handling malformed responses gracefully.","intents":["I want the LLM to reason about which element to interact with next","I need structured action output that can be reliably parsed and executed","I want the system to detect when a task is complete or has failed"],"best_for":["Developers building LLM-based automation systems who need reliable action parsing","Teams automating complex workflows requiring multi-step reasoning","Researchers studying LLM reasoning for browser automation tasks"],"limitations":["LLM may generate invalid selectors or actions that don't exist on the page — no built-in fallback mechanism","Prompt engineering is critical for accuracy — small changes to the prompt can significantly affect action quality","No support for conditional logic or branching — LLM must choose a single next action","Action determination latency depends on LLM response time (typically 1-3 seconds for GPT-4)"],"requires":["OpenAI API with GPT-4 or GPT-3.5-turbo access","determineNextAction.ts module for parsing and validation","Simplified DOM in a format the LLM can reason about"],"input_types":["prompt string with DOM, action history, and task description","LLM response (text or streaming chunks)"],"output_types":["structured action object (type, selector, value, reasoning)","task completion status (success, failed, in-progress)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-taxy-ai__cap_9","uri":"capability://tool.use.integration.content.script.injection.and.dom.element.targeting","name":"content script injection and dom element targeting","description":"The content script injects into web pages via Chrome's content_scripts manifest configuration, gaining access to the page's DOM and JavaScript context. It extracts DOM information, simplifies it for the LLM, and executes actions by locating elements via CSS selectors or XPath. The script communicates with the background service worker via Chrome's message passing API, sending DOM state and receiving action instructions.","intents":["I want to extract and interact with elements on any webpage","I need to handle dynamic content loaded after page render","I want to execute actions reliably across different page structures"],"best_for":["Developers automating interactions on diverse websites with varying HTML structures","Teams building browser extensions that need reliable DOM access and element targeting","Users automating workflows on sites with dynamic content or JavaScript-heavy interfaces"],"limitations":["Content script cannot access pages with restrictive Content Security Policy (CSP) headers","Cross-origin iframes are inaccessible due to same-origin policy — cannot automate interactions within iframes from different domains","Dynamic content loaded via JavaScript after initial page render requires explicit triggers to be captured","Element selectors may become invalid if page structure changes — no built-in selector robustness"],"requires":["Chrome extension manifest with content_scripts configuration","Target page must allow content script injection (not blocked by CSP or site configuration)","CSS selector or XPath support for element targeting"],"input_types":["action instructions from background worker (type, selector, value)"],"output_types":["simplified DOM representation (JSON or text format)","action execution results (success/failure, error messages)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":28,"verified":false,"data_access_risk":"high","permissions":["Chrome browser (Manifest V3 compatible)","OpenAI API key with GPT-4 or GPT-3.5-turbo access","Active internet connection for API calls to OpenAI","Chrome content script execution permissions on target domain","DOM must be accessible via standard JavaScript APIs (blocked by cross-origin restrictions)","LLM integration for completion detection","Background service worker with task state management","Popup UI for user-initiated termination","Node.js 16+ with npm or yarn","Webpack 5+ (included in package.json)"],"failure_modes":["Limited to 50 sequential actions per task — complex workflows may exceed this threshold","Requires OpenAI API key and active internet connection for LLM inference","Cannot handle JavaScript-heavy SPAs that require complex state management beyond DOM observation","No built-in error recovery — if an action fails, the task terminates rather than attempting alternatives","Simplification heuristics may miss interactive elements with non-standard markup or ARIA attributes","Cannot preserve complex layout information — LLM receives flattened element list without spatial relationships","Dynamic content loaded after initial page render is not captured unless explicitly triggered","Simplified DOM loses context about element visibility, disabled state, and CSS-based interactivity","Completion detection relies on LLM judgment — may incorrectly detect completion if page state is ambiguous","50-action limit is a hard cap — no way to extend for complex workflows without code changes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.34,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.050Z","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=taxy-ai","compare_url":"https://unfragile.ai/compare?artifact=taxy-ai"}},"signature":"R45Lgg/AWOZGFdjctqtjyFbNmWK1cRo9peh1vkLEjP2eOVzQ0/qbQv36Nc34kcOa9fF9qUWWgpRFSxESimuyCg==","signedAt":"2026-06-20T22:43:09.147Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/taxy-ai","artifact":"https://unfragile.ai/taxy-ai","verify":"https://unfragile.ai/api/v1/verify?slug=taxy-ai","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"}}