{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-skaplanofficial--raycast-promptlab","slug":"skaplanofficial--raycast-promptlab","name":"Raycast-PromptLab","type":"skill","url":"https://www.raycast.com/HelloImSteven/promptlab","page_url":"https://unfragile.ai/skaplanofficial--raycast-promptlab","categories":["browser-extensions"],"tags":["ai","automation","autonomous-agent","chatgpt-api","extension","gpt","mac","macos","prompt-engineering","prompts","raycast","raycast-extension"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-skaplanofficial--raycast-promptlab__cap_0","uri":"capability://memory.knowledge.dynamic.placeholder.resolution.with.system.context.injection","name":"dynamic-placeholder-resolution-with-system-context-injection","description":"Resolves template placeholders ({{selectedFiles}}, {{clipboardText}}, {{todayEvents}}, {{currentApplication}}) at runtime by querying macOS system APIs, Raycast context, and file system state. Uses a placeholder resolution pipeline that maps placeholder tokens to resolver functions that fetch real-time context data, enabling prompts to dynamically bind to user environment state without manual context passing.","intents":["I want my AI prompt to automatically include the files I have selected in Finder","I need the AI to know what application I'm currently using and adapt its response","I want to inject today's calendar events into a prompt without manual copy-paste","I need the clipboard content automatically available to the AI command"],"best_for":["macOS users building context-aware AI workflows","automation enthusiasts who want AI to react to system state","teams creating reusable PromptLab commands that work across different contexts"],"limitations":["Placeholder resolution is synchronous and blocks command execution if system APIs are slow","Limited to macOS system context — no cross-platform placeholder support","Custom placeholders require manual resolver function implementation in TypeScript","No built-in caching of placeholder values — each execution re-fetches system state"],"requires":["macOS 10.15+","Raycast 1.40+","Appropriate system permissions for file access and calendar queries"],"input_types":["template strings with {{placeholder}} syntax","system file paths","calendar event queries"],"output_types":["resolved prompt text with injected context","structured context objects"],"categories":["memory-knowledge","context-injection"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_1","uri":"capability://automation.workflow.action.script.execution.with.applescript.and.shell.automation","name":"action-script-execution-with-applescript-and-shell-automation","description":"Executes AppleScript or shell commands after AI response generation, enabling post-processing automation workflows. Parses action script definitions from command configuration, executes them in the system shell or AppleScript runtime, and chains results back into the conversation context. Supports conditional execution based on AI response content and error handling with fallback behaviors.","intents":["I want the AI to generate code and automatically save it to a file","I need to run a shell command based on what the AI recommends","I want the AI to control macOS applications (open files, send messages) after responding","I need to chain multiple AI commands together with automated actions between them"],"best_for":["power users building complex automation workflows","developers integrating PromptLab into CI/CD or deployment pipelines","teams automating repetitive tasks with AI-driven decision making"],"limitations":["AppleScript execution requires explicit user permission and may fail silently if app permissions are denied","Shell script execution runs with user privileges — no privilege escalation or sandboxing","No built-in timeout mechanism for long-running action scripts","Error output from action scripts is not automatically captured or displayed to user"],"requires":["macOS 10.15+","System permissions for AppleScript execution","Shell environment with standard Unix tools available"],"input_types":["AppleScript code blocks","shell script code blocks","AI response text for conditional parsing"],"output_types":["shell command exit codes","AppleScript execution results","file system modifications","application state changes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_10","uri":"capability://memory.knowledge.browser.integration.with.tab.and.webpage.context.extraction","name":"browser-integration-with-tab-and-webpage-context-extraction","description":"Extracts context from the active browser tab including page title, URL, selected text, and full page content. Injects browser context into prompts via placeholders like {{browserTabTitle}}, {{browserTabURL}}, and {{selectedBrowserText}}. Enables AI commands to analyze web content, summarize articles, and answer questions about the current webpage without manual copy-paste.","intents":["I want the AI to summarize the article I'm currently reading","I need to ask questions about the content on my current webpage","I want to extract structured data from a website","I need the AI to analyze the page I'm viewing and suggest actions"],"best_for":["users working with web content","researchers analyzing online articles","teams automating web data extraction"],"limitations":["Browser integration only works with supported browsers (Safari, Chrome) — limited to macOS","Page content extraction may fail on JavaScript-heavy sites","Large webpages may be truncated due to context size limits","No support for extracting data from behind login walls"],"requires":["macOS 10.15+","Supported browser (Safari, Chrome)","Browser permissions for content access"],"input_types":["browser tab metadata","webpage content","selected text"],"output_types":["extracted webpage content","browser context metadata","AI analysis of webpage"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_11","uri":"capability://automation.workflow.advanced.settings.configuration.with.model.and.behavior.customization","name":"advanced-settings-configuration-with-model-and-behavior-customization","description":"Provides granular configuration options for command behavior including temperature, max tokens, system prompts, timeout settings, and response formatting. Stores settings in Raycast preferences, enabling users to fine-tune AI model behavior and command execution without modifying command definitions. Supports per-command overrides of global settings.","intents":["I want to adjust the creativity level of AI responses for specific commands","I need to set a maximum token limit to control response length","I want to customize the system prompt for a command","I need to configure timeout behavior for long-running commands"],"best_for":["advanced users fine-tuning AI behavior","teams standardizing model parameters across commands","developers optimizing for cost or latency"],"limitations":["Settings UI is limited to basic parameters — advanced model features require JSON editing","No validation of parameter values — invalid settings may cause API errors","Settings changes apply immediately — no preview or dry-run capability","No settings versioning — changes overwrite previous configurations"],"requires":["Raycast 1.40+","Understanding of AI model parameters (temperature, tokens, etc.)"],"input_types":["configuration parameters","model settings","timeout values"],"output_types":["stored settings","applied configuration"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_12","uri":"capability://automation.workflow.data.import.export.with.command.backup.and.migration","name":"data-import-export-with-command-backup-and-migration","description":"Supports importing and exporting command definitions as JSON files, enabling backup, migration, and sharing of command configurations. Implements JSON serialization of command metadata, prompts, action scripts, and settings. Provides import validation to detect incompatible command versions and handles data migration when PromptLab updates change the command schema.","intents":["I want to backup my custom commands","I need to migrate my commands to a new Mac","I want to share my command configuration with a colleague","I need to restore commands from a backup"],"best_for":["users managing command backups","teams sharing command libraries","developers migrating between machines"],"limitations":["Import/export is file-based — no cloud sync or version control integration","No conflict resolution when importing commands with duplicate names","Large command libraries may create large JSON files","No validation of imported commands — malicious commands could be imported"],"requires":["Raycast 1.40+","File system access for import/export"],"input_types":["command configuration JSON","exported command files"],"output_types":["exported JSON files","imported command definitions"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_13","uri":"capability://search.retrieval.search.and.execution.interface.for.command.discovery.and.invocation","name":"search-and-execution-interface-for-command-discovery-and-invocation","description":"Implements a searchable command palette (search-commands.tsx) that allows users to quickly find and execute PromptLab commands by name, description, or tags. Provides fuzzy search matching, command preview, and one-click execution. Integrates with Raycast's command search to make PromptLab commands discoverable alongside native Raycast commands.","intents":["I want to quickly find and run a PromptLab command","I need to search for commands by keyword or tag","I want to see a preview of what a command does before running it","I need to execute a command with custom parameters"],"best_for":["users with large command libraries","power users relying on keyboard shortcuts","teams standardizing command discovery"],"limitations":["Search is limited to command metadata — no full-text search of command prompts","Fuzzy search may return irrelevant results for ambiguous queries","No search history or saved searches","Command preview is limited to metadata — no execution preview"],"requires":["Raycast 1.40+","At least one PromptLab command installed"],"input_types":["search query","command name/description/tags"],"output_types":["search results","command execution"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_14","uri":"capability://automation.workflow.menubar.quick.access.with.pinned.commands","name":"menubar-quick-access-with-pinned-commands","description":"Provides a menubar item that offers quick access to frequently-used PromptLab commands without opening Raycast's main window. Allows users to pin commands to the menubar for one-click execution. Displays command status and recent results in the menubar dropdown, enabling rapid command invocation from anywhere on macOS.","intents":["I want quick access to my most-used commands from the menubar","I need to run a command without opening Raycast","I want to see the status of recent command executions","I need a keyboard shortcut to execute a pinned command"],"best_for":["power users executing commands frequently","users preferring menubar access over Raycast window","teams standardizing quick-access workflows"],"limitations":["Menubar space is limited — only a few commands can be pinned","Menubar dropdown UI is simplified — no full command configuration","No keyboard shortcuts for pinned commands — only mouse access","Menubar status updates may lag if commands run slowly"],"requires":["Raycast 1.40+","macOS 10.15+"],"input_types":["command selection","pin/unpin actions"],"output_types":["menubar dropdown UI","command execution","status display"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_2","uri":"capability://tool.use.integration.multi.model.ai.endpoint.abstraction.with.custom.model.support","name":"multi-model-ai-endpoint-abstraction-with-custom-model-support","description":"Abstracts AI model interactions behind a unified interface supporting OpenAI, Anthropic, and custom HTTP endpoints. Manages model configuration including API keys, base URLs, and request/response schemas. Implements request marshaling that converts PromptLab command context into model-specific input formats and parses model-specific response structures back into unified conversation objects.","intents":["I want to use Claude instead of GPT-4 for my PromptLab commands","I need to point PromptLab at my self-hosted LLM endpoint","I want to switch between multiple AI models for different commands","I need to configure custom request/response schemas for a proprietary AI API"],"best_for":["developers building multi-model AI workflows","enterprises using self-hosted or private LLM deployments","teams evaluating different AI providers without rewriting commands"],"limitations":["Custom endpoint support requires manual JSON schema definition for request/response mapping","No built-in retry logic or fallback to alternative models on API failure","Model switching is global — cannot mix models within a single conversation","API key management is local to Raycast — no centralized credential management"],"requires":["API key for OpenAI, Anthropic, or custom endpoint","Network connectivity to model endpoint","Raycast 1.40+"],"input_types":["model configuration objects","API keys and endpoint URLs","request schema definitions","prompt text and conversation history"],"output_types":["model responses","parsed completion text","token usage metadata"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_3","uri":"capability://planning.reasoning.conversational.chat.interface.with.autonomous.agent.capabilities","name":"conversational-chat-interface-with-autonomous-agent-capabilities","description":"Implements a multi-turn chat interface (CommandChatView) that maintains conversation history and enables autonomous agent behavior where the AI can invoke other PromptLab commands to fulfill user requests. Manages conversation state, renders streaming responses, and provides a command invocation mechanism that allows the AI to recursively call other commands with context from the current conversation.","intents":["I want to have a multi-turn conversation with an AI that can use my custom PromptLab commands","I need the AI to autonomously decide which of my commands to run based on user requests","I want conversation history to persist so I can reference earlier messages","I need the AI to chain multiple commands together to solve complex problems"],"best_for":["users building AI agents that leverage custom command libraries","teams creating conversational automation workflows","developers prototyping agentic AI systems within Raycast"],"limitations":["Conversation history is stored locally in Raycast — no cloud sync or multi-device access","Autonomous command invocation requires explicit AI instruction — no automatic intent detection","No built-in rate limiting or token budget management for long conversations","Command invocation context is limited to current conversation — cannot access external data sources"],"requires":["Raycast 1.40+","Configured AI model endpoint","At least one PromptLab command available for invocation"],"input_types":["user messages","conversation history","command invocation requests from AI"],"output_types":["streamed AI responses","command execution results","conversation state objects"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_4","uri":"capability://data.processing.analysis.file.content.extraction.and.multimodal.context.injection","name":"file-content-extraction-and-multimodal-context-injection","description":"Extracts and injects content from selected files into prompts, supporting multiple file types including text, code, images, audio, video, and office documents. Implements content extraction pipelines that parse file formats (PDF text extraction, image OCR, audio transcription, video frame analysis) and inject extracted content as context into AI prompts. Handles binary file formats and large files with size-aware truncation.","intents":["I want to ask the AI to review code from files I have selected in Finder","I need the AI to analyze images or screenshots I've selected","I want to transcribe audio files and have the AI summarize them","I need the AI to extract text from PDFs and answer questions about them"],"best_for":["developers using PromptLab for code review and analysis","content creators working with images, audio, and video","teams processing documents and extracting insights with AI"],"limitations":["Large file support is limited — files over 10MB may be truncated or fail extraction","Image OCR quality depends on image resolution and text clarity","Audio transcription requires network access to transcription service","Office document extraction may lose formatting and embedded objects","Video analysis is limited to frame extraction — no temporal analysis"],"requires":["File access permissions in Raycast","Supported file types (txt, code, pdf, jpg, png, mp3, mp4, docx, xlsx, etc.)","For audio/video: network connectivity to transcription/analysis services"],"input_types":["file paths","file content (text, binary)","image data","audio/video streams"],"output_types":["extracted text content","structured metadata","transcribed audio","image analysis results"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_5","uri":"capability://automation.workflow.command.creation.and.configuration.ui.with.template.builder","name":"command-creation-and-configuration-ui-with-template-builder","description":"Provides a visual command builder interface (create-command.tsx) that allows users to define custom AI commands without coding. Captures command metadata (name, description, icon), prompt template with placeholder syntax, model selection, action script definitions, and execution options. Stores command definitions as JSON in Raycast's local storage, enabling non-technical users to create reusable AI commands through a form-based UI.","intents":["I want to create a custom AI command without writing code","I need to build a command that uses specific placeholders and action scripts","I want to save my command configuration so I can reuse it later","I need to share my command with teammates by exporting the configuration"],"best_for":["non-technical users creating custom AI workflows","teams building shared command libraries","power users rapidly prototyping new automation ideas"],"limitations":["UI is limited to basic command configuration — complex conditional logic requires manual JSON editing","No visual placeholder picker — users must know placeholder names by memory","Action script editor is plain text — no syntax highlighting or validation","No command versioning or rollback — overwriting a command is permanent"],"requires":["Raycast 1.40+","Basic understanding of prompt engineering and placeholder syntax"],"input_types":["command name and description","prompt template text","placeholder references","action script code","model and execution settings"],"output_types":["command configuration JSON","stored command definition","shareable command export"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_6","uri":"capability://memory.knowledge.command.discovery.and.community.sharing.with.command.store","name":"command-discovery-and-community-sharing-with-command-store","description":"Implements a command discovery interface (discover-commands.tsx) that connects to a community command store, allowing users to browse, preview, and import pre-built commands from other users. Manages command metadata including author, description, tags, and ratings. Supports command import/export via JSON serialization, enabling a marketplace-like ecosystem where users can share and discover reusable automation patterns.","intents":["I want to find pre-built PromptLab commands for common tasks","I need to share my custom command with the community","I want to import a command someone else created and customize it","I need to browse commands by category or use case"],"best_for":["users discovering pre-built automation patterns","community contributors sharing commands","teams building shared command libraries across organizations"],"limitations":["Command store is community-driven — no curation or quality assurance","No built-in versioning — importing a command gets the latest version only","No dependency management — commands may reference other commands that aren't installed","Security: imported commands can contain arbitrary action scripts — user must review before importing"],"requires":["Raycast 1.40+","Network connectivity to command store","Trust in community-contributed commands"],"input_types":["command metadata (name, description, tags)","command configuration JSON","author information"],"output_types":["command listings","command previews","imported command definitions","exported command JSON"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_7","uri":"capability://memory.knowledge.persistent.variable.storage.and.state.management","name":"persistent-variable-storage-and-state-management","description":"Manages persistent variables that can be referenced across multiple command executions and conversations. Stores variable state in Raycast's local storage, enabling commands to maintain state between runs and share data across the command ecosystem. Supports variable interpolation in prompts using placeholder syntax and provides APIs for commands to read/write variables during execution.","intents":["I want to store a user preference that persists across multiple command runs","I need to share data between different PromptLab commands","I want to maintain conversation context across separate command invocations","I need to track state for multi-step automation workflows"],"best_for":["users building stateful automation workflows","teams creating interconnected command chains","developers implementing memory-based AI agents"],"limitations":["Variables are stored locally in Raycast — no cloud sync or backup","No built-in encryption — sensitive data stored in plaintext","Variable scope is global — no namespace isolation between commands","No automatic cleanup — orphaned variables persist indefinitely"],"requires":["Raycast 1.40+","Local storage access"],"input_types":["variable names","variable values (strings, JSON)","placeholder references"],"output_types":["variable values","interpolated prompt text"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_8","uri":"capability://automation.workflow.command.execution.history.and.audit.logging","name":"command-execution-history-and-audit-logging","description":"Tracks execution history of all PromptLab commands, storing metadata including timestamp, command name, input parameters, AI response, and execution status. Provides a searchable history interface that allows users to review past executions, re-run commands with previous parameters, and export execution logs. Enables audit trails for compliance and debugging of automation workflows.","intents":["I want to see what commands I've run and when","I need to re-run a command with the same parameters from yesterday","I want to export my command execution history for compliance","I need to debug why a command failed by reviewing its execution log"],"best_for":["users auditing their automation workflows","teams maintaining compliance records","developers debugging command execution issues"],"limitations":["History is stored locally — no cloud backup or multi-device sync","Large execution histories may impact Raycast performance","No automatic pruning — history grows indefinitely unless manually cleared","Sensitive data in prompts/responses is logged unencrypted"],"requires":["Raycast 1.40+","Local storage space for history"],"input_types":["command execution events","execution metadata"],"output_types":["execution history records","searchable history interface","exportable logs"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-skaplanofficial--raycast-promptlab__cap_9","uri":"capability://automation.workflow.speech.input.and.text.to.speech.output.integration","name":"speech-input-and-text-to-speech-output-integration","description":"Integrates macOS speech recognition for voice input to commands and text-to-speech for reading AI responses aloud. Uses native macOS speech APIs to capture voice input, transcribe to text, and synthesize responses. Enables hands-free command execution and audio feedback, making PromptLab accessible for voice-driven workflows and accessibility use cases.","intents":["I want to speak a prompt instead of typing it","I need the AI response read aloud to me","I want to use PromptLab hands-free while working","I need accessibility features for voice interaction"],"best_for":["users preferring voice interaction","accessibility-focused workflows","hands-free automation scenarios"],"limitations":["Speech recognition accuracy depends on audio quality and background noise","Text-to-speech uses system voices — limited voice options and naturalness","Speech input requires explicit permission in macOS privacy settings","No support for multiple languages in speech recognition"],"requires":["macOS 10.15+","Microphone access permission","Speaker for text-to-speech output"],"input_types":["audio stream from microphone","text for speech synthesis"],"output_types":["transcribed text","audio output"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":35,"verified":false,"data_access_risk":"high","permissions":["macOS 10.15+","Raycast 1.40+","Appropriate system permissions for file access and calendar queries","System permissions for AppleScript execution","Shell environment with standard Unix tools available","Supported browser (Safari, Chrome)","Browser permissions for content access","Understanding of AI model parameters (temperature, tokens, etc.)","File system access for import/export","At least one PromptLab command installed"],"failure_modes":["Placeholder resolution is synchronous and blocks command execution if system APIs are slow","Limited to macOS system context — no cross-platform placeholder support","Custom placeholders require manual resolver function implementation in TypeScript","No built-in caching of placeholder values — each execution re-fetches system state","AppleScript execution requires explicit user permission and may fail silently if app permissions are denied","Shell script execution runs with user privileges — no privilege escalation or sandboxing","No built-in timeout mechanism for long-running action scripts","Error output from action scripts is not automatically captured or displayed to user","Browser integration only works with supported browsers (Safari, Chrome) — limited to macOS","Page content extraction may fail on JavaScript-heavy sites","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.17401990332342743,"quality":0.5,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.15,"quality":0.25,"ecosystem":0.1,"match_graph":0.45,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.064Z","last_scraped_at":"2026-05-03T13:57:09.058Z","last_commit":"2024-01-17T04:33:52Z"},"community":{"stars":314,"forks":17,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=skaplanofficial--raycast-promptlab","compare_url":"https://unfragile.ai/compare?artifact=skaplanofficial--raycast-promptlab"}},"signature":"h4h4kvvf40tVTzpzL/koqtHLN+C+oU7IqqI2WIdI7NQbT5b9LObEx00aap6gaAju1DZC4Fr0sm+1WlDIuexLAw==","signedAt":"2026-06-21T18:16:42.241Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/skaplanofficial--raycast-promptlab","artifact":"https://unfragile.ai/skaplanofficial--raycast-promptlab","verify":"https://unfragile.ai/api/v1/verify?slug=skaplanofficial--raycast-promptlab","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"}}