{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tgpt","slug":"tgpt","name":"tgpt","type":"cli","url":"https://github.com/aandrew-me/tgpt","page_url":"https://unfragile.ai/tgpt","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tgpt__cap_0","uri":"capability://tool.use.integration.api.key.free.ai.model.access.via.provider.abstraction.layer","name":"api-key-free ai model access via provider abstraction layer","description":"Tgpt implements a multi-provider abstraction layer that routes requests to free AI providers (Phind, Isou, KoboldAI) without requiring API keys, while also supporting optional API-key-based providers (OpenAI, Gemini, Deepseek, Groq) and self-hosted Ollama. The architecture uses a provider registry pattern where each provider implements a common interface for request/response handling, enabling transparent switching between free and paid backends based on user configuration or environment variables (AI_PROVIDER, AI_API_KEY).","intents":["Use AI models in terminal without managing API keys or billing","Switch between free and paid providers without code changes","Fall back to local Ollama when internet access is restricted","Prototype AI features without upfront API costs"],"best_for":["Solo developers and hobbyists avoiding API costs","Teams prototyping AI features before committing to paid providers","Users in regions with restricted API access"],"limitations":["Free providers may have rate limits or unstable uptime (Phind, Isou documented as free but not guaranteed)","No guaranteed SLA or response time for free providers","API-key providers require valid credentials and active billing","Ollama requires local installation and model downloads (5GB+ per model)"],"requires":["Internet connection for free/API providers OR local Ollama installation","Environment variables AI_PROVIDER and AI_API_KEY optional for API-based providers","Go runtime or pre-compiled binary for Linux/macOS/Windows/FreeBSD"],"input_types":["text prompts","piped stdin for contextual input"],"output_types":["streaming text responses","complete text blocks (with -w/--whole flag)"],"categories":["tool-use-integration","provider-abstraction"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_1","uri":"capability://memory.knowledge.stateful.interactive.conversation.with.context.memory","name":"stateful interactive conversation with context memory","description":"Tgpt maintains conversation state across multiple turns using two interactive modes: normal interactive (-i/--interactive) for single-line input with command history, and multiline interactive (-m/--multiline) for editor-like input. The architecture preserves previous messages in memory (PrevMessages field in Params structure) and passes them to the AI provider with each new request, enabling the model to maintain context across turns. This is implemented via the interactive loop in main.go (lines 319-425) which accumulates messages and manages the conversation thread.","intents":["Have multi-turn conversations without losing context between prompts","Use command history to recall and modify previous prompts","Write longer, more complex prompts in a text editor interface","Maintain separate conversation threads via ThreadID parameter"],"best_for":["Developers debugging code iteratively with AI assistance","Writers and content creators drafting longer pieces","Users exploring topics through conversational Q&A"],"limitations":["Context memory is in-process only — lost on CLI exit (no persistence layer)","No built-in conversation export or save functionality","Memory grows linearly with conversation length; very long conversations may exceed provider token limits","Multiline mode requires external editor (EDITOR environment variable) — falls back to default if not set"],"requires":["Interactive terminal with TTY support","EDITOR environment variable for multiline mode (vim, nano, emacs, etc.)","Active AI provider connection (free or API-based)"],"input_types":["single-line text input (-i mode)","multi-line text via external editor (-m mode)","command history navigation (arrow keys in -i mode)"],"output_types":["streaming text responses","conversation history in memory (not persisted)"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_10","uri":"capability://image.visual.batch.image.generation.with.customizable.dimensions.and.aspect.ratios","name":"batch image generation with customizable dimensions and aspect ratios","description":"Tgpt's image generation mode supports generating multiple images in a single request via ImgCount parameter, with customizable dimensions (Width, Height) and aspect ratios (ImgRatio). The ImageParams structure enables fine-grained control over generation parameters, and the imagegen module handles batch processing and disk output. Multiple images are saved with sequential naming (e.g., image_1.png, image_2.png) to the specified output directory (Out parameter).","intents":["Generate multiple image variations of the same concept","Create images with specific aspect ratios (square, widescreen, portrait)","Batch generate images for content creation workflows","Control image dimensions for specific use cases (thumbnails, banners, etc.)"],"best_for":["Content creators needing multiple image variations","Designers exploring different aspect ratios","Batch processing workflows requiring multiple images"],"limitations":["Batch generation speed depends on provider (Pollinations/Arta may queue requests)","No progress feedback during batch generation — user waits for all images","Aspect ratio support depends on provider (not all ratios may be available)","Disk space required scales with batch size (1-5MB per image × count)"],"requires":["Disk space for output images","Internet connection to image generation provider","Optional: Image viewer for reviewing generated images"],"input_types":["text description","negative prompt (optional)","image count (ImgCount parameter)","dimensions (Width, Height)","aspect ratio (ImgRatio)"],"output_types":["multiple PNG/JPEG files saved to disk","sequential filenames (image_1.png, image_2.png, etc.)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_11","uri":"capability://tool.use.integration.ollama.self.hosted.model.integration.with.local.inference","name":"ollama self-hosted model integration with local inference","description":"Supports local AI model inference via Ollama, a self-hosted model runner that allows users to run open-source models (Llama, Mistral, etc.) on their own hardware. The implementation treats Ollama as a provider in the registry, routing requests to a local Ollama instance via HTTP API. This enables offline operation and full data privacy, as all inference happens locally without sending data to external providers.","intents":["I want to use AI models without sending data to external providers","I need to run AI inference on my own hardware for privacy or cost reasons","I want to use open-source models like Llama or Mistral in my terminal"],"best_for":["privacy-conscious developers and teams","organizations with data residency requirements","users with powerful local hardware (GPU recommended)"],"limitations":["Requires local Ollama installation and model download (can be 5-50GB per model)","Inference speed depends on local hardware; slower than cloud providers on CPU-only systems","Model quality varies; open-source models may be less capable than proprietary models","No automatic model management; users must manually download and manage models"],"requires":["Ollama installed and running locally (https://ollama.ai)","At least one model downloaded in Ollama (e.g., `ollama pull llama2`)","Sufficient disk space for model files (5-50GB per model)","Optional: GPU for faster inference (NVIDIA CUDA or AMD ROCm supported)"],"input_types":["text prompts"],"output_types":["AI responses from local model"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_12","uri":"capability://tool.use.integration.configuration.via.environment.variables.and.cli.flags","name":"configuration via environment variables and cli flags","description":"Supports configuration through multiple channels: command-line flags (e.g., -p/--provider, -k/--api-key), environment variables (AI_PROVIDER, AI_API_KEY), and configuration files (tgpt.json). The system implements a precedence hierarchy where CLI flags override environment variables, which override config file settings. This enables flexible configuration for different use cases (single invocation, session-wide, or persistent).","intents":["I want to set a default AI provider that persists across multiple CLI invocations","I need to use different API keys for different providers without hardcoding them","I want to configure tgpt differently for different projects or environments"],"best_for":["developers managing multiple API keys and providers","teams standardizing tgpt configuration across environments","users deploying tgpt in CI/CD pipelines with environment-specific settings"],"limitations":["Configuration precedence (CLI > env > file) may be confusing if settings are spread across multiple sources","No validation of configuration values; invalid settings may cause runtime errors","Configuration file (tgpt.json) is not automatically created; users must manually set up","No built-in configuration management UI; all configuration is text-based"],"requires":["CLI flags: -p/--provider, -k/--api-key, -m/--model, -t/--temperature, etc.","Environment variables: AI_PROVIDER, AI_API_KEY","Optional: tgpt.json configuration file in the current directory or home directory"],"input_types":["CLI flags","environment variables","JSON configuration file"],"output_types":["none (configuration only)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_13","uri":"capability://tool.use.integration.proxy.configuration.for.network.requests","name":"proxy configuration for network requests","description":"Supports HTTP/HTTPS proxy configuration via environment variables (HTTP_PROXY, HTTPS_PROXY) or configuration files, enabling tgpt to route requests through corporate proxies or VPNs. The system integrates proxy settings into the HTTP client initialization, allowing transparent proxy support without code changes. This is essential for users in restricted network environments.","intents":["I need to use tgpt behind a corporate proxy without modifying the binary","I want to route AI requests through a VPN or proxy for privacy","I need to configure different proxies for different providers"],"best_for":["enterprise users behind corporate firewalls","developers in restricted network environments","teams using VPNs for privacy or security"],"limitations":["Proxy configuration is global; cannot use different proxies for different providers in a single invocation","No proxy authentication support (username/password); only basic HTTP proxy URLs","Proxy errors are not always clearly reported; may result in timeout errors instead of proxy-specific messages","SOCKS proxies are not supported; only HTTP/HTTPS proxies"],"requires":["Environment variables: HTTP_PROXY, HTTPS_PROXY","Optional: proxy configuration in tgpt.json","Valid HTTP/HTTPS proxy URL (e.g., http://proxy.example.com:8080)"],"input_types":["proxy URL via environment variable or config file"],"output_types":["none (configuration only)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_2","uri":"capability://code.generation.editing.syntax.highlighted.code.generation.with.language.detection","name":"syntax-highlighted code generation with language detection","description":"Tgpt's code generation mode (-c/--code) routes prompts to AI providers with a specialized preprompt that instructs models to generate code, then applies syntax highlighting to the output based on detected language. The implementation uses the helper module (src/helper/helper.go) to parse code blocks from responses and apply terminal color formatting. The Preprompt field in Params structure allows customization of the system message, enabling code-specific instructions to be injected before the user's prompt.","intents":["Generate code snippets with proper syntax highlighting in terminal","Get code examples for specific programming languages","Copy highlighted code directly from terminal output","Understand code structure through color-coded syntax"],"best_for":["Developers writing quick scripts or utility functions","Learners studying code examples in terminal environment","Teams using terminal-first workflows (SSH sessions, remote servers)"],"limitations":["Syntax highlighting limited to terminal color capabilities (256-color or true color)","No IDE integration — output is text-only, not importable into editors","Language detection relies on AI model's code block formatting (language notation) — may fail for ambiguous or unlabeled blocks","No code execution or validation — generated code is not tested before display"],"requires":["Terminal supporting ANSI color codes (most modern terminals)","AI provider capable of generating code (all supported providers)","Optional: TERM environment variable set to enable color output"],"input_types":["text prompts describing desired code","code snippets as context (via piped stdin)"],"output_types":["syntax-highlighted code blocks in terminal","plain text code (if colors disabled)"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_3","uri":"capability://code.generation.editing.shell.command.generation.with.execution.safety","name":"shell command generation with execution safety","description":"Tgpt's shell command mode (-s/--shell) generates executable shell commands from natural language descriptions by routing prompts through AI providers with shell-specific preprompts. The architecture separates generation from execution — commands are displayed to the user for review before running, preventing accidental execution of potentially dangerous commands. The implementation uses the Preprompt field to inject instructions that guide models toward generating safe, idiomatic shell syntax.","intents":["Generate shell commands from natural language descriptions","Learn shell syntax by seeing AI-generated examples","Quickly construct complex command pipelines without manual syntax lookup","Review generated commands before execution for safety"],"best_for":["DevOps engineers and system administrators automating tasks","Developers unfamiliar with shell syntax","Teams standardizing command generation across environments"],"limitations":["Generated commands are not validated for correctness or safety — user must review before execution","No shell-specific syntax validation (e.g., quoting, escaping) — relies on AI model accuracy","Commands generated for one shell (bash) may not work in others (zsh, fish, PowerShell)","No integration with shell history or command execution — output is text-only"],"requires":["AI provider capable of generating shell commands (all supported providers)","Shell environment to execute generated commands (bash, zsh, sh, etc.)","User responsibility to review commands before execution"],"input_types":["natural language descriptions of desired shell operations","context via piped stdin (e.g., file listings, error messages)"],"output_types":["shell command strings (one or multiple commands)","command explanations (if AI provides them)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_4","uri":"capability://image.visual.text.to.image.generation.with.multi.provider.support","name":"text-to-image generation with multi-provider support","description":"Tgpt's image generation mode (-img/--image) routes text descriptions to image generation providers (Pollinations by default, Arta as alternative) via the imagegen module (src/imagegen/imagegen.go). The architecture uses ImageParams structure to configure generation parameters (ImgRatio, ImgNegativePrompt, ImgCount, Width, Height, Out) and supports multiple model options within Arta provider. Generated images are saved to disk (Out parameter specifies path) or displayed via terminal image protocols if supported.","intents":["Generate images from text descriptions without Midjourney/DALL-E subscriptions","Create multiple image variations with different aspect ratios","Use negative prompts to exclude unwanted elements","Batch generate images with custom dimensions"],"best_for":["Content creators prototyping visual ideas quickly","Developers building image generation features","Teams exploring AI image capabilities without API costs"],"limitations":["Image quality and speed depend on provider availability (Pollinations/Arta uptime not guaranteed)","No real-time generation progress feedback — user waits for complete image","Limited control over generation parameters compared to DALL-E (no seed, no guidance scale)","Output images saved to disk only — no streaming or preview in terminal","Arta provider requires model selection; default model may not suit all use cases"],"requires":["Internet connection to reach Pollinations or Arta APIs","Disk space for image output (typically 1-5MB per image)","Optional: Image viewer for displaying generated images (feh, eog, Preview.app, etc.)"],"input_types":["text descriptions of desired images","negative prompts (text descriptions of unwanted elements)","image parameters (aspect ratio, dimensions, count)"],"output_types":["PNG/JPEG image files saved to disk","image metadata (dimensions, generation time)"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_5","uri":"capability://tool.use.integration.piped.input.integration.for.contextual.prompting","name":"piped input integration for contextual prompting","description":"Tgpt supports piping stdin into prompts, enabling users to provide context (code snippets, error messages, file contents) alongside natural language questions. The architecture reads from stdin when available and concatenates it with command-line arguments before sending to AI providers. This is implemented in main.go's argument handling (lines 209-453) which checks for piped input and merges it with explicit prompt text, allowing seamless integration with Unix pipes and command chaining.","intents":["Ask AI questions about code or error messages by piping them directly","Debug issues by piping error logs and asking for solutions","Refactor code by piping file contents and requesting improvements","Analyze data by piping output from other commands"],"best_for":["DevOps engineers debugging via piped logs","Developers analyzing code or errors in terminal workflows","System administrators troubleshooting via command chains"],"limitations":["Piped input is concatenated as-is — no automatic context labeling (e.g., 'this is code' vs 'this is an error')","Large piped inputs may exceed AI provider token limits (typically 4K-128K tokens depending on provider)","No automatic formatting or syntax detection for piped content — AI must infer context from content","Piped input cannot be edited interactively — use multiline mode (-m) for editing"],"requires":["Unix-like shell supporting pipes (bash, zsh, sh, etc.)","Source command or process producing output to pipe","AI provider with sufficient token limit for piped content"],"input_types":["piped stdin from other commands (cat, grep, curl, etc.)","command-line prompt text (combined with piped input)","file contents via cat or redirection"],"output_types":["AI response analyzing or addressing piped context","suggestions or solutions based on piped input"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_6","uri":"capability://automation.workflow.cross.platform.binary.distribution.with.self.update.mechanism","name":"cross-platform binary distribution with self-update mechanism","description":"Tgpt is distributed as pre-compiled binaries for Linux, macOS, Windows, and FreeBSD, with a built-in self-update mechanism (-u/--update flag) that checks for new versions and updates the binary in-place. The architecture uses GitHub releases as the distribution source and implements version checking logic (version.txt file) to determine if updates are available. Installation is supported via multiple package managers (Arch Linux, FreeBSD, Scoop, Chocolatey) and direct download scripts, enabling zero-friction deployment across platforms.","intents":["Install tgpt without compiling from source","Keep tgpt updated with latest features and bug fixes","Deploy tgpt across heterogeneous teams (Windows, macOS, Linux)","Manage tgpt via existing package managers"],"best_for":["Non-technical users wanting quick installation","Teams managing multiple machines with different OSes","Users in restricted environments (no Go compiler available)"],"limitations":["Self-update requires write permissions to binary location (may fail in system directories without sudo)","Update checks require internet connectivity to GitHub releases API","No rollback mechanism — failed updates cannot be reverted automatically","Package manager availability varies by platform (Scoop/Chocolatey Windows-only, Arch Linux AUR-only)"],"requires":["Linux (x86_64, ARM64), macOS (Intel/Apple Silicon), Windows (x86_64), or FreeBSD","Internet connection for initial download and updates","Optional: Package manager (apt, pacman, brew, scoop, chocolatey, pkg)"],"input_types":["installation method selection (direct download, package manager, Go install)"],"output_types":["executable binary in PATH","version information (tgpt --version)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_7","uri":"capability://tool.use.integration.configurable.ai.model.parameters.with.environment.variable.overrides","name":"configurable ai model parameters with environment variable overrides","description":"Tgpt allows configuration of AI model behavior through command-line flags, environment variables (AI_PROVIDER, AI_API_KEY), and configuration files (tgpt.json). The Params structure includes fields for ApiKey, ApiModel, Temperature, Top_p, Max_length enabling fine-grained control over model behavior. The architecture supports hierarchical configuration: command-line flags override environment variables, which override config file settings, enabling both global defaults and per-invocation customization.","intents":["Adjust model creativity via temperature parameter","Set default provider and API key globally","Use different models for different tasks","Control response length and token limits","Configure proxy settings for restricted networks"],"best_for":["Advanced users tuning model behavior for specific tasks","Teams standardizing AI configuration across projects","Users in restricted networks requiring proxy configuration"],"limitations":["Configuration file format (tgpt.json) not documented in DeepWiki — users must infer structure","Parameter support varies by provider (e.g., temperature may not be supported by all free providers)","No validation of parameter values — invalid settings may cause provider errors","Proxy configuration requires manual environment variable setup (HTTP_PROXY, HTTPS_PROXY)"],"requires":["Optional: tgpt.json configuration file in home directory or project root","Optional: Environment variables AI_PROVIDER, AI_API_KEY, HTTP_PROXY, HTTPS_PROXY","Optional: Command-line flags for per-invocation overrides"],"input_types":["configuration file (JSON format)","environment variables","command-line flags"],"output_types":["applied configuration (visible in verbose mode if available)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_8","uri":"capability://text.generation.language.streaming.response.output.with.optional.quiet.mode","name":"streaming response output with optional quiet mode","description":"Tgpt streams AI responses in real-time to the terminal by default, displaying a loading animation while waiting for the provider. The quiet mode (-q/--quiet) suppresses the loading animation for cleaner output in scripts or piped contexts. The whole text mode (-w/--whole) returns the complete response as a single block instead of streaming, useful for processing or piping output to other commands. The implementation uses streaming APIs from providers when available, with fallback to buffered output for providers that don't support streaming.","intents":["See AI responses in real-time without waiting for completion","Suppress loading animations in automated scripts","Get complete responses as single blocks for piping","Reduce visual clutter in terminal output"],"best_for":["Interactive users wanting real-time feedback","Scripts and automation requiring clean output","Users piping tgpt output to other commands"],"limitations":["Streaming output cannot be edited or reviewed before display — no preview mode","Loading animation may interfere with other terminal output in multiplexed environments (tmux, screen)","Whole text mode (-w) requires buffering entire response in memory before output","Some providers may not support streaming (fallback to buffered output)"],"requires":["Terminal supporting ANSI escape codes for loading animation","Optional: Pipe destination for whole text mode output"],"input_types":["prompts (text or piped)"],"output_types":["streaming text (default)","complete text block (-w/--whole)","text without animation (-q/--quiet)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__cap_9","uri":"capability://tool.use.integration.modular.architecture.with.provider.specific.implementations","name":"modular architecture with provider-specific implementations","description":"Tgpt uses a modular architecture where each AI provider (Phind, Isou, KoboldAI, OpenAI, Gemini, Deepseek, Groq, Ollama) implements a common interface for request/response handling. The core logic in main.go routes requests to provider-specific modules based on the AI_PROVIDER setting, enabling new providers to be added without modifying core code. The architecture separates concerns: CLI argument parsing (main.go), business logic (helper.go), image generation (imagegen.go), and provider implementations (separate modules per provider).","intents":["Add new AI providers without modifying core tgpt code","Maintain provider-specific logic in isolated modules","Switch providers at runtime based on configuration","Extend tgpt with custom provider implementations"],"best_for":["Developers contributing new provider support","Teams building custom tgpt forks with proprietary providers","Projects requiring provider abstraction for testing"],"limitations":["Provider interface not documented in DeepWiki — developers must infer from existing implementations","Adding new providers requires Go programming knowledge","No plugin system — new providers require code changes and recompilation","Provider-specific parameters (temperature, top_p) may not be universally supported"],"requires":["Go 1.18+ for compilation","Understanding of provider APIs and authentication methods","Familiarity with tgpt codebase structure"],"input_types":["provider implementation code (Go modules)"],"output_types":["compiled tgpt binary with new provider support"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tgpt__headline","uri":"capability://chatbots.assistants.terminal.based.ai.chatbot","name":"terminal-based ai chatbot","description":"A command-line interface tool that allows users to interact with various AI models directly from the terminal without needing API keys, featuring code execution, shell command generation, and image generation.","intents":["best terminal AI chatbot","AI chatbot for command line","free AI chatbot without API keys","CLI tool for AI interaction","AI chatbot with code generation capabilities"],"best_for":["developers","command line users"],"limitations":["limited to terminal use","requires basic command line knowledge"],"requires":["terminal access"],"input_types":["text input"],"output_types":["text output","code snippets","images"],"categories":["chatbots-assistants"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":57,"verified":false,"data_access_risk":"high","permissions":["Internet connection for free/API providers OR local Ollama installation","Environment variables AI_PROVIDER and AI_API_KEY optional for API-based providers","Go runtime or pre-compiled binary for Linux/macOS/Windows/FreeBSD","Interactive terminal with TTY support","EDITOR environment variable for multiline mode (vim, nano, emacs, etc.)","Active AI provider connection (free or API-based)","Disk space for output images","Internet connection to image generation provider","Optional: Image viewer for reviewing generated images","Ollama installed and running locally (https://ollama.ai)"],"failure_modes":["Free providers may have rate limits or unstable uptime (Phind, Isou documented as free but not guaranteed)","No guaranteed SLA or response time for free providers","API-key providers require valid credentials and active billing","Ollama requires local installation and model downloads (5GB+ per model)","Context memory is in-process only — lost on CLI exit (no persistence layer)","No built-in conversation export or save functionality","Memory grows linearly with conversation length; very long conversations may exceed provider token limits","Multiline mode requires external editor (EDITOR environment variable) — falls back to default if not set","Batch generation speed depends on provider (Pollinations/Arta may queue requests)","No progress feedback during batch generation — user waits for all images","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"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":"2026-06-17T09:51:05.296Z","last_scraped_at":null,"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=tgpt","compare_url":"https://unfragile.ai/compare?artifact=tgpt"}},"signature":"ARruKB1SIAR2dE0RNNBFN20SxdNkCgw0+xUu80wpRc2ctL/R/CX3pRbzMKRwSmRYTieMl3rZPUFRIOIOq5prCQ==","signedAt":"2026-06-22T12:07:13.459Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/tgpt","artifact":"https://unfragile.ai/tgpt","verify":"https://unfragile.ai/api/v1/verify?slug=tgpt","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"}}