{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_invxst","slug":"invxst","name":"Invxst","type":"product","url":"https://www.invxstai.com","page_url":"https://unfragile.ai/invxst","categories":["data-analysis"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_invxst__cap_0","uri":"capability://data.processing.analysis.earnings.report.to.summary.transformation","name":"earnings-report-to-summary-transformation","description":"Converts unstructured earnings reports, SEC filings, and financial documents into plain-English investment summaries using LLM-based extraction and abstractive summarization. The system likely employs document chunking with sliding windows to preserve context across multi-page filings, then applies extractive key-point identification followed by abstractive generation to produce investor-focused narratives highlighting revenue trends, margin changes, guidance, and risk factors.","intents":["I need to understand what a company's earnings report means without reading 50 pages of dense financial prose","I want to quickly identify material changes in a company's financial position compared to prior quarters","I need to extract the key risks and opportunities from an earnings call transcript in under 5 minutes"],"best_for":["retail investors with limited time for fundamental analysis","portfolio managers screening multiple companies for research efficiency","financial advisors needing to brief clients on portfolio holdings"],"limitations":["LLM summarization can omit nuanced guidance or forward-looking statements that move markets","Abstractive summaries may introduce subtle misinterpretations of accounting changes or one-time items","No ability to cross-reference current summary against historical filings for trend validation","Freemium tier likely limits number of documents processed per month or access to real-time filings"],"requires":["Access to earnings reports in PDF, HTML, or text format","Internet connection for real-time filing retrieval from SEC EDGAR or company investor relations","User account (free or paid) on Invxst platform"],"input_types":["PDF documents (10-K, 10-Q, 8-K filings)","HTML earnings call transcripts","Plain text financial statements","Earnings release documents"],"output_types":["structured JSON with key metrics, summary text, and risk highlights","plain-text narrative summary","bullet-point highlights with sentiment indicators"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_1","uri":"capability://data.processing.analysis.market.data.aggregation.and.normalization","name":"market-data-aggregation-and-normalization","description":"Ingests real-time and historical market data from multiple sources (stock prices, options chains, sector indices, economic indicators) and normalizes them into a unified schema for analysis. The system likely maintains connectors to financial data APIs (Alpha Vantage, IEX Cloud, or proprietary feeds) with caching and deduplication logic to handle duplicate ticks, and applies time-series alignment to ensure cross-asset comparisons are temporally consistent.","intents":["I want to see how a stock's price movement correlates with sector performance and broader market indices in real time","I need to pull historical price data for backtesting without manually downloading from multiple sources","I want to monitor multiple watchlists and get alerts when price or volume thresholds are breached"],"best_for":["active traders building custom screening workflows","portfolio managers tracking real-time P&L across holdings","retail investors building personal investment dashboards"],"limitations":["Real-time data latency depends on upstream API providers; free tiers often have 15-20 minute delays","Freemium tier likely restricts historical data depth (e.g., 1 year vs 10 years of daily OHLCV)","No support for alternative data sources (satellite imagery, credit card transactions, web traffic) that institutional investors use","Data normalization may mask exchange-specific nuances (e.g., pre-market vs regular session volatility)"],"requires":["Active Invxst account with API credentials (if programmatic access is offered)","Real-time market data subscription or free tier API key from underlying data provider","Stable internet connection for continuous data streaming"],"input_types":["ticker symbols or ISIN codes","date ranges for historical queries","asset class filters (equities, options, indices, commodities)"],"output_types":["OHLCV (open, high, low, close, volume) time series in JSON or CSV","normalized price feeds with metadata (exchange, currency, adjustment factors)","aggregated sector and index performance snapshots"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_10","uri":"capability://data.processing.analysis.news.sentiment.and.event.impact.analysis","name":"news-sentiment-and-event-impact-analysis","description":"Aggregates financial news and social media sentiment for individual stocks and analyzes the correlation between sentiment shifts and price movements. The system likely uses NLP-based sentiment classification (positive/negative/neutral) on news articles and social posts, then correlates sentiment changes with subsequent stock returns to quantify the impact of news events on price.","intents":["I want to understand the sentiment around a stock I'm considering based on recent news and social media","I need to identify whether recent price movements are driven by fundamental news or just noise","I want to get early warning of negative sentiment shifts that might precede price declines"],"best_for":["sentiment-driven traders looking for contrarian opportunities","fundamental analysts seeking context for price movements","retail investors wanting to understand market perception of their holdings"],"limitations":["Sentiment analysis can be inaccurate, especially for sarcasm or complex financial language","Social media sentiment is often driven by retail traders and may not reflect institutional views","Freemium tier likely provides only current sentiment snapshot, not historical sentiment trends","Sentiment can be noisy and subject to manipulation (e.g., coordinated social media campaigns)"],"requires":["Financial news feeds (e.g., Reuters, Bloomberg, Yahoo Finance news)","Social media data (Twitter, Reddit, StockTwits) for sentiment extraction","NLP models trained on financial sentiment classification","Historical price data for correlation analysis"],"input_types":["ticker symbol","time window for sentiment analysis (1 week, 1 month, 3 months)","sentiment source selection (news, social media, or both)"],"output_types":["current sentiment score (positive/negative/neutral) with confidence","sentiment trend over time (rising/falling/stable)","list of recent news articles with sentiment classification","correlation between sentiment changes and price movements","sentiment momentum indicator"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_11","uri":"capability://search.retrieval.stock.screening.and.filtering","name":"stock-screening-and-filtering","description":"Enables users to define custom screening criteria (valuation multiples, growth rates, dividend yield, technical indicators) and identify stocks matching those criteria from a universe of thousands. The system likely maintains a pre-computed database of fundamental and technical metrics updated daily, then applies user-defined filters using a rule engine to quickly return matching stocks without requiring real-time calculation.","intents":["I want to find all stocks in the market that meet my investment criteria (e.g., P/E < 15, dividend yield > 3%)","I need to screen for stocks with specific characteristics (e.g., high growth, low debt, strong margins)","I want to save and reuse screening criteria to monitor for new opportunities"],"best_for":["value investors screening for undervalued stocks","growth investors finding high-growth opportunities","dividend investors identifying income-generating stocks"],"limitations":["Freemium tier likely limits number of screening criteria or universe size (e.g., US large-cap only)","Pre-computed metrics may be stale (updated daily vs real-time), missing intraday opportunities","No support for complex custom metrics or backtesting of screening rules","Screening results can be noisy; many matching stocks may not be investable (illiquid, delisted, etc.)"],"requires":["Fundamental and technical metrics database updated at least daily","Rule engine for filtering and combining criteria","Stock universe definition (e.g., US equities, international, specific sectors)"],"input_types":["screening criteria (valuation, growth, profitability, dividend, technical metrics)","filters (sector, market cap, country, liquidity)","sorting preferences (by metric value, market cap, etc.)"],"output_types":["list of matching stocks with key metrics displayed","sortable table with customizable columns","saved screening templates for future use","export functionality (CSV, JSON) for further analysis"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_2","uri":"capability://planning.reasoning.ai.generated.investment.thesis.synthesis","name":"ai-generated-investment-thesis-synthesis","description":"Combines summarized earnings data, market trends, and analyst sentiment into coherent investment theses that articulate bull and bear cases for individual securities. The system likely uses multi-step reasoning (chain-of-thought style) to weigh quantitative signals (valuation metrics, growth rates) against qualitative factors (competitive positioning, management quality) and generates structured arguments with confidence scores, enabling users to understand the reasoning behind AI-generated recommendations.","intents":["I want to see both the bull and bear case for a stock I'm considering, synthesized from multiple data sources","I need to understand why the AI thinks a stock is undervalued or overvalued, with specific supporting evidence","I want to compare investment theses across multiple stocks to identify the most compelling opportunity"],"best_for":["individual investors building conviction on stock picks","financial advisors explaining stock recommendations to clients","portfolio managers screening for new positions with AI-assisted due diligence"],"limitations":["AI-generated theses can suffer from recency bias, overweighting recent earnings beats or price momentum","Confidence scores may be artificially high due to LLM overconfidence; no calibration against historical accuracy","Cannot account for black-swan events or tail risks that fall outside training data distribution","Freemium tier likely limits thesis generation frequency or depth of analysis (e.g., bull/bear cases only vs detailed scenario modeling)"],"requires":["Completed earnings summaries and market data from upstream capabilities","Invxst account with thesis generation feature enabled","Sufficient historical data on the security (typically 2+ years of financials)"],"input_types":["ticker symbol","optional user-provided context (e.g., 'compare to sector peers', 'focus on ESG factors')","date range for analysis window"],"output_types":["structured JSON with bull case, bear case, valuation summary, and confidence scores","narrative text explaining key drivers and risks","visual comparison charts (valuation multiples vs peers, growth trajectory)"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_3","uri":"capability://automation.workflow.real.time.market.alert.and.notification.system","name":"real-time-market-alert-and-notification-system","description":"Monitors user-defined watchlists and thresholds (price targets, volume spikes, earnings dates, sector rotations) and delivers alerts via email, push notifications, or in-app messages when conditions are met. The system likely uses event-driven architecture with streaming data processors (e.g., Kafka-style pipelines) that evaluate rules against incoming market ticks in near-real-time, with deduplication logic to prevent alert fatigue.","intents":["I want to be notified immediately when a stock I'm watching hits my target price, without constantly checking the app","I need alerts for earnings announcements and economic data releases that could impact my portfolio","I want to set up complex alerts (e.g., 'notify me if this stock rises 5% AND volume exceeds 2x average') without coding"],"best_for":["active traders who need to react quickly to market movements","busy professionals who can't monitor markets continuously","portfolio managers tracking multiple positions across asset classes"],"limitations":["Alert latency depends on data feed freshness; free tier may have 15-20 minute delays vs real-time for paid","Freemium tier likely limits number of active alerts or watchlist size","No native integration with trading platforms; users must manually execute trades after receiving alerts","Alert fatigue risk if users set too many thresholds; no built-in alert optimization or filtering"],"requires":["Active Invxst account with notification preferences configured","Email address or mobile device for receiving alerts","Real-time market data feed with sufficient freshness (typically <5 minute delay for paid tiers)"],"input_types":["ticker symbols and watchlist definitions","alert rules (price targets, volume thresholds, percentage changes)","notification preferences (email, push, SMS, webhook)"],"output_types":["alert notifications via email, push, or in-app message","alert history log with timestamp and triggered condition details","optional webhook payloads for integration with trading bots"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_4","uri":"capability://data.processing.analysis.portfolio.performance.attribution.and.analytics","name":"portfolio-performance-attribution-and-analytics","description":"Analyzes user portfolio holdings and decomposes returns into contributions from individual positions, sectors, and macro factors (market beta, interest rate sensitivity, currency exposure). The system likely uses time-weighted return calculations and factor attribution models to isolate the impact of each holding on overall portfolio performance, enabling users to understand whether outperformance came from stock picking skill or market timing.","intents":["I want to understand which of my stock picks actually contributed to my portfolio's returns vs which were drags","I need to see how much of my portfolio's performance came from sector allocation vs individual stock selection","I want to compare my portfolio's risk-adjusted returns against a benchmark to assess my skill"],"best_for":["individual investors evaluating their own investment performance","financial advisors demonstrating value-add to clients","portfolio managers conducting post-trade analysis and performance reviews"],"limitations":["Attribution analysis requires accurate cost basis and transaction history; missing or incorrect data degrades accuracy","Freemium tier likely provides only basic return calculations, not sophisticated factor attribution","No support for complex positions (options, derivatives, short sales) that require specialized accounting","Benchmark selection is user-dependent; system cannot automatically choose optimal benchmark for comparison"],"requires":["Complete portfolio transaction history (buy/sell dates, quantities, prices)","Current market values for all holdings","Benchmark selection (e.g., S&P 500, Russell 2000, custom index)","Optional: dividend and corporate action history for precise return calculations"],"input_types":["portfolio holdings list with cost basis","transaction history (buys, sells, dividends)","benchmark ticker or custom benchmark definition","date range for analysis"],"output_types":["time-weighted return (TWR) and money-weighted return (MWR) metrics","position-level contribution to total return","sector and asset class attribution breakdown","risk metrics (volatility, Sharpe ratio, max drawdown) vs benchmark","visual performance charts and comparison tables"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_5","uri":"capability://data.processing.analysis.sector.and.macro.trend.analysis","name":"sector-and-macro-trend-analysis","description":"Identifies emerging trends across sectors and macro factors (interest rates, inflation, GDP growth, currency movements) and correlates them with individual stock performance to highlight which securities are well-positioned for current market conditions. The system likely uses time-series correlation analysis and sentiment extraction from financial news to detect regime shifts and sector rotations, then surfaces relevant holdings or opportunities to users.","intents":["I want to know which sectors are likely to outperform in the current macro environment","I need to understand how rising interest rates will impact my portfolio's holdings","I want to identify stocks that are benefiting from or suffering from current market trends"],"best_for":["macro-focused investors building thematic portfolios","tactical asset allocators rotating between sectors","retail investors seeking context for their stock picks within broader market trends"],"limitations":["Macro trend identification is inherently uncertain and subject to regime changes; past correlations may not hold","Freemium tier likely provides only high-level trend summaries, not detailed sector rotation signals","No support for alternative macro indicators (credit spreads, volatility term structure, commodity curves) that institutional investors use","Sentiment analysis from news can be noisy and subject to media bias"],"requires":["Real-time macro data feeds (interest rates, inflation, GDP, currency indices)","Financial news and sentiment data sources","Historical sector and stock performance data for correlation analysis"],"input_types":["macro factor selection (interest rates, inflation, GDP, currency, commodities)","sector or stock ticker for trend analysis","time window for trend identification (e.g., 'last 3 months', 'last year')"],"output_types":["trend identification with direction (bullish/bearish) and confidence score","correlation matrix showing relationships between macro factors and sector/stock performance","narrative analysis explaining the macro drivers and implications","list of stocks positioned to benefit or suffer from identified trends"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_6","uri":"capability://data.processing.analysis.comparative.valuation.analysis","name":"comparative-valuation-analysis","description":"Calculates and compares valuation multiples (P/E, P/B, EV/EBITDA, PEG ratio) for a given stock against its sector peers, historical averages, and growth rates to assess whether the stock is cheap or expensive. The system likely uses normalized earnings and forward guidance to compute forward-looking multiples, then applies statistical analysis (percentile rankings, z-scores) to contextualize valuations within peer groups.","intents":["I want to know if a stock is trading at a discount or premium to its peers","I need to compare a stock's valuation multiple against its historical average to identify mean reversion opportunities","I want to see whether a stock's valuation is justified by its growth rate (PEG analysis)"],"best_for":["value investors screening for undervalued stocks","growth investors assessing whether growth justifies valuation","fundamental analysts building valuation models"],"limitations":["Valuation multiples can be distorted by one-time items, accounting changes, or cyclical earnings; requires manual adjustment","Freemium tier likely provides only basic multiples (P/E, P/B), not comprehensive valuation metrics","Peer group selection is critical but often subjective; system may use overly broad or narrow peer sets","Forward multiples depend on analyst estimates which can be inaccurate, especially for high-growth or distressed companies"],"requires":["Current and historical financial statements (income statement, balance sheet)","Current market capitalization and share count","Analyst earnings estimates for forward multiples","Peer group definition (by sector, market cap, geography)"],"input_types":["ticker symbol","optional peer group filter (sector, market cap range, geography)","valuation metric selection (P/E, P/B, EV/EBITDA, PEG, etc.)"],"output_types":["current and forward valuation multiples","peer group comparison with percentile rankings","historical valuation chart showing current vs average","valuation assessment (undervalued/fairly valued/overvalued) with confidence score","growth-adjusted valuation (PEG ratio, EV/Growth)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_7","uri":"capability://data.processing.analysis.earnings.estimate.consensus.tracking","name":"earnings-estimate-consensus-tracking","description":"Aggregates analyst earnings estimates from multiple sources and tracks consensus expectations for revenue, EPS, and other metrics across quarters and years. The system likely maintains a time-series of estimate revisions to detect momentum (rising vs falling estimates) and identifies earnings surprises by comparing actual results against consensus, enabling users to spot stocks with positive or negative estimate revisions.","intents":["I want to see what analysts expect a company to earn and how those expectations have changed recently","I need to identify stocks where earnings estimates are rising (positive momentum) or falling (negative momentum)","I want to know if a stock is likely to beat or miss earnings based on estimate trends"],"best_for":["earnings-focused traders looking for estimate revision momentum","fundamental analysts tracking consensus expectations","portfolio managers monitoring earnings risk for holdings"],"limitations":["Analyst estimates can be systematically biased (e.g., too optimistic for growth stocks); consensus may not reflect true expectations","Freemium tier likely provides only current consensus, not historical revision trends","No support for sell-side research reports that provide context for estimates","Estimate revisions can be noisy and subject to outlier analysts; requires filtering for signal"],"requires":["Access to analyst estimate databases (e.g., FactSet, Refinitiv, Yahoo Finance consensus)","Historical estimate data for revision tracking","Actual earnings results for comparison against consensus"],"input_types":["ticker symbol","fiscal period (current quarter, next quarter, current year, next year)","metric selection (revenue, EPS, EBITDA, etc.)"],"output_types":["consensus estimate with number of analysts and range (high/low)","estimate revision history showing trend over time","earnings surprise percentage (actual vs consensus)","estimate momentum indicator (rising/falling/stable)","visual chart of estimate revisions and actual results"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_8","uri":"capability://data.processing.analysis.risk.assessment.and.volatility.analysis","name":"risk-assessment-and-volatility-analysis","description":"Quantifies downside risk for individual stocks and portfolios using metrics like beta, standard deviation, value-at-risk (VaR), and maximum drawdown. The system likely calculates these metrics from historical price data and correlations, then contextualizes them against benchmarks and peer groups to help users understand the risk profile of their holdings.","intents":["I want to understand how volatile a stock is compared to the market and its peers","I need to assess the worst-case loss scenario for my portfolio under normal market conditions","I want to identify which of my holdings are the riskiest and consider diversification"],"best_for":["risk-conscious investors building diversified portfolios","portfolio managers conducting risk analysis and stress testing","financial advisors explaining portfolio risk to clients"],"limitations":["Historical volatility may not predict future volatility, especially during regime changes","VaR assumes normal distribution of returns, which underestimates tail risk during market crashes","Freemium tier likely provides only basic volatility metrics, not sophisticated risk models","Correlation estimates are unstable and time-varying; static correlations can be misleading"],"requires":["Historical price data (typically 1-3 years minimum for accurate volatility estimates)","Benchmark index data for beta calculation","Peer group data for comparative risk analysis"],"input_types":["ticker symbol or portfolio holdings list","time window for risk calculation (1 year, 3 years, 5 years)","confidence level for VaR (95%, 99%)","benchmark selection for beta calculation"],"output_types":["volatility (annualized standard deviation)","beta (systematic risk relative to benchmark)","value-at-risk (VaR) with confidence interval","maximum drawdown and recovery time","Sharpe ratio and other risk-adjusted return metrics","correlation matrix for portfolio holdings"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_invxst__cap_9","uri":"capability://data.processing.analysis.dividend.and.income.analysis","name":"dividend-and-income-analysis","description":"Tracks dividend history, yield, payout ratios, and sustainability for dividend-paying stocks, and identifies dividend growth trends or cuts. The system likely maintains historical dividend data and compares current yields against historical averages to identify high-yield opportunities, while also analyzing payout ratios and free cash flow to assess dividend sustainability.","intents":["I want to find stocks with high and sustainable dividend yields for income generation","I need to track whether a company is likely to cut its dividend based on payout ratio and cash flow trends","I want to identify dividend growth stocks that have consistently increased payouts over time"],"best_for":["income-focused investors building dividend portfolios","retirees seeking passive income from stock holdings","dividend growth investors seeking long-term capital appreciation with income"],"limitations":["High dividend yield can signal financial distress (dividend trap); requires manual assessment of sustainability","Freemium tier likely provides only current yield and payout ratio, not historical dividend growth analysis","No support for dividend reinvestment calculations or tax-adjusted returns","Dividend cuts are often announced suddenly; system cannot predict cuts with certainty"],"requires":["Historical dividend payment data (ex-date, payment date, amount per share)","Current stock price for yield calculation","Financial statements for payout ratio and cash flow analysis"],"input_types":["ticker symbol","time window for dividend history (1 year, 5 years, 10 years)","yield threshold for screening (e.g., 'show stocks with yield > 3%')"],"output_types":["current dividend yield and annual dividend per share","dividend payout ratio (dividends / earnings)","dividend growth rate over time","dividend sustainability assessment based on cash flow","historical dividend chart and ex-dividend dates","list of dividend growth stocks or high-yield opportunities"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Access to earnings reports in PDF, HTML, or text format","Internet connection for real-time filing retrieval from SEC EDGAR or company investor relations","User account (free or paid) on Invxst platform","Active Invxst account with API credentials (if programmatic access is offered)","Real-time market data subscription or free tier API key from underlying data provider","Stable internet connection for continuous data streaming","Financial news feeds (e.g., Reuters, Bloomberg, Yahoo Finance news)","Social media data (Twitter, Reddit, StockTwits) for sentiment extraction","NLP models trained on financial sentiment classification","Historical price data for correlation analysis"],"failure_modes":["LLM summarization can omit nuanced guidance or forward-looking statements that move markets","Abstractive summaries may introduce subtle misinterpretations of accounting changes or one-time items","No ability to cross-reference current summary against historical filings for trend validation","Freemium tier likely limits number of documents processed per month or access to real-time filings","Real-time data latency depends on upstream API providers; free tiers often have 15-20 minute delays","Freemium tier likely restricts historical data depth (e.g., 1 year vs 10 years of daily OHLCV)","No support for alternative data sources (satellite imagery, credit card transactions, web traffic) that institutional investors use","Data normalization may mask exchange-specific nuances (e.g., pre-market vs regular session volatility)","Sentiment analysis can be inaccurate, especially for sarcasm or complex financial language","Social media sentiment is often driven by retail traders and may not reflect institutional views","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:31.445Z","last_scraped_at":"2026-04-05T13:23:42.560Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=invxst","compare_url":"https://unfragile.ai/compare?artifact=invxst"}},"signature":"tc+Oa27gobqYU3rHkzFOfHTW0/+1yxjBdmNn02h+tsU9esot7fJGV7dUgQwPX9co9JCpJzfMDWv0dSHTm3lBAQ==","signedAt":"2026-06-21T04:27:33.635Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/invxst","artifact":"https://unfragile.ai/invxst","verify":"https://unfragile.ai/api/v1/verify?slug=invxst","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"}}