{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_stonksgpt","slug":"stonksgpt","name":"StonksGPT","type":"webapp","url":"https://stonks.news","page_url":"https://unfragile.ai/stonksgpt","categories":["data-analysis"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_stonksgpt__cap_0","uri":"capability://search.retrieval.natural.language.company.information.retrieval","name":"natural-language company information retrieval","description":"Accepts free-form natural language queries about companies and returns structured company intelligence by translating user intent into database lookups and aggregated data sources. The system likely uses semantic understanding to map conversational queries (e.g., 'What's Apple's revenue trend?') to specific financial metrics and company attributes, then retrieves and synthesizes results from multiple underlying data sources without requiring users to learn terminal syntax or specific query languages.","intents":["I want to quickly look up a company's basic financials without navigating multiple websites","I need to understand a company's business model and key metrics in plain English","I want to compare company fundamentals without manually pulling data from SEC filings"],"best_for":["retail investors conducting preliminary due diligence","business students researching companies for coursework","non-technical founders evaluating potential partners or competitors"],"limitations":["No real-time data refresh — company metrics may be stale by hours or days","Query interpretation relies on NLP which may misunderstand domain-specific financial terminology","Cannot handle complex multi-step financial analysis (e.g., 'companies with improving margins and declining debt')"],"requires":["Internet connection to access backend data sources","Web browser or API client to submit queries"],"input_types":["natural language text queries"],"output_types":["structured text summaries","financial metrics (revenue, market cap, P/E ratio, etc.)","company descriptions"],"categories":["search-retrieval","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_1","uri":"capability://data.processing.analysis.multi.source.financial.data.aggregation","name":"multi-source financial data aggregation","description":"Integrates company data from multiple sources (likely SEC filings, company websites, financial databases) into a unified query interface, abstracting away the need for users to manually visit separate platforms. The system maintains connectors or ETL pipelines to ingest and normalize data from heterogeneous sources, then serves unified responses that cite or blend information from multiple origins.","intents":["I want company fundamentals from authoritative sources without toggling between Yahoo Finance, SEC Edgar, and investor relations pages","I need to verify company claims against official SEC filings","I want a single dashboard view of company data instead of managing multiple browser tabs"],"best_for":["retail investors who lack institutional data subscriptions","researchers prioritizing convenience over institutional-grade verification","casual investors exploring multiple companies quickly"],"limitations":["No clear sourcing methodology disclosed — users cannot verify which data came from which source","Aggregation may mask data conflicts or inconsistencies between sources","Update frequency for each source is unknown, risking stale or inconsistent data across queries","No audit trail showing when data was last refreshed from each source"],"requires":["Active connections to underlying data sources (SEC Edgar, company websites, financial APIs)","Data normalization layer to handle schema differences across sources"],"input_types":["company ticker or name"],"output_types":["unified company profiles","aggregated financial metrics","blended company descriptions"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_2","uri":"capability://data.processing.analysis.company.fundamentals.lookup.with.historical.context","name":"company fundamentals lookup with historical context","description":"Retrieves and presents company financial metrics (revenue, market cap, P/E ratio, debt levels, employee count, etc.) with historical snapshots to show trends over time. The system stores or accesses time-series financial data, likely from quarterly/annual SEC filings or financial data providers, and can surface how metrics have evolved across multiple reporting periods.","intents":["I want to see if a company's revenue has been growing or declining over the past 3-5 years","I need to understand a company's profitability trend before deciding to invest","I want to compare a company's current valuation metrics to historical averages"],"best_for":["value investors analyzing long-term company trends","students learning fundamental analysis","retail investors screening for growth or value characteristics"],"limitations":["Historical data is static and non-real-time — does not reflect intraday or minute-level changes","Limited to historical/quarterly data; cannot provide forward-looking projections or analyst estimates","No integration with earnings alerts or breaking news that could invalidate historical trends","Data freshness depends on SEC filing lag (typically 30-90 days after quarter end)"],"requires":["Access to historical financial databases (SEC Edgar, financial data APIs)","Time-series storage for multi-period metric tracking"],"input_types":["company ticker or name","optional: time range or specific metrics"],"output_types":["financial metrics (revenue, net income, EPS, debt, etc.)","historical trend data","year-over-year or quarter-over-quarter comparisons"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_3","uri":"capability://text.generation.language.company.profile.synthesis.and.summarization","name":"company profile synthesis and summarization","description":"Generates concise, human-readable company overviews by synthesizing business descriptions, industry classification, key products/services, and leadership information from multiple sources. The system likely uses text generation or template-based synthesis to create coherent company profiles that combine structured data (industry, employee count) with narrative content (business model, competitive positioning).","intents":["I want a quick summary of what a company does without reading their 10-K filing","I need to understand a company's competitive positioning and market focus","I want to know a company's key products and revenue streams at a glance"],"best_for":["business students learning about companies quickly","retail investors doing preliminary screening","non-financial professionals needing company context for business discussions"],"limitations":["Synthesized summaries may oversimplify complex business models or miss nuanced competitive dynamics","No real-time updates to company strategy or product changes — reflects historical positioning","Risk of hallucination or inaccuracy in synthesized descriptions without explicit source citation","Cannot capture recent pivots, acquisitions, or strategic shifts that haven't been formally filed"],"requires":["Access to company descriptions from SEC filings, websites, and business databases","Text generation or summarization model to synthesize coherent profiles"],"input_types":["company ticker or name"],"output_types":["company description text","industry classification","key products/services list","business model summary"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_4","uri":"capability://memory.knowledge.conversational.follow.up.and.context.retention","name":"conversational follow-up and context retention","description":"Maintains conversation context across multiple turns, allowing users to ask follow-up questions about a company without re-specifying the company name or context. The system likely stores the current conversation state (company in focus, previously retrieved metrics) and uses it to interpret subsequent queries, enabling natural dialogue flow.","intents":["I want to ask follow-up questions about a company without repeating its name each time","I want to compare metrics within the same conversation without losing context","I want to drill down into specific aspects of a company I've already looked up"],"best_for":["users conducting exploratory research sessions","investors comparing multiple metrics for the same company","students learning through iterative questioning"],"limitations":["Context retention is session-scoped — conversation history is lost when session ends","No persistent user profiles or saved research — each new session starts fresh","Context window may be limited, causing earlier conversation turns to be forgotten in long sessions","No ability to save or export conversation history for later reference"],"requires":["Session management infrastructure to track conversation state","Context encoding mechanism to pass prior conversation turns to the language model"],"input_types":["natural language follow-up queries"],"output_types":["contextual responses referencing prior conversation turns","comparative analysis across multiple queries"],"categories":["memory-knowledge","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_5","uri":"capability://automation.workflow.freemium.access.tier.with.usage.limits","name":"freemium access tier with usage limits","description":"Provides free access to core company lookup and summarization features with usage quotas or rate limits, while premium tiers unlock higher query volumes, advanced filtering, or additional data sources. The system implements quota tracking and tier enforcement at the API or session level to differentiate free vs. paid users.","intents":["I want to try financial research tools without committing to a paid subscription","I need to research a few companies casually without paying for institutional data","I want to evaluate the tool's quality before upgrading to premium features"],"best_for":["retail investors exploring financial research without institutional budgets","students and educators evaluating tools for classroom use","casual users with low-frequency research needs"],"limitations":["Free tier quotas may be restrictive, forcing users to upgrade for regular use","Premium features are not clearly documented, creating uncertainty about upgrade value","No clear pricing transparency — cost of premium tiers is not disclosed in available information","Free tier may have degraded data freshness or limited data sources compared to premium"],"requires":["User authentication system to track tier and usage","Quota enforcement mechanism at API or session level","Payment processing for premium tier upgrades"],"input_types":["user authentication credentials"],"output_types":["tier-specific feature access","usage quota tracking"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_stonksgpt__cap_6","uri":"capability://search.retrieval.company.search.and.disambiguation","name":"company search and disambiguation","description":"Resolves company names or tickers to specific entities, handling ambiguity when multiple companies share similar names or when users provide partial/misspelled identifiers. The system likely uses fuzzy matching, ticker resolution, or entity disambiguation to map user input to canonical company records in the underlying database.","intents":["I want to look up a company but I'm not sure of the exact spelling or ticker","I need to distinguish between similarly-named companies (e.g., multiple 'Tech' companies)","I want to search by company name instead of ticker symbol"],"best_for":["casual users unfamiliar with stock tickers","international investors researching non-US companies","users conducting exploratory research without precise company identifiers"],"limitations":["Fuzzy matching may return incorrect companies for ambiguous queries","Limited to companies in the underlying database — private companies or very small firms may not be found","No disambiguation UI to let users select from multiple matches — system may silently return wrong company","International company name variations (e.g., Chinese vs. English names) may not be handled"],"requires":["Company master database with tickers, names, and aliases","Fuzzy matching or entity resolution algorithm"],"input_types":["company name (full or partial)","stock ticker","company alias or alternative name"],"output_types":["canonical company identifier","company name and ticker","optional: list of similar companies for disambiguation"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Internet connection to access backend data sources","Web browser or API client to submit queries","Active connections to underlying data sources (SEC Edgar, company websites, financial APIs)","Data normalization layer to handle schema differences across sources","Access to historical financial databases (SEC Edgar, financial data APIs)","Time-series storage for multi-period metric tracking","Access to company descriptions from SEC filings, websites, and business databases","Text generation or summarization model to synthesize coherent profiles","Session management infrastructure to track conversation state","Context encoding mechanism to pass prior conversation turns to the language model"],"failure_modes":["No real-time data refresh — company metrics may be stale by hours or days","Query interpretation relies on NLP which may misunderstand domain-specific financial terminology","Cannot handle complex multi-step financial analysis (e.g., 'companies with improving margins and declining debt')","No clear sourcing methodology disclosed — users cannot verify which data came from which source","Aggregation may mask data conflicts or inconsistencies between sources","Update frequency for each source is unknown, risking stale or inconsistent data across queries","No audit trail showing when data was last refreshed from each source","Historical data is static and non-real-time — does not reflect intraday or minute-level changes","Limited to historical/quarterly data; cannot provide forward-looking projections or analyst estimates","No integration with earnings alerts or breaking news that could invalidate historical trends","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"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":"2026-05-24T12:16:33.648Z","last_scraped_at":"2026-04-05T13:23:42.559Z","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=stonksgpt","compare_url":"https://unfragile.ai/compare?artifact=stonksgpt"}},"signature":"te3TD0NgpEkp6jt+am28gSPBbzImhJBWI27gJFr2RAeepTfNJP7CexFgE8AcAIl/W6L5CVSMDBm+J9KQZT5HCA==","signedAt":"2026-06-21T10:15:53.900Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/stonksgpt","artifact":"https://unfragile.ai/stonksgpt","verify":"https://unfragile.ai/api/v1/verify?slug=stonksgpt","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"}}