{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_sharehouse","slug":"sharehouse","name":"Sharehouse","type":"product","url":"https://sharehouse.app","page_url":"https://unfragile.ai/sharehouse","categories":["text-writing"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_sharehouse__cap_0","uri":"capability://text.generation.language.personalized.rental.cover.letter.generation.with.tenant.profile.synthesis","name":"personalized rental cover letter generation with tenant profile synthesis","description":"Generates customized rental cover letters by synthesizing user-provided tenant information (employment history, rental background, references, personal circumstances) through a language model prompt pipeline that emphasizes landlord-relevant factors like income stability, payment reliability, and community fit. The system likely uses structured form inputs to extract key data points, then constructs a multi-turn prompt that instructs the LLM to weave these facts into a compelling narrative that addresses common landlord concerns without sounding generic or AI-generated.","intents":["I need to quickly generate a professional cover letter for a rental application without hiring a writing service","I want to highlight my strengths as a tenant (stable job, clean rental history, references) in a way that resonates with landlords","I'm competing in a tight rental market and need to stand out from other applicants with a personalized narrative"],"best_for":["Individual renters in competitive housing markets applying to private landlords or smaller properties","Renters without professional writing skills or access to paid application preparation services","Applicants seeking to supplement traditional screening criteria (credit checks, income verification) with a human narrative"],"limitations":["No integration with major rental platforms (Zillow, Apartments.com, Craigslist) — requires manual copy-paste workflow","Generated letters may sound formulaic or overly polished, potentially raising skepticism from landlords familiar with AI writing patterns","Effectiveness depends entirely on landlord willingness to read and weight cover letters; many landlords rely primarily on credit scores and income verification","No A/B testing or feedback loop to optimize letter quality based on application success rates","Cannot verify or validate user-provided information (employment, rental history), so letters may contain unverified claims"],"requires":["Web browser with JavaScript enabled","User-provided tenant information (employment details, rental history, references, personal circumstances)","No API keys or authentication required for free tier"],"input_types":["structured form data (text fields for employment, rental history, references, personal details)","optional narrative context or specific landlord concerns the user wants to address"],"output_types":["plain text cover letter (typically 200-400 words)","formatted text suitable for copy-paste into rental applications"],"categories":["text-generation-language","automation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_1","uri":"capability://data.processing.analysis.tenant.profile.data.collection.and.structuring.via.guided.form.interface","name":"tenant profile data collection and structuring via guided form interface","description":"Collects and structures tenant information through a multi-step form interface that guides users through relevant categories (employment, rental history, references, personal circumstances, landlord preferences). The form likely uses conditional logic to show/hide fields based on user responses, validates input formats, and organizes data into a structured schema that can be passed to the LLM prompt pipeline for letter generation.","intents":["I need a simple way to input my tenant information without worrying about what details matter most","I want to ensure I'm providing all the information that will make my cover letter compelling to landlords","I prefer a guided experience that tells me what to fill in rather than a blank text box"],"best_for":["Non-technical renters who benefit from structured guidance and form validation","Users applying to multiple properties who want to reuse and modify tenant profile data","Renters unfamiliar with what information landlords actually care about"],"limitations":["Form-based input may feel restrictive compared to free-form narrative input for users with complex housing situations","No data persistence or account system mentioned — users likely cannot save profiles across sessions","Form validation may reject legitimate but non-standard employment or housing situations","No integration with external data sources (employment verification, credit bureaus) to auto-populate fields"],"requires":["Web browser with JavaScript enabled","User willingness to provide personal information (employment, rental history, references)"],"input_types":["text input (employment title, company name, rental history dates, reference names/contact info)","optional file uploads or structured data import"],"output_types":["structured JSON or internal data model representing tenant profile","validated form data ready for LLM prompt injection"],"categories":["data-processing-analysis","automation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_2","uri":"capability://text.generation.language.llm.powered.narrative.generation.with.landlord.perspective.prompting","name":"llm-powered narrative generation with landlord-perspective prompting","description":"Invokes a language model (likely OpenAI GPT-3.5 or GPT-4) with a carefully engineered prompt that instructs the model to synthesize tenant profile data into a compelling rental cover letter from a landlord's perspective. The prompt likely includes instructions to emphasize specific signals (income stability, payment reliability, community fit, references), avoid red flags, maintain a professional but personable tone, and keep the letter within typical length constraints (200-400 words). The system may use prompt chaining or multi-turn interactions to refine the output.","intents":["I want the AI to write a cover letter that sounds professional and human, not generic or obviously AI-generated","I need the letter to address common landlord concerns (will this tenant pay rent on time? will they take care of the property?)","I want to generate multiple versions of the letter with different tones or emphases"],"best_for":["Renters who want AI assistance but need the output to sound authentic and personable","Users applying to landlords who value narrative context alongside traditional screening criteria","Applicants seeking to differentiate themselves in competitive markets where cover letters might influence decisions"],"limitations":["LLM outputs are non-deterministic — same input may generate slightly different letters across invocations","No built-in mechanism to prevent the model from generating overly polished or obviously AI-written text that raises landlord skepticism","Cannot verify factual claims in the generated letter (e.g., employment dates, reference accuracy)","Model may hallucinate or invent details if user input is vague or incomplete","No feedback loop to optimize prompts based on application success rates or landlord feedback"],"requires":["API access to a language model (OpenAI, Anthropic, or similar) — likely handled server-side by Sharehouse","Structured tenant profile data from the form collection step","Sufficient API quota/credits to handle user requests"],"input_types":["structured tenant profile data (employment, rental history, references, personal circumstances)","optional user preferences (tone, length, emphasis areas)"],"output_types":["plain text rental cover letter (typically 200-400 words)","optionally multiple versions for user comparison"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_3","uri":"capability://text.generation.language.multi.version.letter.generation.and.comparison.interface","name":"multi-version letter generation and comparison interface","description":"Enables users to generate multiple variations of their rental cover letter with different tones, emphases, or lengths, then compare and select the best version. This likely involves re-invoking the LLM with modified prompts (e.g., 'emphasize employment stability' vs. 'emphasize community involvement') and presenting the results side-by-side for user evaluation. The interface may include copy-to-clipboard functionality and version history tracking.","intents":["I want to see how my cover letter sounds with different tones (professional vs. personable, formal vs. casual)","I want to generate multiple versions and pick the one that feels most authentic to my voice","I want to emphasize different strengths (employment stability vs. rental history vs. references) and see which resonates best"],"best_for":["Renters who want to experiment with different narrative approaches before submitting","Users applying to multiple landlords with different profiles (corporate vs. individual, luxury vs. affordable housing)","Applicants seeking to optimize their letter through iterative refinement"],"limitations":["Generating multiple versions increases API costs and latency","No guidance on which version is most likely to succeed with landlords — users must rely on intuition","Comparing multiple AI-generated letters may amplify concerns about authenticity if all versions sound similarly polished","No A/B testing capability to measure which versions actually improve application success rates"],"requires":["Web browser with JavaScript enabled","Sufficient API quota to generate multiple letter versions","User willingness to review and compare multiple outputs"],"input_types":["structured tenant profile data","user-specified variation parameters (tone, emphasis, length)"],"output_types":["multiple plain text cover letter versions (typically 2-5 variations)","side-by-side comparison interface"],"categories":["text-generation-language","automation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_4","uri":"capability://automation.workflow.copy.to.clipboard.and.export.functionality.with.format.preservation","name":"copy-to-clipboard and export functionality with format preservation","description":"Provides one-click copy-to-clipboard functionality and optional export formats (plain text, PDF, formatted document) that preserve the generated cover letter's formatting and allow easy integration into rental application workflows. The system likely detects the user's operating system and browser to optimize clipboard handling, and may include options to export with or without formatting.","intents":["I want to quickly copy my cover letter and paste it into a rental application form","I need to save my cover letter as a PDF or document file to attach to an email or application","I want to use the same letter across multiple rental applications with minimal friction"],"best_for":["Renters applying to multiple properties who need quick, frictionless export","Users applying through various rental platforms with different submission methods (web forms, email, PDF attachments)","Applicants who want to maintain a local copy of their letters for record-keeping"],"limitations":["No direct integration with rental platforms — requires manual copy-paste or file upload workflow","PDF export may not preserve formatting perfectly across different browsers or operating systems","No tracking of which letters were submitted to which properties","Clipboard functionality may be blocked by browser security policies in some contexts"],"requires":["Web browser with clipboard API support (modern browsers)","Optional: PDF generation library (likely server-side)"],"input_types":["generated cover letter text"],"output_types":["plain text (clipboard)","PDF file (optional)","formatted document (optional)"],"categories":["automation-workflow","automation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_5","uri":"capability://memory.knowledge.tenant.profile.persistence.and.reuse.across.multiple.applications","name":"tenant profile persistence and reuse across multiple applications","description":"Stores user-provided tenant profile data (employment, rental history, references) in browser local storage or a user account system, enabling quick reuse and modification across multiple rental applications without re-entering information. The system likely includes profile editing, version history, and the ability to create multiple profiles for different application scenarios (e.g., 'solo applicant' vs. 'co-applicant with partner').","intents":["I'm applying to multiple properties and don't want to re-enter my information each time","I want to save my tenant profile and modify it slightly for different landlords or property types","I want to maintain multiple profiles for different application scenarios (solo vs. co-applicant)"],"best_for":["Renters applying to multiple properties in a short timeframe","Users who want to experiment with different profile variations without losing their original data","Applicants in competitive markets applying to dozens of properties"],"limitations":["Browser local storage has limited capacity (~5-10MB) and is cleared if user clears browser data","No apparent account system or cloud sync mentioned — profiles may not persist across devices","No encryption or security measures mentioned for storing sensitive personal information","Editing profiles requires returning to the form interface rather than inline editing"],"requires":["Web browser with local storage support","Optional: user account system (if cloud persistence is implemented)"],"input_types":["structured tenant profile data"],"output_types":["stored profile data (JSON or similar format)","profile list/selector interface"],"categories":["memory-knowledge","automation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sharehouse__cap_6","uri":"capability://planning.reasoning.landlord.relevant.information.prioritization.and.emphasis.guidance","name":"landlord-relevant information prioritization and emphasis guidance","description":"Provides contextual guidance or prompting that helps users understand which tenant information matters most to landlords (employment stability, payment history, references, community fit) and emphasizes these factors in the generated cover letter. This may be implemented through form hints, educational content, or prompt engineering that instructs the LLM to weight certain information more heavily. The system likely uses domain knowledge about rental screening criteria to guide both user input and letter generation.","intents":["I want to know what information landlords actually care about when evaluating tenants","I want my cover letter to emphasize the factors that will most influence a landlord's decision","I'm not sure which of my strengths (employment, rental history, references) to highlight"],"best_for":["First-time renters unfamiliar with what landlords prioritize","Renters with non-traditional employment or housing situations who want to frame their circumstances positively","Applicants seeking to understand the rental screening process and optimize their applications"],"limitations":["Guidance is generic and may not apply to specific landlord preferences or property types","No feedback mechanism to learn which factors actually influenced landlord decisions","Cannot account for local rental market variations (e.g., some markets prioritize income verification over narrative)","May inadvertently encourage users to over-emphasize certain factors in ways that sound inauthentic"],"requires":["Domain knowledge about rental screening criteria (likely embedded in prompts or form design)","User willingness to follow guidance and provide relevant information"],"input_types":["user questions or form interactions","tenant profile data"],"output_types":["contextual hints or educational content","weighted emphasis in generated cover letters"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"low","permissions":["Web browser with JavaScript enabled","User-provided tenant information (employment details, rental history, references, personal circumstances)","No API keys or authentication required for free tier","User willingness to provide personal information (employment, rental history, references)","API access to a language model (OpenAI, Anthropic, or similar) — likely handled server-side by Sharehouse","Structured tenant profile data from the form collection step","Sufficient API quota/credits to handle user requests","Sufficient API quota to generate multiple letter versions","User willingness to review and compare multiple outputs","Web browser with clipboard API support (modern browsers)"],"failure_modes":["No integration with major rental platforms (Zillow, Apartments.com, Craigslist) — requires manual copy-paste workflow","Generated letters may sound formulaic or overly polished, potentially raising skepticism from landlords familiar with AI writing patterns","Effectiveness depends entirely on landlord willingness to read and weight cover letters; many landlords rely primarily on credit scores and income verification","No A/B testing or feedback loop to optimize letter quality based on application success rates","Cannot verify or validate user-provided information (employment, rental history), so letters may contain unverified claims","Form-based input may feel restrictive compared to free-form narrative input for users with complex housing situations","No data persistence or account system mentioned — users likely cannot save profiles across sessions","Form validation may reject legitimate but non-standard employment or housing situations","No integration with external data sources (employment verification, credit bureaus) to auto-populate fields","LLM outputs are non-deterministic — same input may generate slightly different letters across invocations","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":0.9,"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":"2026-05-24T12:16:33.096Z","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=sharehouse","compare_url":"https://unfragile.ai/compare?artifact=sharehouse"}},"signature":"QAa4CJxXywwgcVbOA75lHJjuCYAT0qm7mzSy2SOckR+/ODn67Ze1YufDrbKX67iO4pIBoG0Rpe8Ebhoe61XrAA==","signedAt":"2026-06-15T17:04:37.839Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/sharehouse","artifact":"https://unfragile.ai/sharehouse","verify":"https://unfragile.ai/api/v1/verify?slug=sharehouse","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"}}