{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_allcancode","slug":"allcancode","name":"Allcancode","type":"product","url":"https://www.allcancode.com","page_url":"https://unfragile.ai/allcancode","categories":["app-builders"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_allcancode__cap_0","uri":"capability://data.processing.analysis.natural.language.product.requirement.parsing.and.normalization","name":"natural language product requirement parsing and normalization","description":"Converts unstructured product descriptions, user stories, and feature lists into normalized requirement vectors through LLM-based semantic parsing. The system extracts entities (features, integrations, user roles, platforms) and maps them to a standardized taxonomy, enabling downstream cost calculation models to operate on consistent input representations regardless of how founders phrase their ideas.","intents":["I want to describe my product idea in plain English without worrying about technical terminology","I need the system to understand what I mean even if I'm vague about technical details","I want to ensure my requirements are interpreted consistently before cost estimation begins"],"best_for":["Non-technical founders who lack vocabulary for precise technical specification","Product managers transitioning from business language to development requirements","Teams iterating on product scope and needing quick re-estimates as requirements shift"],"limitations":["Ambiguous or contradictory requirements may be normalized incorrectly, leading to downstream estimate errors","Domain-specific jargon outside the training data (e.g., niche fintech or biotech terminology) may be misinterpreted","No interactive clarification loop — system makes single-pass interpretation without asking for disambiguation"],"requires":["Natural language input (English primary, other languages unknown)","Internet connection for LLM API calls","Minimum 50-100 characters of descriptive text for reliable parsing"],"input_types":["unstructured text","feature lists","user stories","product descriptions"],"output_types":["structured requirement vectors","normalized feature taxonomy","extracted metadata (platforms, integrations, user roles)"],"categories":["data-processing-analysis","natural-language-understanding"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_allcancode__cap_1","uri":"capability://data.processing.analysis.multi.layer.cost.decomposition.and.estimation","name":"multi-layer cost decomposition and estimation","description":"Breaks product development into discrete cost layers (frontend, backend, infrastructure, third-party integrations, QA, DevOps) using a hierarchical estimation model. Each layer applies learned cost coefficients based on feature complexity, technology choices, and scope signals extracted from requirements. The system aggregates sub-estimates with uncertainty bands rather than point estimates, surfacing cost ranges that reflect estimation confidence.","intents":["I need to understand where development costs are concentrated (frontend vs backend vs infrastructure)","I want a cost range with confidence intervals, not a false-precision single number","I need to see how costs scale if I add or remove features"],"best_for":["Founders preparing fundraising pitch decks and investor materials","Product managers building business cases and ROI models","Teams evaluating build-vs-buy decisions with cost sensitivity analysis"],"limitations":["Estimates are trained on historical project data with unknown composition — may not reflect current market rates or regional variations","No visibility into cost drivers (e.g., why backend is 40% of total) — black-box output limits negotiation or optimization","Ignores team experience level, tech debt, and integration complexity that experienced developers would flag as cost multipliers","Cannot account for regulatory compliance costs (HIPAA, GDPR, PCI-DSS) that vary by domain"],"requires":["Parsed requirement vectors from upstream NLP capability","Implicit access to historical cost dataset (not user-provided)","No explicit API key or configuration needed"],"input_types":["normalized requirement vectors","feature complexity signals","technology stack indicators"],"output_types":["cost breakdown by layer (frontend, backend, infrastructure, etc.)","cost ranges with confidence bands","cost per feature or cost per user-story"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_allcancode__cap_2","uri":"capability://planning.reasoning.timeline.estimation.with.dependency.aware.scheduling","name":"timeline estimation with dependency-aware scheduling","description":"Estimates project duration by modeling task dependencies, parallelization opportunities, and critical path constraints. The system maps features to development phases (discovery, design, backend, frontend, integration, QA, deployment) and calculates timeline based on task sequencing and team capacity assumptions. Outputs timeline ranges reflecting uncertainty in estimation and potential for scope creep or technical blockers.","intents":["I need to know how long my MVP will take to build, not just the cost","I want to understand which features are on the critical path and which can be parallelized","I need a timeline range that accounts for uncertainty, not a false-precision date"],"best_for":["Founders planning product launch windows and go-to-market timing","Investors evaluating time-to-revenue and competitive urgency","Teams making build-vs-partner decisions based on speed-to-market"],"limitations":["Assumes standard team composition and productivity — does not account for team experience, onboarding time, or context-switching overhead","No visibility into which features are on critical path or which can be parallelized — output is aggregate timeline only","Cannot model external dependencies (third-party API availability, regulatory approval, vendor integrations) that often extend timelines","Ignores rework and iteration cycles typical in early-stage products"],"requires":["Parsed requirement vectors with feature complexity signals","Implicit assumptions about team size and productivity (not configurable)"],"input_types":["normalized requirement vectors","feature list with complexity indicators"],"output_types":["timeline estimate in weeks/months","timeline range with confidence bands","phase breakdown (discovery, design, development, QA, launch)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_allcancode__cap_3","uri":"capability://planning.reasoning.technology.stack.recommendation.and.cost.impact.analysis","name":"technology stack recommendation and cost impact analysis","description":"Suggests technology choices (frontend framework, backend language, database, hosting platform) based on feature requirements and cost optimization. The system models cost implications of each stack choice (e.g., serverless vs managed containers, SQL vs NoSQL) and surfaces tradeoffs between development speed, operational complexity, and long-term maintenance costs. Recommendations are based on learned patterns from historical projects with similar feature profiles.","intents":["I don't know what tech stack to choose — what would you recommend for my product?","How much more expensive is it to use technology X vs Y?","What are the long-term operational costs of different architecture choices?"],"best_for":["Non-technical founders who need guidance on technology choices without hiring a CTO","Product managers evaluating build-vs-buy or monolith-vs-microservices decisions","Teams optimizing for cost vs development speed tradeoffs"],"limitations":["Recommendations are based on historical project data — may not reflect emerging technologies or niche stacks optimal for specific domains","No consideration of team expertise or existing infrastructure — recommends generic optimal stacks rather than team-specific choices","Cost models for hosting and operations are approximate and may not reflect actual cloud pricing or reserved instance discounts","Cannot account for regulatory or compliance requirements that mandate specific technologies (e.g., on-premise deployment for healthcare)"],"requires":["Parsed requirement vectors with feature complexity and integration signals","Implicit access to historical tech stack and cost data"],"input_types":["normalized requirement vectors","feature list with integration requirements"],"output_types":["recommended technology stack (frontend, backend, database, hosting)","cost comparison across alternative stacks","tradeoff analysis (development speed vs operational complexity vs cost)"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_allcancode__cap_4","uri":"capability://planning.reasoning.interactive.cost.and.timeline.sensitivity.analysis","name":"interactive cost and timeline sensitivity analysis","description":"Allows founders to adjust product scope (add/remove features, change complexity, modify integrations) and instantly recalculates cost and timeline estimates. The system models how changes propagate through the cost and timeline models, surfacing which features have highest cost-per-value and which are critical path blockers. Enables what-if analysis (e.g., 'what if we launch MVP without payment processing?') without re-running full estimation.","intents":["I want to see how costs change if I remove feature X or simplify feature Y","Which features should I cut to hit my budget or timeline target?","What's the cost difference between MVP and full product?"],"best_for":["Founders iterating on product scope and budget constraints","Investors and stakeholders exploring cost-benefit of feature prioritization","Teams making scope-vs-timeline-vs-budget tradeoff decisions"],"limitations":["Assumes linear or simple multiplicative cost models — does not capture non-linear complexity (e.g., payment processing is cheap alone but expensive with multi-currency support)","No persistence of scenarios — cannot save and compare multiple what-if analyses","Changes to scope do not recalculate team composition or hiring costs — assumes fixed team size","Cannot model dependencies between features (e.g., removing auth affects multiple features)"],"requires":["Initial cost and timeline estimates from upstream capabilities","Interactive UI with real-time recalculation (web-based or native app)"],"input_types":["scope adjustments (add/remove features, change complexity)","budget or timeline constraints"],"output_types":["updated cost and timeline estimates","cost-per-feature breakdown","sensitivity analysis (which features have highest cost impact)"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_allcancode__cap_5","uri":"capability://text.generation.language.fundraising.ready.cost.and.timeline.report.generation","name":"fundraising-ready cost and timeline report generation","description":"Generates formatted, investor-ready documents (PDF, slide deck, or HTML) that present cost estimates, timeline projections, and technology recommendations in a professional format suitable for pitch decks and investor materials. Reports include executive summary, detailed cost breakdown, timeline Gantt chart, risk assessment, and assumptions documentation. Formatting and structure are optimized for investor consumption and due diligence.","intents":["I need a professional cost estimate document for my investor pitch deck","I want to document my assumptions and methodology for investor due diligence","I need a timeline projection that looks credible in a pitch deck"],"best_for":["Founders preparing Series A/B pitch decks and investor materials","Teams documenting product development plans for board meetings","Companies conducting internal due diligence or business case reviews"],"limitations":["Reports present AI-generated estimates as authoritative without caveats about accuracy or limitations","No ability to customize report format or branding for specific investor preferences","Assumptions documentation is generic (e.g., 'assumes standard team composition') rather than specific to the product or team","Reports do not include risk mitigation strategies or contingency planning"],"requires":["Completed cost and timeline estimates from upstream capabilities","Export/report generation capability (PDF, HTML, or slide format)"],"input_types":["cost breakdown by layer","timeline estimates and phase breakdown","technology recommendations","product requirements and scope"],"output_types":["PDF report","HTML report","PowerPoint/slide deck compatible format","executive summary document"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Natural language input (English primary, other languages unknown)","Internet connection for LLM API calls","Minimum 50-100 characters of descriptive text for reliable parsing","Parsed requirement vectors from upstream NLP capability","Implicit access to historical cost dataset (not user-provided)","No explicit API key or configuration needed","Parsed requirement vectors with feature complexity signals","Implicit assumptions about team size and productivity (not configurable)","Parsed requirement vectors with feature complexity and integration signals","Implicit access to historical tech stack and cost data"],"failure_modes":["Ambiguous or contradictory requirements may be normalized incorrectly, leading to downstream estimate errors","Domain-specific jargon outside the training data (e.g., niche fintech or biotech terminology) may be misinterpreted","No interactive clarification loop — system makes single-pass interpretation without asking for disambiguation","Estimates are trained on historical project data with unknown composition — may not reflect current market rates or regional variations","No visibility into cost drivers (e.g., why backend is 40% of total) — black-box output limits negotiation or optimization","Ignores team experience level, tech debt, and integration complexity that experienced developers would flag as cost multipliers","Cannot account for regulatory compliance costs (HIPAA, GDPR, PCI-DSS) that vary by domain","Assumes standard team composition and productivity — does not account for team experience, onboarding time, or context-switching overhead","No visibility into which features are on critical path or which can be parallelized — output is aggregate timeline only","Cannot model external dependencies (third-party API availability, regulatory approval, vendor integrations) that often extend timelines","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":"2026-05-24T12:16:29.133Z","last_scraped_at":"2026-04-05T13:23:42.561Z","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=allcancode","compare_url":"https://unfragile.ai/compare?artifact=allcancode"}},"signature":"6g8J7+8nj7GYgWeSBKMyOZ8jGZt4L+pAY/TCARtynNfe0GudKv6Szfte+fRV95mdVwWkGpIZBTtdm5R4IxBDDg==","signedAt":"2026-06-19T19:08:48.468Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/allcancode","artifact":"https://unfragile.ai/allcancode","verify":"https://unfragile.ai/api/v1/verify?slug=allcancode","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"}}