{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_docuo","slug":"docuo","name":"Docuo","type":"product","url":"https://www.spreading.ai","page_url":"https://unfragile.ai/docuo","categories":["documentation"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_docuo__cap_0","uri":"capability://code.generation.editing.ai.powered.documentation.content.auto.generation","name":"ai-powered documentation content auto-generation","description":"Automatically generates documentation content from source code, API specifications, and codebase analysis using LLM-based extraction and synthesis. The system analyzes code structure, function signatures, and existing comments to produce initial documentation drafts, reducing manual writing overhead. This works by parsing source files, extracting semantic information, and feeding it to language models that generate contextually appropriate documentation sections with proper formatting and structure.","intents":["I want to automatically generate API documentation from my codebase without manually writing every endpoint description","I need to keep documentation in sync with code changes without dedicating a team member to documentation maintenance","I want to generate multiple documentation variants (quick-start, deep-dive, API reference) from a single source of truth"],"best_for":["SaaS companies with rapidly evolving APIs and SDKs","Open-source projects with limited documentation bandwidth","Developer tool teams shipping frequent feature updates"],"limitations":["Generated content requires human review and editing — LLM outputs may contain inaccuracies or miss domain-specific context","Requires well-structured, commented code to produce high-quality documentation — legacy codebases with minimal comments produce lower-quality outputs","Cannot automatically detect breaking changes or deprecated APIs without explicit code annotations"],"requires":["Source code repository access (Git, GitHub, GitLab, or direct file upload)","API key for LLM provider (OpenAI, Anthropic, or self-hosted model)","Code files in supported languages (JavaScript, Python, TypeScript, Java, Go, Rust minimum)"],"input_types":["source code files","OpenAPI/Swagger specifications","JSDoc/docstring comments","function signatures"],"output_types":["markdown documentation","HTML pages","structured documentation metadata","API reference tables"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_1","uri":"capability://automation.workflow.interactive.documentation.customization.without.code","name":"interactive documentation customization without code","description":"Provides a visual editor and configuration system that allows non-developers to customize documentation layout, branding, navigation structure, and user experience without writing code or deploying changes. Uses a drag-and-drop interface combined with CSS variable overrides and component configuration to enable responsive, branded documentation sites. The system stores customization preferences as configuration objects that are applied at render time, allowing instant preview and A/B testing of different layouts.","intents":["I want to match our documentation site's branding to our product without hiring a developer or forking a static site generator","I need to reorganize documentation structure and navigation for different user personas (beginners vs advanced users) without rebuilding the site","I want to test different documentation layouts and measure which one reduces support tickets"],"best_for":["Product managers and technical writers who own documentation strategy","Marketing teams creating customer-facing knowledge bases","Non-technical founders building documentation as part of product launch"],"limitations":["Customization is constrained to pre-built component library — highly custom layouts requiring bespoke HTML/CSS are not supported","Performance may degrade with very large documentation sites (10,000+ pages) due to client-side rendering of customization layers","No built-in version control for customization changes — reverting to previous layouts requires manual reconfiguration"],"requires":["Docuo account with editor permissions","Web browser with modern CSS support (Chrome 90+, Firefox 88+, Safari 14+)","Brand assets (logo, color palette, fonts) in standard formats (PNG, SVG, WOFF2)"],"input_types":["documentation markdown or HTML","brand color codes (hex, RGB)","custom fonts (WOFF2, TTF)","logo images (SVG, PNG)"],"output_types":["customized documentation site","CSS configuration","responsive HTML layouts","preview URLs for testing"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_10","uri":"capability://automation.workflow.integration.with.development.workflows.and.ci.cd.pipelines","name":"integration with development workflows and ci/cd pipelines","description":"Integrates documentation generation and deployment with development workflows through Git webhooks, CI/CD pipeline integration, and API-based content updates. The system can automatically regenerate documentation when code changes are pushed, deploy documentation updates as part of release pipelines, and sync documentation with external sources (GitHub, GitLab, Bitbucket). This enables documentation to be treated as code and versioned alongside product releases.","intents":["I want documentation to update automatically when code is merged to main branch","I need to include documentation deployment as part of our release pipeline","I want to maintain documentation in Git alongside code and sync it to Docuo"],"best_for":["Engineering teams with mature CI/CD practices","Products with frequent releases and documentation updates","Teams wanting to treat documentation as code"],"limitations":["Requires Git repository access and CI/CD pipeline configuration — adds setup complexity","Automatic documentation generation may produce incorrect or incomplete content that requires manual review","Tight coupling between code and documentation can create bottlenecks if documentation review is slow"],"requires":["Git repository (GitHub, GitLab, Bitbucket)","CI/CD platform (GitHub Actions, GitLab CI, Jenkins, etc.)","Docuo API key for authentication","Documentation source files in Git repository"],"input_types":["Git webhooks (push, pull request events)","CI/CD pipeline triggers","API requests with documentation content","source code files"],"output_types":["deployed documentation updates","deployment status notifications","documentation version tags","release notes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_2","uri":"capability://memory.knowledge.dynamic.content.personalization.by.user.segment","name":"dynamic content personalization by user segment","description":"Delivers different documentation content, navigation paths, and UI elements to different user segments (e.g., beginners vs power users, free vs enterprise customers) based on user attributes, behavior, or explicit segment assignment. The system maintains multiple content variants and uses conditional rendering logic to show/hide sections, reorder navigation, and highlight relevant features. This is implemented through a rules engine that evaluates user context at request time and applies content filtering and reordering based on segment-specific configurations.","intents":["I want to show enterprise customers advanced configuration options while hiding them from free-tier users to reduce cognitive load","I need to create a beginner-friendly documentation path that hides advanced topics until users are ready","I want to surface different features based on which product tier a customer is using"],"best_for":["SaaS platforms with tiered pricing models","Products with significant feature variance between user segments","Teams using documentation to drive product adoption and reduce churn"],"limitations":["Requires explicit user identification and segment assignment — cannot personalize for anonymous visitors without additional tracking","Maintaining multiple content variants increases documentation maintenance burden if not properly structured","Personalization rules can become complex and difficult to debug if segment definitions overlap or conflict"],"requires":["User authentication system or segment identifier (user ID, email domain, subscription tier)","Docuo integration with identity provider (OAuth, SAML, or API-based user sync)","Segment definitions configured in Docuo dashboard"],"input_types":["user attributes (tier, role, company, signup date)","behavioral signals (pages viewed, features used)","custom segment rules (JSON or UI-based configuration)"],"output_types":["personalized documentation pages","segment-specific navigation menus","filtered content sections","analytics on segment engagement"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_3","uri":"capability://search.retrieval.ai.powered.semantic.search.across.documentation","name":"ai-powered semantic search across documentation","description":"Provides full-text and semantic search capabilities that understand user intent and return relevant documentation sections even when exact keyword matches don't exist. The system embeds documentation content into vector space using LLM-based embeddings, enabling similarity-based retrieval that captures semantic relationships between queries and content. Search results are ranked by relevance using both keyword matching and semantic similarity, with optional re-ranking based on user engagement metrics or explicit relevance feedback.","intents":["I want users to find answers even when they don't know the exact terminology used in our documentation","I need to understand what users are searching for to identify documentation gaps","I want to reduce support tickets by making documentation more discoverable through intelligent search"],"best_for":["Large documentation sites (500+ pages) where traditional search is insufficient","Products with specialized terminology that users may not know","Teams focused on reducing support burden through self-service discovery"],"limitations":["Semantic search requires embedding generation which adds latency (typically 100-500ms per query) compared to keyword-only search","Embedding quality depends on documentation quality — poorly written or sparse documentation produces lower-quality embeddings","Search index must be regenerated when documentation is updated, introducing potential staleness windows"],"requires":["Docuo account with search enabled","Documentation content in supported formats (markdown, HTML, plain text)","Embedding model access (OpenAI, Anthropic, or self-hosted model)","Search index storage (included in Docuo platform)"],"input_types":["natural language search queries","documentation pages (markdown, HTML)","user feedback on search result relevance"],"output_types":["ranked search results with snippets","relevance scores","search analytics (popular queries, zero-result queries)","suggested related articles"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_4","uri":"capability://automation.workflow.automated.documentation.versioning.and.change.tracking","name":"automated documentation versioning and change tracking","description":"Automatically tracks changes to documentation content, maintains version history, and enables rollback to previous versions without manual intervention. The system creates snapshots of documentation state at configurable intervals or on-demand, stores diffs between versions, and provides a timeline view showing what changed, when, and by whom. This is implemented through a version control layer that sits above the documentation storage, tracking content mutations and maintaining a complete audit trail.","intents":["I want to see what changed in our documentation and revert bad edits without losing work","I need to maintain a changelog showing documentation updates alongside product releases","I want to audit who made changes to critical documentation sections"],"best_for":["Teams with multiple documentation editors who need change visibility","Regulated industries requiring documentation audit trails","Products with frequent documentation updates tied to releases"],"limitations":["Version history storage grows linearly with documentation size and change frequency — very active documentation sites may require storage optimization","Rollback is content-only — cannot rollback customization changes or configuration separately from content","No built-in merge conflict resolution for simultaneous edits to the same section"],"requires":["Docuo account with versioning enabled","Documentation stored in Docuo platform (not external Git repositories)","Editor permissions for users who need to view version history"],"input_types":["documentation content changes","user identity (for audit trail)","rollback target version"],"output_types":["version history timeline","diff views showing changes","rollback confirmations","audit logs with user attribution"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_5","uri":"capability://text.generation.language.multi.language.documentation.generation.and.management","name":"multi-language documentation generation and management","description":"Automatically generates and manages documentation in multiple languages using machine translation combined with human review workflows. The system detects the primary documentation language, generates translations using LLM-based translation models, and provides a workflow for translators to review and refine translations before publication. Translations are stored separately but linked to the source content, enabling synchronized updates where changes to source content trigger translation regeneration.","intents":["I want to provide documentation in multiple languages without hiring translators for every language","I need to keep translations in sync with source documentation as we update features","I want to support global users without maintaining separate documentation sites per language"],"best_for":["Global SaaS companies serving non-English-speaking markets","Open-source projects with international communities","Products expanding into new geographic markets"],"limitations":["Machine translation quality varies by language pair and domain — technical terminology may be mistranslated and require manual correction","Maintaining translation workflows adds overhead — requires translator review and approval before publication","Some languages may not be supported by the underlying translation model, requiring fallback to human translation"],"requires":["Docuo account with translation features enabled","Source documentation in supported language","Translation model access (OpenAI, Anthropic, or self-hosted)","Translator accounts for review workflows (optional but recommended)"],"input_types":["source documentation in primary language","target language codes (ISO 639-1 format)","translator feedback and corrections","terminology glossaries (optional)"],"output_types":["translated documentation pages","language-specific site URLs or subdirectories","translation status reports","translation memory for consistency"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_6","uri":"capability://data.processing.analysis.analytics.and.engagement.tracking.for.documentation","name":"analytics and engagement tracking for documentation","description":"Tracks user engagement with documentation including page views, search queries, time spent, scroll depth, and user flow patterns. The system collects behavioral data through client-side instrumentation, aggregates it server-side, and provides dashboards showing which documentation sections are most/least used, where users drop off, and which search queries return zero results. This data is used to identify documentation gaps and prioritize content improvements based on actual user behavior.","intents":["I want to know which documentation pages are actually being read and which are being ignored","I need to identify documentation gaps by seeing what users search for but don't find","I want to measure if documentation improvements actually reduce support tickets"],"best_for":["Product teams using documentation as a support cost reduction lever","Content teams optimizing documentation ROI","Companies with data-driven documentation strategies"],"limitations":["Analytics require user identification or session tracking — cannot track anonymous visitors without additional tracking mechanisms","Correlation between documentation engagement and support ticket reduction requires external data integration","Privacy regulations (GDPR, CCPA) may restrict what behavioral data can be collected and stored"],"requires":["Docuo account with analytics enabled","User identification system or session tracking enabled","Privacy policy updated to disclose analytics collection","Optional: integration with support ticketing system for correlation analysis"],"input_types":["page view events","search queries","user scroll and interaction events","time-on-page metrics"],"output_types":["engagement dashboards","page popularity rankings","search query reports","user flow visualizations","zero-result search reports"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_7","uri":"capability://code.generation.editing.interactive.code.examples.and.embedded.runnable.snippets","name":"interactive code examples and embedded runnable snippets","description":"Embeds executable code examples directly in documentation that users can run, modify, and experiment with without leaving the documentation site. The system supports multiple languages and runtimes (JavaScript, Python, etc.) and can execute code in sandboxed environments or against live APIs. Code examples are syntax-highlighted, version-controlled with documentation, and can be automatically generated from test suites or example files in the codebase.","intents":["I want users to learn by doing — running code examples directly in documentation rather than copying and pasting into their own environment","I need to keep code examples in sync with actual API behavior by running them against live endpoints","I want to reduce support questions by providing interactive examples that demonstrate common use cases"],"best_for":["Developer tool and API documentation","Educational content and tutorials","Products with complex configuration or integration patterns"],"limitations":["Executing arbitrary code requires sandboxing which adds latency (typically 1-5 seconds per execution) and may timeout for long-running operations","Not all code can be safely executed in a sandbox — code requiring local file system access or system calls will fail","Maintaining runnable examples requires keeping them in sync with API changes and library versions"],"requires":["Docuo account with code execution features enabled","Supported runtime environment (Node.js, Python, etc.)","Optional: API credentials for examples that call live endpoints","Sandbox infrastructure (included in Docuo platform or external)"],"input_types":["code snippets in supported languages","API endpoints for live execution","example input data and parameters","test cases for validation"],"output_types":["rendered code with syntax highlighting","execution results and output","error messages and debugging information","modified code after user edits"],"categories":["code-generation-editing","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_8","uri":"capability://automation.workflow.documentation.feedback.and.community.contribution.workflows","name":"documentation feedback and community contribution workflows","description":"Enables users to provide feedback on documentation quality, suggest improvements, and contribute corrections through built-in workflows. The system collects feedback (thumbs up/down, comments, edit suggestions) at the page level, routes feedback to appropriate team members, and provides workflows for reviewing and merging community contributions. This is implemented through a feedback collection layer that captures user input and integrates with notification and review systems.","intents":["I want to know when documentation is confusing or outdated from the people actually using it","I want to crowdsource documentation improvements from power users and community members","I need a lightweight way to collect and prioritize documentation improvements without managing a separate issue tracker"],"best_for":["Open-source projects with active communities","SaaS companies wanting to leverage customer feedback for documentation","Teams with limited documentation resources"],"limitations":["Feedback quality varies — not all suggestions are valid or actionable","Managing community contributions requires review overhead and clear contribution guidelines","Spam and off-topic feedback may require moderation"],"requires":["Docuo account with feedback features enabled","Notification system configured (email, Slack, etc.)","Optional: GitHub integration for syncing feedback to issues"],"input_types":["user feedback (ratings, comments)","suggested edits or corrections","community contributions (markdown, code)"],"output_types":["feedback aggregation dashboards","notification alerts for new feedback","contribution review workflows","merged contributions"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_docuo__cap_9","uri":"capability://automation.workflow.documentation.site.performance.optimization.and.cdn.delivery","name":"documentation site performance optimization and cdn delivery","description":"Automatically optimizes documentation site performance through image compression, code splitting, lazy loading, and global CDN distribution. The system analyzes documentation assets, applies optimization techniques, and serves content from geographically distributed edge servers to minimize latency for users worldwide. Performance metrics are tracked and reported through dashboards showing page load times, Core Web Vitals, and optimization impact.","intents":["I want documentation to load fast for users worldwide without manually optimizing assets","I need to ensure documentation meets Core Web Vitals standards for SEO and user experience","I want to understand how documentation performance impacts user engagement and support ticket volume"],"best_for":["Global SaaS companies serving users across multiple regions","Teams focused on user experience and SEO","Products where documentation is a critical user journey"],"limitations":["CDN caching can introduce staleness — documentation updates may take time to propagate globally","Performance optimization is automatic but may not be optimal for all content types (e.g., very large embedded media)","Some optimizations may impact functionality (e.g., lazy loading may delay content visibility)"],"requires":["Docuo account with performance optimization enabled","Documentation hosted on Docuo platform (not external CDN)"],"input_types":["documentation content and assets","performance optimization preferences","geographic region targeting"],"output_types":["optimized documentation site","performance metrics dashboards","Core Web Vitals reports","optimization recommendations"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Source code repository access (Git, GitHub, GitLab, or direct file upload)","API key for LLM provider (OpenAI, Anthropic, or self-hosted model)","Code files in supported languages (JavaScript, Python, TypeScript, Java, Go, Rust minimum)","Docuo account with editor permissions","Web browser with modern CSS support (Chrome 90+, Firefox 88+, Safari 14+)","Brand assets (logo, color palette, fonts) in standard formats (PNG, SVG, WOFF2)","Git repository (GitHub, GitLab, Bitbucket)","CI/CD platform (GitHub Actions, GitLab CI, Jenkins, etc.)","Docuo API key for authentication","Documentation source files in Git repository"],"failure_modes":["Generated content requires human review and editing — LLM outputs may contain inaccuracies or miss domain-specific context","Requires well-structured, commented code to produce high-quality documentation — legacy codebases with minimal comments produce lower-quality outputs","Cannot automatically detect breaking changes or deprecated APIs without explicit code annotations","Customization is constrained to pre-built component library — highly custom layouts requiring bespoke HTML/CSS are not supported","Performance may degrade with very large documentation sites (10,000+ pages) due to client-side rendering of customization layers","No built-in version control for customization changes — reverting to previous layouts requires manual reconfiguration","Requires Git repository access and CI/CD pipeline configuration — adds setup complexity","Automatic documentation generation may produce incorrect or incomplete content that requires manual review","Tight coupling between code and documentation can create bottlenecks if documentation review is slow","Requires explicit user identification and segment assignment — cannot personalize for anonymous visitors without additional tracking","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.2,"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":"2026-05-24T12:16:30.283Z","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=docuo","compare_url":"https://unfragile.ai/compare?artifact=docuo"}},"signature":"tcfCoZFOidhe/hUZFs+uq7MxRw6YU8hVFK3/IhjILXaV7s9C5A+tlYp6obQTNgJ40BTxM6RtLR1eKlmwktIoAQ==","signedAt":"2026-06-19T21:30:46.498Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/docuo","artifact":"https://unfragile.ai/docuo","verify":"https://unfragile.ai/api/v1/verify?slug=docuo","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"}}