{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"swimm","slug":"swimm","name":"Swimm","type":"product","url":"https://swimm.io","page_url":"https://unfragile.ai/swimm","categories":["documentation","code-editors"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"swimm__cap_0","uri":"capability://data.processing.analysis.deterministic.code.analysis.for.business.logic.extraction","name":"deterministic-code-analysis-for-business-logic-extraction","description":"Performs static code analysis using proprietary deterministic algorithms (not LLM-based inference) to extract business rules, decision logic, validations, and control flow from source code without executing it. Analyzes code structure to identify conditional branches, loops, data transformations, and policy enforcement points, then maps these to human-readable business concepts. Works across multiple programming languages including COBOL, Java, Python, and C/C++, handling legacy and modern codebases up to 100M+ lines of code.","intents":["I need to understand what business rules are embedded in this legacy COBOL system without reading thousands of lines of code","I want to extract the decision logic and validation rules from our codebase to document them for compliance audits","I need to identify all the places where a specific business policy is enforced across our system"],"best_for":["enterprise teams modernizing legacy systems (mainframe, COBOL, banking)","compliance-heavy organizations needing to document business logic for audits","large teams with complex codebases where knowledge transfer is a bottleneck"],"limitations":["Cannot extract behavior from reflection, metaprogramming, or dynamic code generation — limited to statically analyzable code paths","Does not infer runtime behavior or execution-dependent logic — only deterministic control flow","Accuracy may degrade on heavily obfuscated code or polyglot systems with unclear language boundaries","Processing time for 100M+ LOC codebases is undisclosed — latency characteristics unknown"],"requires":["Source code in Git repository or accessible file system","Supported programming language (COBOL confirmed; others assumed but unverified)","Swimm cloud account or on-premise/air-gapped deployment with sufficient compute"],"input_types":["source code files","git repositories","codebase snapshots"],"output_types":["structured business rule descriptions","control flow diagrams","decision tree representations","policy enforcement mappings"],"categories":["data-processing-analysis","code-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_1","uri":"capability://automation.workflow.auto.generated.markdown.documentation.with.code.sync","name":"auto-generated-markdown-documentation-with-code-sync","description":"Automatically generates documentation in Swimm's `sw.md` Markdown format from analyzed code, embedding code snippet references with 'Smart Tokens' (superscript markers) that maintain bidirectional links to source code. Documentation is stored in the Git repository alongside code, enabling version control and automatic synchronization when code changes. CI/CD integration detects when documentation becomes stale relative to source code and flags it for review, ensuring documentation freshness without manual maintenance.","intents":["I want documentation that automatically updates when code changes, without manual sync overhead","I need to embed live code references in documentation that stay synchronized with actual source","I want to prevent outdated documentation from being merged into the repository"],"best_for":["teams using Git-based workflows who want documentation-as-code","organizations with strict documentation freshness requirements","developers who want to avoid manual documentation maintenance"],"limitations":["CI check mechanism for doc freshness is undisclosed — exact detection and enforcement logic unknown","Smart Tokens require Swimm tooling to maintain — switching to other documentation systems requires manual migration","Markdown export is portable, but Swimm-specific metadata sections may not render correctly in other tools (Confluence, Notion)","Real-time sync latency unknown — documentation may lag code changes by minutes to hours"],"requires":["Git repository with write access","CI/CD pipeline integration (GitHub Actions, GitLab CI, Jenkins, or equivalent)","Swimm account with repository access"],"input_types":["analyzed code from deterministic-code-analysis capability","git commit history"],"output_types":["sw.md Markdown files","rendered HTML documentation","CI/CD check reports"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_10","uri":"capability://planning.reasoning.proof.of.concept.and.enterprise.sales.engagement","name":"proof-of-concept-and-enterprise-sales-engagement","description":"Offers proof-of-concept (POC) programs and flexible project-based pricing for system integrators and enterprises evaluating Swimm. Sales-driven engagement model with custom quotes based on codebase size (lines of code), deployment model (cloud vs. on-premise), and LLM provider (Swimm-hosted vs. customer-managed). No public pricing available — requires contact with sales team for evaluation and pricing.","intents":["I want to evaluate Swimm on our codebase before committing to a purchase","I need custom pricing for our specific deployment model and codebase size","I'm a system integrator and need flexible project-based pricing for my clients"],"best_for":["enterprise customers with large codebases requiring custom evaluation","system integrators and consulting firms building solutions for clients","organizations with specific compliance or deployment requirements"],"limitations":["No self-serve pricing or free tier — requires sales engagement and evaluation period","POC timeline and scope are undisclosed — evaluation period may be weeks or months","Pricing is opaque and not publicly available — difficult to budget or compare costs","Sales-driven model may result in longer sales cycles and higher friction for small teams"],"requires":["Contact with Swimm sales team","Willingness to participate in POC evaluation","Access to representative codebase for evaluation"],"input_types":["codebase information (size, languages, structure)","deployment requirements (cloud, on-premise, air-gapped)","use case and business requirements"],"output_types":["POC evaluation results","custom pricing quote","implementation timeline and scope"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_2","uri":"capability://image.visual.legacy.ui.screen.generation.from.code.analysis","name":"legacy-ui-screen-generation-from-code-analysis","description":"Generates visual representations of user interface screens and workflows from legacy code analysis without requiring runtime execution. Extracts UI structure, field definitions, navigation flows, and screen transitions from source code (particularly effective for COBOL-based systems with embedded screen definitions), then renders these as diagrams and documentation. Enables non-technical stakeholders to understand system behavior and data flows through UI mockups derived purely from static code analysis.","intents":["I need to understand what screens and workflows this legacy COBOL system provides without running it","I want to visualize the user journey through our mainframe application based on code analysis","I need to document the UI structure for modernization planning without reverse-engineering the system"],"best_for":["mainframe and legacy system modernization teams","business analysts and architects who need to understand system behavior without technical depth","teams planning UI/UX modernization of legacy applications"],"limitations":["Works only on code with explicit UI definitions (COBOL screens, form definitions) — does not infer UI from generic business logic","Cannot capture runtime UI behavior, dynamic field population, or conditional screen rendering that depends on runtime state","Accuracy depends on how explicitly UI structure is defined in source code — implicit or framework-based UIs may not be captured","Generated screens show structure only, not styling, colors, or visual design details"],"requires":["Source code with explicit UI definitions (COBOL screen sections, form definitions, etc.)","Supported legacy platform (COBOL confirmed; others unknown)"],"input_types":["analyzed legacy code with UI definitions"],"output_types":["screen mockup diagrams","workflow visualizations","field mapping documentation","navigation flow charts"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_3","uri":"capability://data.processing.analysis.system.mapping.and.dependency.tracking","name":"system-mapping-and-dependency-tracking","description":"Maps codebase structure to business functions and tracks data flows, dependencies, and system boundaries across programs, jobs, and subsystems. Creates a dependency graph showing how code modules interact, where data flows between systems, and which business functions depend on which code components. Enables architects and teams to understand system topology, identify integration points, and plan modernization or refactoring efforts with full visibility into cross-system dependencies.","intents":["I need to understand how all the programs in our mainframe system interact and depend on each other","I want to map which business functions are implemented by which code modules across our codebase","I need to identify all the places where data flows between systems for a modernization project"],"best_for":["enterprise architects planning system modernization or refactoring","teams managing large, complex codebases with unclear dependencies","organizations planning microservices migration or system decomposition"],"limitations":["Dependency tracking is limited to statically analyzable dependencies — cannot detect runtime-only dependencies or plugin-based architectures","Cross-system dependencies may be incomplete if systems communicate via undocumented protocols or message queues","Accuracy depends on code clarity — systems with implicit dependencies or indirect coupling may be misrepresented","Large systems (100M+ LOC) may produce dependency graphs too complex to visualize or navigate effectively"],"requires":["Complete codebase or representative subset in supported languages","Clear module/program boundaries in code structure"],"input_types":["analyzed code from deterministic-code-analysis capability","codebase structure and module definitions"],"output_types":["dependency graphs","system topology diagrams","data flow visualizations","module interaction maps"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_4","uri":"capability://tool.use.integration.swimm.mcp.protocol.context.provision.for.ai.agents","name":"swimm-mcp-protocol-context-provision-for-ai-agents","description":"Exposes analyzed code understanding via the Model Context Protocol (MCP) standard, enabling AI agents and LLM-based tools to consume Swimm's code analysis as structured context. Provides deterministic code insights (business rules, dependencies, flows) to AI agents in a standardized format, allowing agents to make informed decisions during code modernization, refactoring, or generation tasks. Supports both Swimm-hosted LLMs and customer-managed LLM instances (Azure OpenAI, OpenAI Enterprise, or self-hosted models).","intents":["I want my AI code modernization agent to understand the business logic in my legacy system before generating new code","I need to provide context about system dependencies and data flows to an LLM-based refactoring tool","I want to use my own LLM (Azure OpenAI or self-hosted) with Swimm's code analysis for agentic code generation"],"best_for":["teams using AI agents for code modernization or refactoring","organizations with customer-managed LLMs who want to integrate code analysis","enterprises building custom agentic workflows that need code understanding"],"limitations":["MCP context window size and latency are undisclosed — may limit how much code context can be provided per agent request","Requires integration with MCP-compatible AI agents — not all LLM tools support MCP yet","Context quality depends on upstream code analysis accuracy — garbage in, garbage out","Customer-managed LLM support is mentioned but specific integration mechanisms are undisclosed"],"requires":["Swimm account with codebase analyzed","MCP-compatible AI agent or LLM tool","API credentials for customer-managed LLM (if using Azure OpenAI or self-hosted)"],"input_types":["analyzed code context from deterministic-code-analysis capability","agent queries or prompts requesting code understanding"],"output_types":["structured code context in MCP format","business rule summaries","dependency information","code snippet references with Smart Tokens"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_5","uri":"capability://tool.use.integration.ide.integrated.documentation.browsing.and.editing","name":"ide-integrated-documentation-browsing-and-editing","description":"Integrates Swimm documentation directly into IDE environments (VSCode confirmed, others unknown) enabling developers to browse auto-generated documentation, view code-to-doc links, and edit documentation without leaving their editor. Renders `sw.md` files with Smart Token links that jump between documentation and source code, providing seamless navigation between understanding (docs) and implementation (code). Supports inline documentation viewing and editing within the development workflow.","intents":["I want to read documentation about this code module without switching away from my IDE","I need to click from documentation to the actual code it references and back again","I want to update documentation while reviewing code changes in my editor"],"best_for":["developers who spend most time in IDEs and want documentation integrated into their workflow","teams using VSCode as primary editor","organizations where documentation review is part of code review process"],"limitations":["IDE support is limited to VSCode — other IDEs (IntelliJ, Visual Studio, etc.) not mentioned","Smart Token link navigation may be slow or unreliable in large codebases","Editing documentation in IDE may not trigger CI freshness checks immediately","IDE plugin performance impact on large projects is unknown"],"requires":["VSCode 1.80+ (or equivalent version requirement unknown)","Swimm VSCode extension installed","Git repository with sw.md files"],"input_types":["sw.md documentation files","source code files with Smart Token references"],"output_types":["rendered documentation in IDE","code-to-doc navigation links","edited documentation ready for commit"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_6","uri":"capability://automation.workflow.ci.cd.documentation.freshness.checking","name":"ci-cd-documentation-freshness-checking","description":"Integrates with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.) to automatically detect when code changes make documentation stale and blocks merges or flags PRs until documentation is updated. Compares code changes against corresponding documentation to identify mismatches, then reports freshness status as a CI check that can be configured to block or warn. Prevents outdated documentation from being merged into the repository, enforcing documentation-as-code discipline.","intents":["I want to prevent PRs from being merged if the documentation is out of sync with code changes","I need to flag documentation that needs updating when code is modified","I want to enforce a policy that all code changes must have corresponding documentation updates"],"best_for":["teams with strict documentation requirements or compliance mandates","organizations using Git-based workflows with CI/CD pipelines","projects where documentation accuracy is critical (financial, healthcare, regulated industries)"],"limitations":["CI check mechanism and detection algorithm are undisclosed — unclear how it determines staleness","May produce false positives (flagging documentation as stale when it's actually still accurate) or false negatives","Requires CI/CD pipeline integration — not available for teams using other version control systems","Configuration options for blocking vs. warning are unknown"],"requires":["CI/CD pipeline (GitHub Actions, GitLab CI, Jenkins, or equivalent)","Swimm CI integration configured in pipeline","Git repository with sw.md documentation files"],"input_types":["code changes in pull requests","corresponding sw.md documentation files"],"output_types":["CI check status (pass/fail/warning)","freshness reports","documentation update recommendations"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_7","uri":"capability://data.processing.analysis.multi.language.codebase.analysis.with.language.specific.extraction","name":"multi-language-codebase-analysis-with-language-specific-extraction","description":"Analyzes source code across multiple programming languages (COBOL explicitly supported; Java, Python, C/C++ assumed) using language-specific parsing and analysis rules. Extracts business logic, control flow, and dependencies using syntax and semantic understanding tailored to each language's paradigms (e.g., COBOL's procedural structure, Java's OOP patterns, Python's dynamic typing). Handles polyglot systems where multiple languages interact, though accuracy may degrade at language boundaries.","intents":["I need to analyze a codebase that uses multiple programming languages (COBOL, Java, Python, etc.)","I want to understand how business logic is distributed across different languages in our system","I need to document a system that has both legacy COBOL and modern Python components"],"best_for":["enterprises with polyglot systems or multi-language migrations","organizations modernizing legacy systems by adding new languages alongside old ones","teams managing systems with COBOL, Java, Python, C/C++, and other common languages"],"limitations":["Language support is partially documented — COBOL confirmed, others assumed but unverified","Polyglot systems may have incomplete dependency tracking at language boundaries","Language-specific features (e.g., Python decorators, Java annotations) may not be fully analyzed","Accuracy may degrade when languages interact via reflection, FFI, or other indirect mechanisms"],"requires":["Source code in supported programming languages","Clear language boundaries or explicit language declarations in codebase"],"input_types":["source code files in multiple languages","git repositories with mixed-language codebases"],"output_types":["language-specific analysis results","cross-language dependency maps","unified documentation across languages"],"categories":["data-processing-analysis","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_8","uri":"capability://automation.workflow.on.premise.and.air.gapped.deployment.with.data.residency","name":"on-premise-and-air-gapped-deployment-with-data-residency","description":"Supports deployment in on-premise and air-gapped (disconnected) environments where code never leaves the customer's infrastructure. Enables analysis of sensitive codebases (financial systems, healthcare, government) without sending code to cloud services. Supports customer-managed LLM instances (Azure OpenAI, OpenAI Enterprise, self-hosted models) so that both code analysis and AI context provision remain within customer control. Complies with SOC 2 Type II and ISO 27001 standards.","intents":["I need to analyze our codebase without sending it to cloud services due to security/compliance requirements","I want to use Swimm in an air-gapped environment where there's no internet connectivity","I need to ensure all code analysis and LLM processing stays within our infrastructure"],"best_for":["financial institutions and regulated industries with strict data residency requirements","government and defense contractors with classified code","organizations with air-gapped networks or offline systems","enterprises with strict data governance policies"],"limitations":["On-premise deployment requires significant infrastructure and operational overhead — not suitable for small teams","Air-gapped deployment requires manual updates and patches — no automatic updates from cloud","Customer-managed LLM support is mentioned but specific integration and operational requirements are undisclosed","Support and troubleshooting may be more complex in air-gapped environments"],"requires":["On-premise infrastructure (compute, storage, networking)","Customer-managed LLM instance (Azure OpenAI, OpenAI Enterprise, or self-hosted) for AI features","Network isolation or air-gap setup if required","SOC 2 Type II and ISO 27001 compliance certification (Swimm's, not customer's)"],"input_types":["source code in on-premise or air-gapped repository"],"output_types":["documentation and analysis results stored on-premise","MCP context for customer-managed LLMs"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__cap_9","uri":"capability://text.generation.language.markdown.export.and.documentation.portability","name":"markdown-export-and-documentation-portability","description":"Exports auto-generated documentation in standard Markdown format (`sw.md` files) that can be read, edited, and rendered in any Markdown-compatible tool (GitHub, GitLab, VSCode, Notion, Confluence, etc.). Documentation is stored in Git repositories as first-class artifacts, enabling version control, branching, and merging alongside code. Provides portability and reduces vendor lock-in by using open standards, though Swimm-specific metadata sections (Smart Tokens, analysis metadata) may not render correctly in other tools.","intents":["I want to export documentation from Swimm and use it in other tools like Confluence or Notion","I need to ensure documentation isn't locked into Swimm's proprietary format","I want to store documentation in Git alongside code for version control"],"best_for":["teams using multiple documentation tools and wanting portability","organizations with existing Markdown-based documentation workflows","projects where documentation-as-code is a requirement"],"limitations":["Swimm-specific metadata (Smart Tokens, analysis metadata) may not render or function in other tools","Bidirectional sync with other tools (Confluence, Notion) is not mentioned — export is likely one-way","Markdown export may lose formatting or interactive features when imported into other systems","Manual migration of Smart Token links to other systems would be required when switching tools"],"requires":["Swimm account with generated documentation","Git repository or file system access to export to"],"input_types":["sw.md documentation files from Swimm"],"output_types":["standard Markdown files (.md)","git commits with documentation"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"swimm__headline","uri":"capability://documentation.ai.powered.documentation.generator.for.codebases","name":"ai-powered documentation generator for codebases","description":"Swimm is an AI-powered tool that auto-generates and maintains documentation directly from your codebase, ensuring it stays current with code changes and integrates seamlessly into your development workflow.","intents":["best AI documentation tool","documentation generator for codebases","auto-sync documentation for developers","integrated documentation solutions for IDEs","code documentation that updates automatically"],"best_for":["developers working with complex code","teams needing up-to-date documentation"],"limitations":[],"requires":[],"input_types":["various programming languages"],"output_types":["Markdown documentation"],"categories":["documentation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":55,"verified":false,"data_access_risk":"high","permissions":["Source code in Git repository or accessible file system","Supported programming language (COBOL confirmed; 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