{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"mabl","slug":"mabl","name":"Mabl","type":"platform","url":"https://www.mabl.com","page_url":"https://unfragile.ai/mabl","categories":["testing-quality","app-builders"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"mabl__cap_0","uri":"capability://code.generation.editing.low.code.end.to.end.test.authoring.with.natural.language.generation","name":"low-code end-to-end test authoring with natural language generation","description":"Mabl converts natural language descriptions and Jira tickets into executable end-to-end test definitions through an AI-powered low-code interface, eliminating the need for manual test script coding. The platform parses user intent from text input and generates test steps that interact with web applications through browser automation, storing test artifacts in Mabl's proprietary format for cloud execution.","intents":["I want to create E2E tests without writing code or learning Selenium/Playwright","I need to generate test cases directly from Jira issue descriptions to keep tests in sync with requirements","I want to author tests in a visual interface that non-technical QA engineers can understand and modify"],"best_for":["QA teams without software development experience","enterprises wanting to reduce test automation bottlenecks","teams using Jira as source of truth for test requirements"],"limitations":["Tests are locked to Mabl's proprietary format with no standard export mechanism documented","Natural language generation accuracy depends on clarity of input descriptions; ambiguous requirements may produce incorrect test steps","Low-code interface abstracts away fine-grained control available in code-first frameworks like Playwright or Cypress","No support for custom test logic beyond Mabl's predefined step library"],"requires":["Mabl platform account (free tier available)","Web application with stable DOM selectors or visual elements","Jira integration enabled for ticket-based test generation"],"input_types":["natural language text descriptions","Jira ticket content","user interaction recordings"],"output_types":["executable test definitions","test step sequences","test execution reports"],"categories":["code-generation-editing","test-automation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_1","uri":"capability://automation.workflow.agentic.auto.healing.test.recovery.with.runtime.failure.classification","name":"agentic auto-healing test recovery with runtime failure classification","description":"Mabl's runtime executes tests with embedded AI agents that detect failures in real-time and automatically apply healing strategies (element selector updates, retry logic, DOM structure adaptation) without human intervention. The platform classifies failures into categories (real regression, app change, environmental noise) using machine learning models trained on 8+ years of test execution data, enabling intelligent recovery decisions.","intents":["I want tests to automatically recover from minor UI changes without manual maintenance","I need to distinguish between real bugs and flaky tests caused by timing or environment issues","I want to reduce the manual effort of updating selectors when the application UI changes"],"best_for":["teams with rapidly evolving UI/UX where selector brittleness is a major pain point","enterprises running high-frequency test suites where manual failure triage is expensive","organizations wanting to reduce test maintenance overhead by 40-60%"],"limitations":["Auto-healing works best for CSS/XPath selector changes; complex DOM restructuring may exceed recovery capabilities","Failure classification accuracy depends on historical test data; new applications with limited execution history may misclassify failures","Recovery strategies are limited to Mabl's predefined healing library; custom recovery logic is not supported","Healing decisions are opaque to users; no audit trail of what changes were applied to recover a test"],"requires":["Mabl platform account with cloud execution enabled","Sufficient historical test execution data (minimum 50+ runs recommended for accurate ML classification)","Web application with stable semantic structure (healing fails if DOM is completely restructured)"],"input_types":["test execution failures","DOM snapshots","error logs"],"output_types":["healed test execution results","failure classification labels","recovery action logs"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_10","uri":"capability://tool.use.integration.slack.and.microsoft.teams.notifications.with.failure.alerts.and.recovery.proposals","name":"slack and microsoft teams notifications with failure alerts and recovery proposals","description":"Mabl sends real-time notifications to Slack and Microsoft Teams when tests fail, including failure summaries, affected features, and AI-generated recovery proposals. The platform uses machine learning to classify failures and suggest remediation steps, enabling teams to respond to test failures without accessing the Mabl dashboard.","intents":["I want to be notified immediately when critical tests fail","I need to understand why a test failed without logging into Mabl","I want AI-generated suggestions for how to fix a failing test"],"best_for":["teams with on-call rotations or rapid incident response requirements","organizations wanting to reduce mean time to resolution (MTTR) for test failures","enterprises using Slack or Teams as primary communication platform"],"limitations":["Notifications are limited to failure alerts; no support for success notifications or custom event types","Recovery proposals are AI-generated and may be inaccurate; manual verification is required","Notifications are sent to channels; no support for direct messages or user-specific routing","Notification filtering is limited to test severity; no support for custom routing rules based on test tags or owners"],"requires":["Slack or Microsoft Teams workspace","Mabl platform account with notification integration enabled","Slack/Teams bot configured with appropriate permissions"],"input_types":["test failure events","failure classification data","recovery analysis"],"output_types":["slack/teams messages","failure summaries","recovery proposals"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_11","uri":"capability://automation.workflow.unlimited.cloud.test.execution.with.concurrent.test.run.scaling","name":"unlimited cloud test execution with concurrent test run scaling","description":"Mabl provides unlimited concurrent test execution on managed cloud infrastructure with automatic scaling to handle peak loads. The platform distributes test execution across cloud resources without per-run charges or concurrency limits, enabling teams to run large test suites in parallel without infrastructure management.","intents":["I want to run my entire test suite in parallel without waiting for sequential execution","I need to scale test execution during peak CI/CD periods without provisioning additional infrastructure","I want predictable test execution costs without per-run charges"],"best_for":["enterprises with large test suites (1000+ tests) requiring parallel execution","organizations with unpredictable test execution patterns","teams wanting to eliminate infrastructure management overhead"],"limitations":["Unlimited concurrency is claimed but no technical ceiling is documented; actual limits may exist","Cloud execution latency includes network round-trip time to Mabl infrastructure; local execution may be faster for small test suites","Pricing is custom/quote-based; 'unlimited' claims are tied to subscription tier and may not apply to all plans","No option for on-premise or self-hosted execution; all tests must run on Mabl's cloud infrastructure"],"requires":["Mabl platform account with cloud execution enabled","Stable internet connectivity","Application accessible from Mabl's cloud infrastructure"],"input_types":["test definitions","test execution requests"],"output_types":["test execution results","execution logs","performance metrics"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_12","uri":"capability://automation.workflow.unlimited.local.test.execution.via.cli.with.offline.execution.capability","name":"unlimited local test execution via cli with offline execution capability","description":"Mabl provides a command-line interface (CLI) that enables local test execution on developer machines or CI/CD runners without cloud infrastructure. Local execution allows teams to run tests offline, integrate with custom CI/CD pipelines, and avoid cloud dependencies while maintaining access to Mabl's test definitions and reporting.","intents":["I want to run Mabl tests locally on my machine without cloud dependencies","I need to integrate Mabl tests into custom CI/CD pipelines that don't support cloud webhooks","I want to execute tests offline in environments without internet connectivity"],"best_for":["teams with strict data residency or security requirements","organizations with custom CI/CD infrastructure","developers wanting to run tests locally during development"],"limitations":["Local execution requires CLI installation and configuration; no support for serverless or containerless execution","Local execution performance depends on machine resources; no automatic scaling like cloud execution","Test results must be manually uploaded to Mabl for reporting; no automatic result synchronization","Local execution bypasses Mabl's cloud infrastructure; auto-healing and failure classification may not work as expected"],"requires":["Mabl CLI installed (version and language not specified)","Local machine with sufficient resources (CPU, memory, disk)","Test definitions exported from Mabl platform"],"input_types":["test definitions","CLI commands"],"output_types":["test execution results","execution logs"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_13","uri":"capability://data.processing.analysis.comprehensive.test.execution.diagnostics.and.flakiness.reporting","name":"comprehensive test execution diagnostics and flakiness reporting","description":"Mabl captures detailed diagnostic data during test execution including network traces, DOM snapshots, browser logs, and video recordings. The platform analyzes execution patterns to identify flaky tests (tests that fail intermittently) and separates real failures from environmental noise, enabling teams to distinguish between bugs and test infrastructure issues.","intents":["I want to understand why a test failed by reviewing detailed execution traces","I need to identify flaky tests that fail intermittently due to timing or environment issues","I want to debug test failures without reproducing them locally"],"best_for":["teams with large test suites struggling with flaky tests","organizations wanting to improve test reliability and reduce false positives","enterprises needing detailed failure diagnostics for root cause analysis"],"limitations":["Diagnostic data collection adds overhead to test execution; no option to disable collection for performance-critical tests","Video recording is storage-intensive; retention policies and storage limits are not documented","Flakiness detection requires historical execution data; new tests have no flakiness baseline","Diagnostic data is stored in Mabl's cloud; no option for local storage or export"],"requires":["Mabl platform account with diagnostics enabled","Sufficient storage quota for diagnostic data"],"input_types":["test execution traces","network logs","browser logs","video recordings"],"output_types":["diagnostic reports","flakiness scores","failure root cause analysis"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_14","uri":"capability://data.processing.analysis.account.level.test.quality.dashboards.with.trend.analysis.and.coverage.metrics","name":"account-level test quality dashboards with trend analysis and coverage metrics","description":"Mabl provides dashboards that aggregate test execution data across all tests and environments, displaying metrics like test pass rates, flakiness trends, coverage gaps, and test execution velocity. Dashboards enable teams to track test quality over time and identify areas needing improvement.","intents":["I want to see overall test quality metrics across my entire test suite","I need to track test reliability trends over time","I want to identify which areas of the application have insufficient test coverage"],"best_for":["QA leaders and engineering managers wanting visibility into test quality","teams wanting to track test quality improvements over time","organizations needing metrics for quality reporting and compliance"],"limitations":["Dashboards are account-level; no support for project-level or team-level dashboards","Metrics are limited to test execution data; no integration with code coverage or mutation testing data","Trend analysis requires historical data; new accounts have limited trend visibility","Dashboards are read-only; no support for custom metrics or KPI definitions"],"requires":["Mabl platform account with dashboard access enabled","Minimum 50+ test executions to establish baseline metrics"],"input_types":["test execution results","historical execution data"],"output_types":["quality dashboards","trend graphs","coverage reports"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_2","uri":"capability://image.visual.visual.change.detection.and.assertion.with.pixel.level.comparison","name":"visual change detection and assertion with pixel-level comparison","description":"Mabl captures visual snapshots of web applications during test execution and performs pixel-level comparison against baseline images to detect unintended visual regressions. The platform uses computer vision algorithms to identify changed regions, filter out noise (animations, timestamps), and generate visual diff reports highlighting what changed between test runs.","intents":["I want to catch visual regressions that functional assertions miss (layout shifts, color changes, font rendering)","I need to verify that responsive design changes work correctly across different screen sizes","I want to detect unintended CSS changes that don't break functionality but degrade user experience"],"best_for":["teams with design-heavy applications where visual consistency is critical","enterprises running cross-browser testing where rendering differences matter","organizations wanting to catch visual regressions before they reach production"],"limitations":["Pixel-level comparison is sensitive to rendering differences across browsers and OS versions; same visual design may produce different pixel values","Dynamic content (timestamps, user IDs, animated elements) must be masked or excluded from comparison to avoid false positives","Visual assertions require manual baseline establishment; no automatic baseline generation for new tests","Comparison is computationally expensive; visual assertion execution time adds 500ms-2s per assertion depending on image size"],"requires":["Mabl platform account with visual testing module enabled","Stable rendering environment (consistent browser version, OS, font rendering)","Baseline images established for each test scenario"],"input_types":["web application screenshots","baseline visual snapshots","region masks for dynamic content"],"output_types":["visual diff reports","pixel-level change maps","regression severity scores"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_3","uri":"capability://automation.workflow.api.testing.with.request.response.validation.and.data.driven.execution","name":"api testing with request/response validation and data-driven execution","description":"Mabl enables creation of API tests that validate HTTP request/response behavior, including status codes, headers, response body structure, and performance metrics. Tests support data-driven execution where test parameters are sourced from external datasets, allowing a single test definition to execute against multiple input combinations without code duplication.","intents":["I want to test REST APIs without writing code or using Postman collections","I need to validate API responses against expected schemas and data contracts","I want to run the same API test against multiple datasets (users, products, environments) without duplicating test definitions"],"best_for":["QA teams testing microservices and API-first architectures","teams wanting to shift left by testing APIs before UI integration","organizations needing data-driven API testing without custom scripting"],"limitations":["API testing is limited to HTTP/REST; no support for gRPC, GraphQL, or WebSocket protocols documented","Data-driven execution requires external data source integration; no built-in data generation or mocking","Response validation is schema-based; no support for complex business logic validation or custom assertion functions","API test execution latency includes network round-trip time; no local API mocking to reduce test execution time"],"requires":["Mabl platform account with API testing module enabled","Accessible API endpoint (public or internal network)","API authentication credentials (API keys, OAuth tokens, basic auth)"],"input_types":["HTTP request definitions (method, URL, headers, body)","expected response schemas","external data sources (CSV, JSON, database)"],"output_types":["API test execution results","response validation reports","performance metrics (latency, throughput)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_4","uri":"capability://planning.reasoning.test.impact.analysis.with.change.to.test.mapping","name":"test impact analysis with change-to-test mapping","description":"Mabl analyzes code changes (commits, pull requests) and automatically identifies which tests are relevant to those changes using dependency analysis and historical test coverage data. The platform surfaces only impacted tests to developers, reducing test suite execution time and focusing CI/CD pipelines on tests that could be affected by the change.","intents":["I want to run only the tests affected by my code changes instead of the full test suite","I need to understand which tests cover the code I just modified","I want to reduce CI/CD pipeline execution time by skipping irrelevant tests"],"best_for":["teams with large test suites (1000+ tests) where full suite execution is expensive","organizations using GitHub/GitLab with frequent pull requests","enterprises wanting to optimize CI/CD pipeline efficiency without sacrificing coverage"],"limitations":["Test Impact Analysis requires historical test execution data; new codebases or tests have no coverage history and cannot be mapped","Mapping accuracy depends on code instrumentation; tests that don't explicitly reference changed code may be missed","Impact analysis is limited to code-level changes; infrastructure, configuration, or environment changes are not detected","False negatives are possible if tests have implicit dependencies not captured in code analysis"],"requires":["Mabl platform account with Test Impact Analysis module enabled","GitHub or GitLab integration configured","Minimum 50+ test executions to establish coverage baseline"],"input_types":["code commits/pull requests","test execution history","code dependency graphs"],"output_types":["list of impacted tests","coverage impact reports","test execution recommendations"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_5","uri":"capability://automation.workflow.mobile.app.testing.for.ios.and.android.with.gesture.automation","name":"mobile app testing for ios and android with gesture automation","description":"Mabl extends test automation to native iOS and Android applications, enabling creation of tests that interact with mobile apps through gesture automation (taps, swipes, long-presses) and element inspection. Tests are authored in the same low-code interface as web tests, with platform-specific element locators and mobile-specific assertions (device orientation, notifications, permissions).","intents":["I want to automate testing of native iOS and Android apps without learning Appium or XCUITest","I need to test mobile-specific interactions like swipes, pinches, and gesture navigation","I want to verify app behavior across different device types and OS versions"],"best_for":["mobile development teams wanting to shift left with automated testing","enterprises with cross-platform apps (iOS + Android) needing unified test framework","organizations lacking Appium expertise and wanting low-code mobile testing"],"limitations":["Mobile testing requires cloud device infrastructure or local device connection; no support for emulator-only testing documented","Gesture automation is limited to standard interactions (tap, swipe, long-press); complex multi-touch gestures are not supported","Mobile element locators are fragile; app updates that change view hierarchies require test updates","Testing of native modules and platform-specific APIs is not supported; only UI-level interactions are automated"],"requires":["Mabl platform account with mobile testing module enabled","iOS app (compiled .ipa) or Android app (compiled .apk)","Physical device or cloud device farm access"],"input_types":["mobile app binaries","gesture sequences","mobile element selectors"],"output_types":["mobile test execution results","device-specific screenshots","gesture interaction logs"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_6","uri":"capability://automation.workflow.performance.testing.and.monitoring.with.latency.throughput.metrics","name":"performance testing and monitoring with latency/throughput metrics","description":"Mabl captures performance metrics during test execution including page load times, API response latencies, and resource utilization. The platform tracks performance trends over time and alerts on performance regressions, enabling teams to detect performance degradation before it impacts users.","intents":["I want to monitor application performance as part of my automated test suite","I need to detect performance regressions in CI/CD pipelines before they reach production","I want to track performance trends over time to identify optimization opportunities"],"best_for":["teams with performance-sensitive applications (e-commerce, financial services)","organizations wanting to shift left with performance testing","enterprises needing continuous performance monitoring without separate load testing tools"],"limitations":["Performance testing is limited to single-user scenarios; no load testing or stress testing at scale","Metrics are collected from Mabl's cloud infrastructure; performance may not reflect real-world user network conditions","Performance baselines must be manually established; no automatic threshold detection","Performance regression alerts require manual threshold configuration; no intelligent anomaly detection"],"requires":["Mabl platform account with performance monitoring enabled","Web application with stable performance characteristics","Performance baseline established from historical test runs"],"input_types":["test execution traces","network timing data","resource utilization metrics"],"output_types":["performance reports","latency/throughput metrics","performance trend graphs"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_7","uri":"capability://automation.workflow.accessibility.testing.with.wcag.compliance.validation","name":"accessibility testing with wcag compliance validation","description":"Mabl includes accessibility testing capabilities that validate web applications against WCAG 2.1 standards, checking for issues like missing alt text, color contrast violations, keyboard navigation problems, and semantic HTML structure. Tests can be configured to enforce specific accessibility levels (A, AA, AAA) and generate compliance reports.","intents":["I want to ensure my application meets WCAG accessibility standards","I need to catch accessibility regressions in CI/CD pipelines","I want to generate accessibility compliance reports for audits and legal requirements"],"best_for":["organizations with legal/regulatory accessibility requirements","enterprises building public-facing applications with diverse user bases","teams wanting to shift left with accessibility testing"],"limitations":["Automated accessibility testing catches only ~30-40% of accessibility issues; manual testing is still required for complex interactions","Accessibility validation is limited to WCAG 2.1; newer standards (WCAG 3.0) are not supported","False positives are common; accessibility rules require manual review to confirm violations","Testing is limited to visual/DOM-level accessibility; runtime accessibility APIs and screen reader behavior are not tested"],"requires":["Mabl platform account with accessibility testing module enabled","Web application with semantic HTML structure"],"input_types":["web application pages","WCAG compliance level (A, AA, AAA)","accessibility rule configurations"],"output_types":["accessibility violation reports","WCAG compliance scores","remediation recommendations"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_8","uri":"capability://tool.use.integration.github.and.gitlab.ci.cd.integration.with.pr.status.checks.and.inline.comments","name":"github and gitlab ci/cd integration with pr status checks and inline comments","description":"Mabl integrates natively with GitHub and GitLab to trigger test execution on pull requests, report test results as status checks, and post inline comments on code changes that are affected by test failures. The platform automatically surfaces test failures in the PR review interface, enabling developers to see test impact without leaving GitHub/GitLab.","intents":["I want test results to appear as status checks on my pull requests","I need to see which tests failed and why without leaving GitHub/GitLab","I want to block merging of PRs that fail critical tests"],"best_for":["teams using GitHub or GitLab as primary development platform","organizations wanting to enforce test quality gates in PR workflows","enterprises with distributed teams needing asynchronous test feedback"],"limitations":["Integration is limited to GitHub and GitLab; other VCS platforms (Bitbucket, Azure DevOps) are not supported","Status checks are binary (pass/fail); no support for conditional status based on test severity or impact","Inline comments are limited to test failure summaries; detailed failure logs require clicking through to Mabl dashboard","PR integration requires webhook configuration; no automatic setup for GitHub Apps"],"requires":["GitHub or GitLab account with repository access","Mabl platform account with CI/CD integration enabled","Repository webhook configured to trigger Mabl test execution"],"input_types":["pull request events","code changes","test execution results"],"output_types":["PR status checks","inline PR comments","test failure summaries"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__cap_9","uri":"capability://tool.use.integration.jira.integration.with.atlassian.rovo.for.ai.powered.test.discovery.and.execution","name":"jira integration with atlassian rovo for ai-powered test discovery and execution","description":"Mabl integrates with Jira through Atlassian Rovo (Atlassian's AI assistant) to enable natural language test discovery and execution directly from Jira tickets. Users can ask Rovo to find and run tests related to a specific issue, and Rovo surfaces test results and recommendations within the Jira interface.","intents":["I want to find and run relevant tests for a Jira issue without leaving Jira","I need to understand test coverage for a specific feature or bug fix","I want to ask Rovo to run tests and get results in natural language"],"best_for":["organizations using Jira as source of truth for requirements and issues","teams wanting to reduce context switching between Jira and test tools","enterprises with Atlassian Cloud subscriptions"],"limitations":["Rovo integration is limited to Atlassian Cloud; on-premise Jira is not supported","Test discovery depends on Rovo's natural language understanding; ambiguous queries may return incorrect tests","Rovo is an Atlassian product; Mabl's role in the integration is unclear and may be limited to data provision","Integration is read-only for test execution; test creation and modification must happen in Mabl"],"requires":["Jira Cloud account with Atlassian Rovo enabled","Mabl platform account with Jira integration configured","Tests must be linked to Jira issues for discovery"],"input_types":["natural language queries in Rovo","Jira issue context","test metadata"],"output_types":["test recommendations","test execution results","natural language summaries"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"mabl__headline","uri":"capability://testing.quality.ai.driven.test.automation.platform","name":"ai-driven test automation platform","description":"Mabl is an intelligent test automation platform that leverages machine learning to create, execute, and maintain reliable end-to-end tests for web and mobile applications, providing features like auto-healing tests and visual change detection in a low-code interface.","intents":["best AI test automation platform","test automation for web applications","low-code test automation tools","automated testing solutions with AI","end-to-end testing platforms","test maintenance tools for developers"],"best_for":["teams seeking efficient test automation","developers looking for low-code solutions"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["testing-quality"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":58,"verified":false,"data_access_risk":"high","permissions":["Mabl platform account (free tier available)","Web application with stable DOM selectors or visual elements","Jira integration enabled for ticket-based test generation","Mabl platform account with cloud execution enabled","Sufficient historical test execution data (minimum 50+ runs recommended for accurate ML classification)","Web application with stable semantic structure (healing fails if DOM is completely restructured)","Slack or Microsoft Teams workspace","Mabl platform account with notification integration enabled","Slack/Teams bot configured with appropriate permissions","Stable internet connectivity"],"failure_modes":["Tests are locked to Mabl's proprietary format with no standard export mechanism documented","Natural language generation accuracy depends on clarity of input descriptions; ambiguous requirements may produce incorrect test steps","Low-code interface abstracts away fine-grained control available in code-first frameworks like Playwright or Cypress","No support for custom test logic beyond Mabl's predefined step library","Auto-healing works best for CSS/XPath selector changes; complex DOM restructuring may exceed recovery capabilities","Failure classification accuracy depends on historical test data; new applications with limited execution history may misclassify failures","Recovery strategies are limited to Mabl's predefined healing library; custom recovery logic is not supported","Healing decisions are opaque to users; no audit trail of what changes were applied to recover a test","Notifications are limited to failure alerts; no support for success notifications or custom event types","Recovery proposals are AI-generated and may be inaccurate; manual verification is required","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.25,"match_graph":0.25,"freshness":0.9,"weights":{"adoption":0.3,"quality":0.25,"ecosystem":0.15,"match_graph":0.25,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.328Z","last_scraped_at":null,"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=mabl","compare_url":"https://unfragile.ai/compare?artifact=mabl"}},"signature":"mYAG+040kpJHqXu0nMHe2BqMNU6Yn8uwZ5UMNpf21N/TW51EMHxHi6Zh30VH9DJUFAI5tMY8JVQZNKCMD/leAw==","signedAt":"2026-06-15T07:43:07.722Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mabl","artifact":"https://unfragile.ai/mabl","verify":"https://unfragile.ai/api/v1/verify?slug=mabl","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"}}