{"id":2061,"date":"2025-10-16T12:59:48","date_gmt":"2025-10-16T07:29:48","guid":{"rendered":"https:\/\/www.getpanto.ai\/blog\/?p=2061"},"modified":"2026-04-20T11:30:12","modified_gmt":"2026-04-20T06:00:12","slug":"ai-driven-mobile-qa-testing-metrics","status":"publish","type":"post","link":"https:\/\/www.getpanto.ai\/blog\/ai-driven-mobile-qa-testing-metrics","title":{"rendered":"Testing Metrics for Mobile QA in 2026"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Mobile app quality is critical because users quickly abandon apps that crash or frustrate them. Studies show that a majority of users uninstall an app within days if it performs poorly. To prevent this, QA managers rely on <strong>testing metrics<\/strong> \u2014 quantitative indicators of test coverage, defects, and user experience \u2014 to monitor and improve mobile app <a href=\"https:\/\/www.getpanto.ai\/blog\/code-quality\">quality<\/a>. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These metrics provide clarity on where to invest time, what to fix first, and how to measure the real impact of testing efforts.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"key-metrics-for-mobile-qa\"><span class=\"ez-toc-section\" id=\"key-metrics-for-mobile-qa\"><\/span><strong>Key Metrics for Mobile QA<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Effective mobile QA is built on metrics that track quality from multiple angles. The most important ones fall into five categories:<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"1-performance-and-reliability-metrics\"><span class=\"ez-toc-section\" id=\"1-performance-and-reliability-metrics\"><\/span><strong>1. Performance and Reliability Metrics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">These measure the app\u2019s stability and speed across devices and conditions.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Crash Rate:<\/strong> The percentage of user sessions that end in a crash.<\/li>\n\n\n\n<li><strong>ANR Rate:<\/strong> The rate of \u201cApplication Not Responding\u201d errors or hangs.<\/li>\n\n\n\n<li><strong>App Load Time:<\/strong> How long it takes for the app or its features to become usable.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">High crash or ANR rates directly correlate with user drop-offs. Monitoring and reducing these ensures a smoother user and <a href=\"https:\/\/www.getpanto.ai\/blog\/how-ai-driven-development-tools-are-revolutionizing-the-coding-experience\">coding experience<\/a>. Other related measures include API latency, frame rendering time, and battery or memory usage under load.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"2-coverage-metrics\"><span class=\"ez-toc-section\" id=\"2-coverage-metrics\"><\/span><strong>2. Coverage Metrics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">Coverage <a href=\"https:\/\/www.getpanto.ai\/blog\/code-quality\">metrics<\/a> gauge how thoroughly testing addresses the app.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Test Case Coverage:<\/strong> The percentage of features or requirements tested.<\/li>\n\n\n\n<li><strong>Code Coverage:<\/strong> The proportion of code executed during tests.<\/li>\n\n\n\n<li><strong>Device and OS Coverage:<\/strong> How many device models and OS versions are included in testing.<\/li>\n\n\n\n<li><strong>Localization Coverage:<\/strong> Ensuring all supported languages, regions, and currencies are tested.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Because mobile ecosystems are so fragmented, missing coverage on key devices or OS versions can lead to critical issues that only appear for certain user groups.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"3-defect-metrics\"><span class=\"ez-toc-section\" id=\"3-defect-metrics\"><\/span><strong>3. Defect Metrics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">Defect metrics quantify how many bugs are found \u2014 and how serious they are.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Defect Density:<\/strong> Number of defects per module or per lines of code.<\/li>\n\n\n\n<li><strong>Defect Leakage:<\/strong> Bugs missed in <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-vs-traditional-qa-mobile-testing\">traditional QA<\/a> that appear in production.<\/li>\n\n\n\n<li><strong>Severity Index:<\/strong> Weighted measurement of how severe reported defects are.<\/li>\n\n\n\n<li><strong>Fix Rate:<\/strong> The percentage of reported bugs resolved before release.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Tracking these helps identify weak spots in testing and development, as well as overall product stability trends.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These connect QA outcomes directly to how real users perceive the app.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"4-user-experience-metrics\"><span class=\"ez-toc-section\" id=\"4-user-experience-metrics\"><\/span><strong>4. User Experience Metrics<\/strong><br><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<ul class=\"wp-block-list\">\n<li><strong>App Store Rating and Reviews:<\/strong> Reflect overall satisfaction and usability.<\/li>\n\n\n\n<li><strong>User Retention Rate:<\/strong> Measures how many users keep using the app over time.<\/li>\n\n\n\n<li><strong>Conversion Rate:<\/strong> Tracks how many users complete important in-app goals (like purchases or sign-ups).<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">If ratings drop or <a href=\"https:\/\/www.getpanto.ai\/blog\/zero-code-retention-protecting-code-privacy-in-ai-code-reviews\">retention<\/a> declines, it often means something in performance or UX needs immediate attention.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"5-roi-and-productivity-metrics\"><span class=\"ez-toc-section\" id=\"5-roi-and-productivity-metrics\"><\/span><strong>5. ROI and Productivity Metrics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">Finally, QA needs to demonstrate impact on delivery speed and efficiency.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Release Velocity:<\/strong> Measures how fast new features move from development to production.<\/li>\n\n\n\n<li><strong>Cost of Quality:<\/strong> Compares testing costs to the costs saved by finding bugs early.<\/li>\n\n\n\n<li><strong>Test Execution Rate:<\/strong> Ratio of executed tests to planned ones.<\/li>\n\n\n\n<li><strong>Automation Coverage:<\/strong> Percentage of total tests that are automated.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These metrics show whether <a href=\"https:\/\/www.getpanto.ai\/blog\/revolutionizing-code-reviews-how-ai-is-transforming-technical-debt-management\">technical debt is managed<\/a>, and whether QA investments are paying off \u2014 through faster releases, fewer post-release incidents, and improved team productivity.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"making-metrics-actionable\"><span class=\"ez-toc-section\" id=\"making-metrics-actionable\"><\/span><strong>Making Metrics Actionable<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Collecting metrics is just the first step. The real power lies in using them to guide action. QA teams should ask:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u201cDo our crash rates affect retention?\u201d<\/li>\n\n\n\n<li>\u201cAre we testing the most-used devices and OS versions?\u201d<\/li>\n\n\n\n<li>\u201cWhich parts of the app cause the most severe issues?\u201d<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.getpanto.ai\/products\/code-security\/security-dashboard\">Dashboards <\/a>should emphasize <strong>user-centric and risk-based insights<\/strong>, not just vanity numbers like \u201ctests run.\u201d Meaningful metrics help prioritize fixes, optimize coverage, and communicate value to product and business stakeholders.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"challenges-in-traditional-mobile-qa\"><span class=\"ez-toc-section\" id=\"challenges-in-traditional-mobile-qa\"><\/span><strong>Challenges in <\/strong><a href=\"https:\/\/www.getpanto.ai\/blog\/ai-vs-traditional-qa-mobile-testing\"><strong>Traditional Mobile QA<\/strong><\/a><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">Mobile QA is more complex than web testing because of <strong>device fragmentation<\/strong> \u2014 thousands of Android models and multiple iOS versions. Testing everything manually is nearly impossible, and automated tests often become brittle. Small UI or OS updates can break hundreds of test scripts, leading to time-consuming maintenance instead of active testing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This constant upkeep slows down delivery. Teams may have large <a href=\"https:\/\/www.getpanto.ai\/blog\/ai-driven-development-the-future-of-building-software-in-2025\">AI-driven<\/a> suites that look impressive on paper, but in reality, they miss critical user flows or fail on newer devices. As a result, testing becomes reactive instead of predictive, and metrics stop reflecting real user quality.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"how-aidriven-qa-changes-the-game\"><span class=\"ez-toc-section\" id=\"how-ai-driven-qa-changes-the-game\"><\/span><strong>How AI-Driven QA Changes the Game<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.getpanto.ai\/blog\/vibe-debugging-ai-qa-testing\">AI-powered QA testing<\/a> is redefining mobile QA by automating everything from test creation to maintenance. Instead of relying on humans to write and update scripts, <a href=\"https:\/\/www.getpanto.ai\/blog\/vibe-coding-vs-vibe-debugging-the-modern-developers-reality\"><strong>vibe debugging<\/strong><\/a>&nbsp;uses AI agents to diagnose and fix code issues through natural language conversations, rather than traditional breakpoints or manual inspection..<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Here\u2019s how AI-driven mobile QA improves traditional QA metrics:<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"1-automated-test-generation\"><span class=\"ez-toc-section\" id=\"1-automated-test-generation\"><\/span><strong>1. Automated Test Generation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">AI can generate test cases directly from natural-language requirements or user stories. This dramatically expands <strong>test coverage<\/strong>, including edge cases that human testers might overlook.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"2-intelligent-test-execution\"><span class=\"ez-toc-section\" id=\"2-intelligent-test-execution\"><\/span><strong>2. Intelligent Test Execution<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.getpanto.ai\/blog\/best-ai-code-review-tools\">AI-powered tools<\/a> can execute tests on real devices or emulators at massive scale. They run parallel tests across hundreds of device and OS combinations in minutes, boosting both <strong>device coverage<\/strong> and <strong>test execution rate<\/strong>.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"3-selfhealing-automations\"><span class=\"ez-toc-section\" id=\"3-self-healing-automations\"><\/span><strong>3. Self-Healing Automations<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">When a UI element changes, AI can detect it visually or contextually and automatically update the test script. This reduces test maintenance effort and keeps <strong>automation coverage<\/strong> consistent, even as the app evolves.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"4-smart-test-prioritization\"><span class=\"ez-toc-section\" id=\"4-smart-test-prioritization\"><\/span><strong>4. Smart Test Prioritization<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">AI analyzes code changes, historical failures, and risk factors to prioritize test runs. Critical paths like payments or authentication are tested first, ensuring faster detection of major issues.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"5-predictive-analytics\"><span class=\"ez-toc-section\" id=\"5-predictive-analytics\"><\/span><strong>5. Predictive Analytics<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<p class=\"wp-block-paragraph\">AI correlates test failures, code changes, and crash reports to predict where future defects might occur. These insights make metrics like <strong>defect density<\/strong> and <strong>leakage rate<\/strong> more meaningful \u2014 and actionable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Together, these capabilities make QA faster, smarter, and more reliable \u2014 improving both the <em>efficiency metrics<\/em> (like time to execute tests) and <a href=\"https:\/\/www.getpanto.ai\/blog\/how-ai-code-review-tools-are-transforming-code-quality-and-developer-velocity\"><em>quality <\/em><\/a><em>metrics<\/em> (like user satisfaction and defect rates).<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"manual-vs-aidriven-mobile-qa-which-finds-more-bugs-faster\"><span class=\"ez-toc-section\" id=\"manual-vs-ai-driven-mobile-qa-which-finds-more-bugs-faster\"><\/span><strong>Manual vs. AI-Driven Mobile QA: Which Finds More Bugs, Faster?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">The effectiveness of a mobile QA strategy isn\u2019t just about catching bugs \u2014 it\u2019s about how quickly, accurately, and consistently those bugs are found across a fragmented device landscape. <a href=\"https:\/\/www.getpanto.ai\/blog\/traditional-debugging-vs-vibe-debugging\">Traditional debugging<\/a> has long been the backbone of quality assurance, but it struggles to keep pace with the speed and complexity of modern app development.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI-driven mobile QA, on the other hand, leverages automation, <a href=\"https:\/\/www.getpanto.ai\/products\/ai-code-review\/reinforcement-learning\">reinforcement learning<\/a>, and self-healing mechanisms to deliver deeper coverage, faster feedback, and smarter defect <a href=\"https:\/\/www.getpanto.ai\/products\/code-security\/secret-detection\">detection<\/a>. The comparison below highlights how AI-driven QA outperforms manual testing across key dimensions like speed, accuracy, scalability, and cost-efficiency.<\/p>\n\n\n<h3 class=\"wp-block-heading\" id=\"table-manual-qa-vs-aidriven-qa\"><span class=\"ez-toc-section\" id=\"table-manual-qa-vs-ai-driven-qa\"><\/span><strong>Table: Manual QA vs. AI-Driven QA<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Dimension<\/th><th>Manual QA<\/th><th>AI-Driven QA<\/th><\/tr><\/thead><tbody><tr><td><strong>Speed of defect detection<\/strong><\/td><td>Slow and sequential. Testers must write, execute, and review test cases manually, often finding bugs late in the cycle.<\/td><td>Fast and continuous. AI-driven tests run automatically on every build, catching issues in real time with significantly shorter execution times.<\/td><\/tr><tr><td><strong>Test coverage (code, device, scenario)<\/strong><\/td><td>Limited by human capacity. QA teams can only test a small set of devices and scenarios due to time and resource limits.<\/td><td>Broad and systematic. AI generates and executes hundreds of tests in parallel across vast device and OS combinations, greatly improving coverage.<\/td><\/tr><tr><td><strong>Scalability (devices &amp; OS versions)<\/strong><\/td><td>Poor scalability. Testing more devices or OS versions requires additional testers and physical hardware.<\/td><td>Highly scalable. Cloud-based AI testing runs on multiple devices and OS versions in parallel without extra human effort.<\/td><\/tr><tr><td><strong>Accuracy in UI regressions<\/strong><\/td><td>Manual testers can overlook small visual or layout shifts, leading to inconsistent regression checks.<\/td><td>AI visual testing compares screens pixel-by-pixel, detecting subtle UI regressions consistently and accurately.<\/td><\/tr><tr><td><strong>Handling of edge-case flows<\/strong><\/td><td>Depends on tester creativity and time; rare or complex user paths are often skipped or missed.<\/td><td>AI explores and generates diverse test scenarios, including edge cases, based on data patterns and user behavior analysis.<\/td><\/tr><tr><td><strong>Maintenance effort (UI changes)<\/strong><\/td><td>Very high. UI or workflow updates require manual rework of test steps, slowing down teams.<\/td><td>Low. AI tests self-heal when elements change, automatically adjusting locators and steps with minimal human input.<\/td><\/tr><tr><td><strong>Time to execute full test suites<\/strong><\/td><td>Long. Manual execution can take hours or days, delaying releases.<\/td><td>Short. AI-driven suites run in minutes using parallel execution across environments.<\/td><\/tr><tr><td><strong>Frequency &amp; reliability of runs<\/strong><\/td><td>Infrequent and inconsistent. Manual runs depend on tester availability and can vary in accuracy.<\/td><td>Frequent and reliable. AI executes consistent tests automatically in continuous integration environments.<\/td><\/tr><tr><td><strong>Cost-effectiveness over time<\/strong><\/td><td>High ongoing costs as testing scales linearly with app complexity and team size.<\/td><td>High ROI. Initial setup costs are offset by long-term savings in time, labor, and reduced post-release defects.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n<h2 class=\"wp-block-heading\" id=\"the-future-panto-ais-upcoming-mobile-qa-agent\"><span class=\"ez-toc-section\" id=\"the-future-panto-ais-upcoming-mobile-qa-agent\"><\/span><strong>The Future: Panto AI\u2019s Upcoming Mobile QA Agent<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<p class=\"wp-block-paragraph\">One of the most exciting developments in this space is <strong>Panto AI\u2019s upcoming AI-driven mobile QA<\/strong> <strong>agent<\/strong> for mobile testing. <a href=\"https:\/\/www.getpanto.ai\">Panto <\/a>aims to make the entire QA process so seamless that a bot itself can navigate through new features, execute tests on real devices, and create test reports automatically.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Panto AI agent will be designed to:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Understand requirements in natural language<\/strong> or even generate test cases automatically based on organizational context.<\/li>\n\n\n\n<li><strong>Execute those tests<\/strong> on both real devices and emulators at scale.<\/li>\n\n\n\n<li><strong>Automate test runs<\/strong> across device matrices within seconds in the backend.<\/li>\n\n\n\n<li><strong>Self-heal broken automations<\/strong> when UI elements change \u2014 remapping user journeys and providing feedback autonomously.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">With this kind of intelligence, testing will shift from being a repetitive task to an adaptive, self-learning process. Unlike<a href=\"https:\/\/www.getpanto.ai\/blog\/ai-vs-traditional-qa-mobile-testing\"> traditional QA teams<\/a>, teams using Panto will be able to focus on strategy and innovation while the AI-driven mobile QA handles execution, maintenance, and reporting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Testing metrics are the backbone of mobile QA, helping teams measure everything from reliability to user satisfaction. But as mobile ecosystems grow more complex, maintaining those metrics manually becomes unsustainable.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI-driven mobile QA (<a href=\"https:\/\/www.getpanto.ai\/blog\/vibe-debugging-ai-qa-testing\">aka vibe debugging<\/a>) offers a new way forward \u2014 one that\u2019s faster, more adaptive, and truly scalable. With upcoming innovations, we\u2019re moving toward a future where testing is not just automated, but <strong>autonomous<\/strong>: intelligent systems that understand, execute, and optimize quality at every stage of the release cycle.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n","protected":false},"excerpt":{"rendered":"<p>Mobile app quality is critical because users quickly abandon apps that crash or frustrate them. Studies show that a majority of users uninstall an app within days if it performs poorly. To prevent this, QA managers rely on testing metrics \u2014 quantitative indicators of test coverage, defects, and user experience \u2014 to monitor and improve [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":2068,"comment_status":"open","ping_status":"open","sticky":false,"template":"wp-custom-template-panto-blogs-v3","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2061","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-coding"],"_links":{"self":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts\/2061","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/comments?post=2061"}],"version-history":[{"count":0,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/posts\/2061\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/media\/2068"}],"wp:attachment":[{"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/media?parent=2061"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/categories?post=2061"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.getpanto.ai\/blog\/wp-json\/wp\/v2\/tags?post=2061"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}