[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-openai-ios-ettrace-performance":3,"mdc-rd4hi9-key":36,"related-repo-openai-ios-ettrace-performance":2727,"related-org-openai-ios-ettrace-performance":2849},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"ios-ettrace-performance","profile iOS app performance with ETTrace","Capture and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"openai","OpenAI","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fopenai.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Performance","performance","tag",{"name":17,"slug":18,"type":15},"iOS","ios",{"name":20,"slug":21,"type":15},"Mobile","mobile",{"name":23,"slug":24,"type":15},"Debugging","debugging",3992,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins","2026-04-27T05:45:29.742562",null,465,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"OpenAI Plugins","https:\u002F\u002Fgithub.com\u002Fopenai\u002Fplugins\u002Ftree\u002FHEAD\u002Fplugins\u002Fbuild-ios-apps\u002Fskills\u002Fios-ettrace-performance","---\nname: ios-ettrace-performance\ndescription: Capture and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.\n---\n\n# iOS ETTrace Performance\n\nUse this skill to capture a focused, symbolicated ETTrace profile from an iOS simulator app. Pair it with `..\u002Fios-debugger-agent\u002FSKILL.md` when the task also needs simulator build, install, launch, UI driving, logs, or screenshots.\n\n## Core Workflow\n\n1. Pick one focused flow and write down the expected start and stop points.\n2. Build the exact simulator app that will be installed and profiled.\n3. Temporarily link ETTrace into that app target for simulator\u002Fdebug profiling.\n4. Collect UUID-matched dSYMs for the app executable and embedded dynamic frameworks.\n5. Capture one launch or runtime trace.\n6. Preserve the processed flamegraph JSON immediately after the run.\n7. Analyze only the processed JSON and report the flow, artifacts, hotspots, and caveats.\n\nAvoid broad \"use the app for a while\" captures. One trace should correspond to one user-visible flow.\n\n## Setup\n\nUse a writable run folder for each profiling session:\n\n```bash\nif [ -z \"${RUN_DIR:-}\" ]; then\n  RUN_DIR=\"$(mktemp -d \"${TMPDIR:-\u002Ftmp}\u002Fcodex-ios-ettrace.XXXXXX\")\"\nfi\nmkdir -p \"$RUN_DIR\"\n```\n\nInstall the ETTrace runner CLI if it is not already available:\n\n```bash\nbrew install emergetools\u002Fhomebrew-tap\u002Fettrace\n```\n\n`ettrace` is the host-side macOS runner. The app must also link an `ETTrace.xcframework` for the iOS Simulator architecture.\nThis workflow is validated for ETTrace v1.1.0 processed `output_\u003Cthread>.json` files with top-level `nodes`.\n\n## Link ETTrace Into The App\n\nWire ETTrace into the exact app target being profiled. Keep the integration in a clearly temporary patch and remove it when the profiling task is done unless the user explicitly asks to keep it.\n\nPreferred options:\n\n- Reuse an existing simulator-compatible `ETTrace.xcframework` if the repo already vendors one.\n- If none exists, build a simulator-only copy into `RUN_DIR` from the upstream ETTrace package.\n- Link the framework directly into the app target, not only into tests, resources, data files, or a nested launcher target.\n- Confirm launch logs print `Starting ETTrace`.\n- Profile only one ETTrace-instrumented simulator app at a time because simulator mode listens on a fixed localhost port.\n\nBuild a simulator framework when needed:\n\n```bash\nETTRACE_TAG=\"${ETTRACE_TAG:-v1.1.0}\" # Override to match the installed runner when Homebrew updates.\nETTRACE_SRC=\"$RUN_DIR\u002FETTrace-src\"\nif [ ! -d \"$ETTRACE_SRC\" ]; then\n  git clone --depth 1 --branch \"$ETTRACE_TAG\" https:\u002F\u002Fgithub.com\u002FEmergeTools\u002FETTrace \"$ETTRACE_SRC\"\nfi\n\nrm -rf \"$RUN_DIR\u002FETTrace-iphonesimulator.xcarchive\" \"$RUN_DIR\u002FETTrace.xcframework\"\npushd \"$ETTRACE_SRC\" >\u002Fdev\u002Fnull\nxcodebuild archive \\\n  -scheme ETTrace \\\n  -archivePath \"$RUN_DIR\u002FETTrace-iphonesimulator.xcarchive\" \\\n  -sdk iphonesimulator \\\n  -destination 'generic\u002Fplatform=iOS Simulator' \\\n  BUILD_LIBRARY_FOR_DISTRIBUTION=YES \\\n  INSTALL_PATH='Library\u002FFrameworks' \\\n  SKIP_INSTALL=NO \\\n  CLANG_CXX_LANGUAGE_STANDARD=c++17\n\nxcodebuild -create-xcframework \\\n  -framework \"$RUN_DIR\u002FETTrace-iphonesimulator.xcarchive\u002FProducts\u002FLibrary\u002FFrameworks\u002FETTrace.framework\" \\\n  -output \"$RUN_DIR\u002FETTrace.xcframework\"\npopd >\u002Fdev\u002Fnull\n```\n\nFor Bazel apps, a temporary import usually looks like:\n\n```python\nload(\"@rules_apple\u002F\u002Fapple:apple.bzl\", \"apple_dynamic_xcframework_import\")\n\npackage(default_visibility = [\"\u002F\u002Fvisibility:public\"])\n\napple_dynamic_xcframework_import(\n    name = \"ETTrace\",\n    xcframework_imports = glob([\"ETTrace.xcframework\u002F**\"]),\n)\n```\n\nFor Xcode projects, temporarily add the simulator `ETTrace.xcframework` to the app target's Link Binary With Libraries \u002F Embed Frameworks phases for the debug simulator build you are profiling, then remove that wiring after profiling.\n\n## Symbolication Gate\n\nDo not draw conclusions from an unsymbolicated flamegraph. Before every capture, prepare a dSYM folder that includes the app dSYM and any embedded first-party dynamic framework dSYMs.\n\nCollect dSYMs after the final build that produced the installed app:\n\n```bash\nSKILL_DIR=\"\u003Cabsolute path to this loaded skill folder>\"\nAPP=\"\u003Cpath-to-built-simulator-App.app>\"\nDSYMS=\"$RUN_DIR\u002Fdsyms\"\n\n\"$SKILL_DIR\u002Fscripts\u002Fcollect_ios_dsyms.sh\" \\\n  --app \"$APP\" \\\n  --out-dir \"$DSYMS\" \\\n  --search-root \"$(dirname \"$APP\")\" \\\n  --search-root \"$PWD\" \\\n  --extra-dsym \"$RUN_DIR\u002FETTrace-iphonesimulator.xcarchive\u002FdSYMs\u002FETTrace.framework.dSYM\"\n```\n\nAdd `--require-framework \u003CFrameworkName>` for app-owned dynamic frameworks that must symbolicate; use `--require-all-frameworks` only when every embedded framework is app-owned or expected to have symbols. If the helper reports a missing required app or framework dSYM, rebuild the exact simulator app with dSYM generation before tracing, or add the build output directory that contains those dSYMs as another `--search-root`.\n\nVerify important UUIDs before tracing when the report looks suspicious:\n\n```bash\ndwarfdump --uuid \"$APP\u002F$(\u002Fusr\u002Flibexec\u002FPlistBuddy -c 'Print :CFBundleExecutable' \"$APP\u002FInfo.plist\")\"\nfind \"$DSYMS\" -maxdepth 1 -type d -name '*.dSYM' -print -exec dwarfdump --uuid {} \\;\n```\n\nAfter ETTrace exits, read its symbolication summary. Treat meaningful first-party \"have library but no symbol\" lines as a failed trace unless they are tiny noise. Unsymbolicated system-framework or ETTrace internal buckets are usually acceptable.\n\n## Capture\n\nFor launch traces:\n\n```bash\ncd \"$RUN_DIR\"\nCAPTURE_MARKER=\"$RUN_DIR\u002F.ettrace-capture-start\"\n: > \"$CAPTURE_MARKER\"\nfind \"$RUN_DIR\" -maxdepth 1 \\( -name 'output.json' -o -name 'output_*.json' \\) -delete\nettrace --simulator --launch --verbose --dsyms \"$DSYMS\"\n```\n\nUse `--launch` only when measuring startup or first render. The first launch connection can force quit the app; relaunch from the simulator home screen rather than Xcode if prompted. For first-launch-after-install traces, temporarily set `ETTraceRunAtStartup=YES` in the app Info.plist, then run `ettrace --simulator` and launch from the home screen.\n\nFor runtime flow traces:\n\n```bash\ncd \"$RUN_DIR\"\nCAPTURE_MARKER=\"$RUN_DIR\u002F.ettrace-capture-start\"\n: > \"$CAPTURE_MARKER\"\nfind \"$RUN_DIR\" -maxdepth 1 \\( -name 'output.json' -o -name 'output_*.json' \\) -delete\nettrace --simulator --verbose --dsyms \"$DSYMS\"\n```\n\nStart from a stable screen, start ETTrace, perform exactly one focused flow, wait until visible work is complete, then stop the runner. For wider attribution, add `--multi-thread`; otherwise start with the main thread.\n\nIn Codex, run `ettrace` with a TTY and answer prompts with `write_stdin`. Without a TTY, the runner can exit without a useful trace.\n\n## Preserve Outputs\n\nThe next ETTrace run can overwrite processed flamegraph files, so preserve fresh `output_\u003Cthread-id>.json` files immediately. Do not analyze a saved `output.json`; ETTrace also serves a viewer route with that name, and raw `emerge-output\u002Foutput.json` files are not the processed flamegraph artifacts this workflow expects.\n\n```bash\nPRESERVED_DIR=\"$(mktemp -d \"$RUN_DIR\u002Frun-$(date +%Y%m%d-%H%M%S).XXXXXX\")\"\n: > \"$PRESERVED_DIR\u002Fsummary.txt\"\nif [ ! -e \"$CAPTURE_MARKER\" ]; then\n  echo \"error: capture marker missing; start a fresh ETTrace capture before preserving outputs\" >&2\n  exit 1\nfi\nfind \"$RUN_DIR\" -maxdepth 1 -name 'output_*.json' -newer \"$CAPTURE_MARKER\" -print | while IFS= read -r json; do\n  preserved=\"$PRESERVED_DIR\u002F${json##*\u002F}\"\n  cp \"$json\" \"$preserved\"\n  {\n    echo \"## ${preserved##*\u002F}\"\n    python3 \"$SKILL_DIR\u002Fscripts\u002Fanalyze_flamegraph_json.py\" \"$preserved\"\n  } >> \"$PRESERVED_DIR\u002Fsummary.txt\"\ndone\nif [ ! -s \"$PRESERVED_DIR\u002Fsummary.txt\" ]; then\n  echo \"error: no fresh processed ETTrace output JSON found in $RUN_DIR\" >&2\n  exit 1\nfi\n```\n\nAnalyze only processed `output_*.json` files in `RUN_DIR`. Ignore `output.json` and raw `emerge-output\u002Foutput.json` files unless debugging ETTrace itself. If the analyzer rejects the JSON shape, capture again with the Homebrew ETTrace runner and matching app-side `ETTrace.xcframework` tag instead of trying to interpret the rejected file.\n\n## Read The Profile\n\nStart from `run-*\u002Fsummary.txt`, then inspect processed JSON directly if needed.\n\nReport:\n\n- exact flow, app build, simulator model\u002Fruntime, and run count\n- processed flamegraph JSON paths\n- top active leaves and inclusive first-party stacks with sample weights or percentages\n- whether symbols were complete for app-owned binaries\n- caveats such as first-run setup, simulator-only cost, network variance, or low sample count\n- before\u002Fafter deltas only when the same flow was captured with comparable setup\n\n\n## Cleanup\n\nRemove temporary ETTrace app wiring when profiling is complete unless the user asked to keep it. 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-s",{"type":42,"tag":139,"props":2544,"children":2545},{"style":152},[2546],{"type":47,"value":280},{"type":42,"tag":139,"props":2548,"children":2549},{"style":168},[2550],{"type":47,"value":2134},{"type":42,"tag":139,"props":2552,"children":2553},{"style":214},[2554],{"type":47,"value":2139},{"type":42,"tag":139,"props":2556,"children":2557},{"style":152},[2558],{"type":47,"value":509},{"type":42,"tag":139,"props":2560,"children":2561},{"style":152},[2562],{"type":47,"value":181},{"type":42,"tag":139,"props":2564,"children":2565},{"style":146},[2566],{"type":47,"value":186},{"type":42,"tag":139,"props":2568,"children":2569},{"class":141,"line":874},[2570,2574,2578,2583,2587,2591],{"type":42,"tag":139,"props":2571,"children":2572},{"style":1569},[2573],{"type":47,"value":2191},{"type":42,"tag":139,"props":2575,"children":2576},{"style":152},[2577],{"type":47,"value":280},{"type":42,"tag":139,"props":2579,"children":2580},{"style":214},[2581],{"type":47,"value":2582},"error: no fresh processed ETTrace output JSON found in ",{"type":42,"tag":139,"props":2584,"children":2585},{"style":168},[2586],{"type":47,"value":285},{"type":42,"tag":139,"props":2588,"children":2589},{"style":152},[2590],{"type":47,"value":509},{"type":42,"tag":139,"props":2592,"children":2593},{"style":152},[2594],{"type":47,"value":2209},{"type":42,"tag":139,"props":2596,"children":2597},{"class":141,"line":887},[2598,2602],{"type":42,"tag":139,"props":2599,"children":2600},{"style":1569},[2601],{"type":47,"value":2217},{"type":42,"tag":139,"props":2603,"children":2604},{"style":585},[2605],{"type":47,"value":2222},{"type":42,"tag":139,"props":2607,"children":2608},{"class":141,"line":896},[2609],{"type":42,"tag":139,"props":2610,"children":2611},{"style":146},[2612],{"type":47,"value":261},{"type":42,"tag":50,"props":2614,"children":2615},{},[2616,2618,2623,2625,2630,2632,2637,2639,2644,2646,2651],{"type":47,"value":2617},"Analyze only processed ",{"type":42,"tag":56,"props":2619,"children":2621},{"className":2620},[],[2622],{"type":47,"value":1706},{"type":47,"value":2624}," files in ",{"type":42,"tag":56,"props":2626,"children":2628},{"className":2627},[],[2629],{"type":47,"value":171},{"type":47,"value":2631},". Ignore ",{"type":42,"tag":56,"props":2633,"children":2635},{"className":2634},[],[2636],{"type":47,"value":1684},{"type":47,"value":2638}," and raw ",{"type":42,"tag":56,"props":2640,"children":2642},{"className":2641},[],[2643],{"type":47,"value":2040},{"type":47,"value":2645}," files unless debugging ETTrace itself. If the analyzer rejects the JSON shape, capture again with the Homebrew ETTrace runner and matching app-side ",{"type":42,"tag":56,"props":2647,"children":2649},{"className":2648},[],[2650],{"type":47,"value":337},{"type":47,"value":2652}," tag instead of trying to interpret the rejected file.",{"type":42,"tag":65,"props":2654,"children":2656},{"id":2655},"read-the-profile",[2657],{"type":47,"value":2658},"Read The Profile",{"type":42,"tag":50,"props":2660,"children":2661},{},[2662,2664,2670],{"type":47,"value":2663},"Start from ",{"type":42,"tag":56,"props":2665,"children":2667},{"className":2666},[],[2668],{"type":47,"value":2669},"run-*\u002Fsummary.txt",{"type":47,"value":2671},", then inspect processed JSON directly if needed.",{"type":42,"tag":50,"props":2673,"children":2674},{},[2675],{"type":47,"value":2676},"Report:",{"type":42,"tag":373,"props":2678,"children":2679},{},[2680,2685,2690,2695,2700,2705],{"type":42,"tag":76,"props":2681,"children":2682},{},[2683],{"type":47,"value":2684},"exact flow, app build, simulator model\u002Fruntime, and run count",{"type":42,"tag":76,"props":2686,"children":2687},{},[2688],{"type":47,"value":2689},"processed flamegraph JSON paths",{"type":42,"tag":76,"props":2691,"children":2692},{},[2693],{"type":47,"value":2694},"top active leaves and inclusive first-party stacks with sample weights or percentages",{"type":42,"tag":76,"props":2696,"children":2697},{},[2698],{"type":47,"value":2699},"whether symbols were complete for app-owned binaries",{"type":42,"tag":76,"props":2701,"children":2702},{},[2703],{"type":47,"value":2704},"caveats such as first-run setup, simulator-only cost, network variance, or low sample count",{"type":42,"tag":76,"props":2706,"children":2707},{},[2708],{"type":47,"value":2709},"before\u002Fafter deltas only when the same flow was captured with comparable setup",{"type":42,"tag":65,"props":2711,"children":2713},{"id":2712},"cleanup",[2714],{"type":47,"value":2715},"Cleanup",{"type":42,"tag":50,"props":2717,"children":2718},{},[2719],{"type":47,"value":2720},"Remove temporary ETTrace app wiring when profiling is complete unless the user asked to keep it. Keep or discard run artifacts based on the active task.",{"type":42,"tag":2722,"props":2723,"children":2724},"style",{},[2725],{"type":47,"value":2726},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":2728,"total":2848},[2729,2748,2764,2776,2796,2818,2836],{"slug":2730,"name":2730,"fn":2731,"description":2732,"org":2733,"tags":2734,"stars":25,"repoUrl":26,"updatedAt":2747},"accessibility-and-inclusive-visualization","make data visualizations accessible","Make data visualizations accessible and inclusive. Use when the user needs chart or diagram accessibility guidance, text alternatives for complex visuals, color and contrast review, keyboard support, reduced-motion behavior for animation or parallax, or an accessibility QA workflow for exported figures, UML-like diagrams, and dashboards.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2735,2738,2741,2744],{"name":2736,"slug":2737,"type":15},"Accessibility","accessibility",{"name":2739,"slug":2740,"type":15},"Charts","charts",{"name":2742,"slug":2743,"type":15},"Data Visualization","data-visualization",{"name":2745,"slug":2746,"type":15},"Design","design","2026-06-30T19:00:57.102",{"slug":2749,"name":2749,"fn":2750,"description":2751,"org":2752,"tags":2753,"stars":25,"repoUrl":26,"updatedAt":2763},"agent-browser","automate browser interactions for agents","Browser automation CLI for AI agents. Use when the user needs to interact with websites, verify dev server output, test web apps, navigate pages, fill forms, click buttons, take screenshots, extract data, or automate any browser task. Also triggers when a dev server starts so you can verify it visually.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2754,2757,2760],{"name":2755,"slug":2756,"type":15},"Agents","agents",{"name":2758,"slug":2759,"type":15},"Browser Automation","browser-automation",{"name":2761,"slug":2762,"type":15},"Testing","testing","2026-04-06T18:41:03.44016",{"slug":2765,"name":2765,"fn":2766,"description":2767,"org":2768,"tags":2769,"stars":25,"repoUrl":26,"updatedAt":2775},"agent-browser-verify","verify dev server output with automated browser","Automated browser verification for dev servers. Triggers when a dev server starts to run a visual gut-check with agent-browser — verifies the page loads, checks for console errors, validates key UI elements, and reports pass\u002Ffail before continuing.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2770,2771,2774],{"name":2758,"slug":2759,"type":15},{"name":2772,"slug":2773,"type":15},"Local Development","local-development",{"name":2761,"slug":2762,"type":15},"2026-04-06T18:41:17.526867",{"slug":2777,"name":2777,"fn":2778,"description":2779,"org":2780,"tags":2781,"stars":25,"repoUrl":26,"updatedAt":2795},"agents-sdk","build AI agents on Cloudflare Workers","Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2782,2783,2786,2789,2792],{"name":2755,"slug":2756,"type":15},{"name":2784,"slug":2785,"type":15},"Cloudflare Workers","cloudflare-workers",{"name":2787,"slug":2788,"type":15},"SDK","sdk",{"name":2790,"slug":2791,"type":15},"Serverless","serverless",{"name":2793,"slug":2794,"type":15},"WebSockets","websockets","2026-04-06T18:39:51.717063",{"slug":2797,"name":2797,"fn":2798,"description":2799,"org":2800,"tags":2801,"stars":25,"repoUrl":26,"updatedAt":2817},"ai-elements","build chat UIs with AI Elements","AI Elements component library guidance — pre-built React components for AI interfaces built on shadcn\u002Fui. Use when building chat UIs, message displays, tool call rendering, streaming responses, reasoning panels, or any AI-native interface with the AI SDK.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2802,2805,2808,2811,2814],{"name":2803,"slug":2804,"type":15},"Frontend","frontend",{"name":2806,"slug":2807,"type":15},"React","react",{"name":2809,"slug":2810,"type":15},"shadcn\u002Fui","shadcn-ui",{"name":2812,"slug":2813,"type":15},"UI Components","ui-components",{"name":2815,"slug":2816,"type":15},"Vercel","vercel","2026-04-06T18:40:59.619419",{"slug":2819,"name":2819,"fn":2820,"description":2821,"org":2822,"tags":2823,"stars":25,"repoUrl":26,"updatedAt":2835},"ai-gateway","configure Vercel AI Gateway","Vercel AI Gateway expert guidance. Use when configuring model routing, provider failover, cost tracking, or managing multiple AI providers through a unified API.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2824,2827,2830,2833,2834],{"name":2825,"slug":2826,"type":15},"AI Infrastructure","ai-infrastructure",{"name":2828,"slug":2829,"type":15},"Cost Optimization","cost-optimization",{"name":2831,"slug":2832,"type":15},"LLM","llm",{"name":13,"slug":14,"type":15},{"name":2815,"slug":2816,"type":15},"2026-04-06T18:40:44.377464",{"slug":2837,"name":2837,"fn":2838,"description":2839,"org":2840,"tags":2841,"stars":25,"repoUrl":26,"updatedAt":2847},"ai-generation-persistence","implement persistence patterns for AI generations","AI generation persistence patterns — unique IDs, addressable URLs, database storage, and cost tracking for every LLM generation",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2842,2843,2846],{"name":2828,"slug":2829,"type":15},{"name":2844,"slug":2845,"type":15},"Database","database",{"name":2831,"slug":2832,"type":15},"2026-04-06T18:41:08.513425",600,{"items":2850,"total":3047},[2851,2872,2895,2912,2928,2945,2964,2976,2990,3004,3016,3031],{"slug":2852,"name":2852,"fn":2853,"description":2854,"org":2855,"tags":2856,"stars":2869,"repoUrl":2870,"updatedAt":2871},"prior-auth-packet-builder","build healthcare prior authorization packets","Build a concise prior authorization packet from local case files and payer policy docs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2857,2860,2863,2866],{"name":2858,"slug":2859,"type":15},"Documents","documents",{"name":2861,"slug":2862,"type":15},"Healthcare","healthcare",{"name":2864,"slug":2865,"type":15},"Insurance","insurance",{"name":2867,"slug":2868,"type":15},"Regulatory Compliance","regulatory-compliance",28169,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fopenai-agents-python","2026-04-16T05:11:39.180399",{"slug":2873,"name":2873,"fn":2874,"description":2875,"org":2876,"tags":2877,"stars":2892,"repoUrl":2893,"updatedAt":2894},"aspnet-core","build ASP.NET Core web applications","Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2878,2881,2883,2886,2889],{"name":2879,"slug":2880,"type":15},".NET","dotnet",{"name":2882,"slug":2873,"type":15},"ASP.NET Core",{"name":2884,"slug":2885,"type":15},"Blazor","blazor",{"name":2887,"slug":2888,"type":15},"C#","csharp",{"name":2890,"slug":2891,"type":15},"Web Development","web-development",23787,"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills","2026-04-12T05:07:02.819491",{"slug":2896,"name":2896,"fn":2897,"description":2898,"org":2899,"tags":2900,"stars":2892,"repoUrl":2893,"updatedAt":2911},"chatgpt-apps","build ChatGPT Apps SDK applications","Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2901,2904,2907,2910],{"name":2902,"slug":2903,"type":15},"Apps SDK","apps-sdk",{"name":2905,"slug":2906,"type":15},"ChatGPT","chatgpt",{"name":2908,"slug":2909,"type":15},"MCP","mcp",{"name":9,"slug":8,"type":15},"2026-04-12T05:07:05.468097",{"slug":2913,"name":2913,"fn":2914,"description":2915,"org":2916,"tags":2917,"stars":2892,"repoUrl":2893,"updatedAt":2927},"cli-creator","build CLIs from API docs","Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read\u002Fwrite commands, return stable JSON, manage auth, and pair with a companion skill.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2918,2921,2924],{"name":2919,"slug":2920,"type":15},"API Development","api-development",{"name":2922,"slug":2923,"type":15},"CLI","cli",{"name":2925,"slug":2926,"type":15},"Codex","codex","2026-04-12T05:07:04.132762",{"slug":2929,"name":2929,"fn":2930,"description":2931,"org":2932,"tags":2933,"stars":2892,"repoUrl":2893,"updatedAt":2944},"cloudflare-deploy","deploy projects to Cloudflare","Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2934,2937,2940,2941],{"name":2935,"slug":2936,"type":15},"Cloudflare","cloudflare",{"name":2938,"slug":2939,"type":15},"Cloudflare Pages","cloudflare-pages",{"name":2784,"slug":2785,"type":15},{"name":2942,"slug":2943,"type":15},"Deployment","deployment","2026-04-12T05:07:14.275118",{"slug":2946,"name":2946,"fn":2947,"description":2948,"org":2949,"tags":2950,"stars":2892,"repoUrl":2893,"updatedAt":2963},"define-goal","define and set measurable project goals","Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2951,2954,2957,2960],{"name":2952,"slug":2953,"type":15},"Productivity","productivity",{"name":2955,"slug":2956,"type":15},"Project Management","project-management",{"name":2958,"slug":2959,"type":15},"Strategy","strategy",{"name":2961,"slug":2962,"type":15},"Task Management","task-management","2026-05-23T06:17:16.870838",{"slug":2965,"name":2965,"fn":2966,"description":2967,"org":2968,"tags":2969,"stars":2892,"repoUrl":2893,"updatedAt":2975},"figma","translate Figma designs into code","Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2970,2971,2973,2974],{"name":2745,"slug":2746,"type":15},{"name":2972,"slug":2965,"type":15},"Figma",{"name":2803,"slug":2804,"type":15},{"name":2908,"slug":2909,"type":15},"2026-04-12T05:06:47.939943",{"slug":2977,"name":2977,"fn":2978,"description":2979,"org":2980,"tags":2981,"stars":2892,"repoUrl":2893,"updatedAt":2989},"figma-code-connect-components","connect Figma designs to code components","Connects Figma design components to code components using Code Connect mapping tools. Use when user says \"code connect\", \"connect this component to code\", \"map this component\", \"link component to code\", \"create code connect mapping\", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2982,2983,2986,2987,2988],{"name":2745,"slug":2746,"type":15},{"name":2984,"slug":2985,"type":15},"Design System","design-system",{"name":2972,"slug":2965,"type":15},{"name":2803,"slug":2804,"type":15},{"name":2812,"slug":2813,"type":15},"2026-05-10T05:59:52.971881",{"slug":2991,"name":2991,"fn":2992,"description":2993,"org":2994,"tags":2995,"stars":2892,"repoUrl":2893,"updatedAt":3003},"figma-create-design-system-rules","generate design system rules from Figma","Generates custom design system rules for the user's codebase. Use when user says \"create design system rules\", \"generate rules for my project\", \"set up design rules\", \"customize design system guidelines\", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2996,2997,2998,3001,3002],{"name":2745,"slug":2746,"type":15},{"name":2984,"slug":2985,"type":15},{"name":2999,"slug":3000,"type":15},"Documentation","documentation",{"name":2972,"slug":2965,"type":15},{"name":2803,"slug":2804,"type":15},"2026-05-16T06:07:47.821474",{"slug":3005,"name":3005,"fn":3006,"description":3007,"org":3008,"tags":3009,"stars":2892,"repoUrl":2893,"updatedAt":3015},"figma-implement-design","translate Figma designs into application code","Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions \"implement design\", \"generate code\", \"implement component\", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3010,3011,3012,3013,3014],{"name":2745,"slug":2746,"type":15},{"name":2972,"slug":2965,"type":15},{"name":2803,"slug":2804,"type":15},{"name":2812,"slug":2813,"type":15},{"name":2890,"slug":2891,"type":15},"2026-05-16T06:07:40.583615",{"slug":3017,"name":3017,"fn":3018,"description":3019,"org":3020,"tags":3021,"stars":2892,"repoUrl":2893,"updatedAt":3030},"hatch-pet","create animated pets for Codex","Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3022,3025,3026,3029],{"name":3023,"slug":3024,"type":15},"Animation","animation",{"name":2925,"slug":2926,"type":15},{"name":3027,"slug":3028,"type":15},"Creative","creative",{"name":2745,"slug":2746,"type":15},"2026-05-02T05:31:48.48485",{"slug":3032,"name":3032,"fn":3033,"description":3034,"org":3035,"tags":3036,"stars":2892,"repoUrl":2893,"updatedAt":3046},"imagegen","generate and edit raster images","Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG\u002Fvector\u002Fcode-native assets, extending an established icon or logo system, or building the visual directly in HTML\u002FCSS\u002Fcanvas.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3037,3038,3039,3042,3045],{"name":3027,"slug":3028,"type":15},{"name":2745,"slug":2746,"type":15},{"name":3040,"slug":3041,"type":15},"Image Generation","image-generation",{"name":3043,"slug":3044,"type":15},"Images","images",{"name":9,"slug":8,"type":15},"2026-05-15T06:23:24.312127",675]