[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MC3ZQ2T5X4PYF8HMQFFSGR":3,"skill-same:01M6MC3ZQ2T5X4PYF8HMQFFSGR":89},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":26,"publishedAt":48,"linkOnly":49,"markdownContent":50,"markdownBody":51,"frontMatter":52,"refName":59,"commitSha":60,"skillDirectory":61,"forksCount":62,"repositoryHtmlUrl":63,"repositoryHomepageUrl":64,"ownerHtmlUrl":65,"ownerBlogUrl":66,"ownerDescription":67,"updatedAt":68,"install":69,"resources":82},"01M6MC3ZQ2T5X4PYF8HMQFFSGR","django-test-profiling",null,"Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Use when a Django project has slow tests, unclear test-runtime bottlenecks, CI timing problems, startup overhead, database setup overhead, or a request to find the slowest tests before optimizing.","hashgraph-online\u002Fawesome-codex-plugins","hashgraph-online","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160371962?v=4","01M6CNB6NRJVNNGN14TR01Q6D3","HOL (Hashgraph Online)","01M6JT1HSKKG9V68KQAQGBA7XP",1575,"MIT","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FLVTD-LLC\u002Fskills\u002Fskills\u002Fdjango-test-profiling\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"test","django test profiling","profiling","django","pytest","when","request","overhead","cProfile","timing","tests","runtime","project","runner","testing","use","visualizations","ci","database","code","performance","2026-11-10 10:12:30",false,"---\nname: django-test-profiling\ndescription: Profile and measure slow Django test suites with Django's runner, pytest-django, shell timing, py-spy, cProfile, pytest durations, and profiler visualizations. Use when a Django project has slow tests, unclear test-runtime bottlenecks, CI timing problems, startup overhead, database setup overhead, or a request to find the slowest tests before optimizing.\nlicense: MIT\ncompatibility: Codex, Claude Code, and other Agent Skills-compatible clients.\nmetadata:\n  version: \"0.1.0\"\n  displayName: Django Test Profiling\n  category: Django\n  tags: django,testing,profiling,pytest,performance\n---\n\n# Django Test Profiling\n\nUse this skill before changing a Django test suite for speed. Measurement decides which optimization is worth doing; otherwise it is easy to spend time on harmless settings while the real cost sits in startup, database setup, fixture construction, or a small set of slow tests.\n\n## Measurement Workflow\n\n1. Capture a full wall-clock baseline.\n   - Prefer shell timing because it includes Python startup, Django import time, test discovery, database setup, and teardown.\n   - Record the exact command, environment, and repeat count.\n\n2. Separate framework phases when possible.\n   - For Django's runner, use `--timing` to see database setup and teardown.\n   - For pytest, compare shell timing with `pytest --durations`.\n\n3. Find the slowest tests.\n   - For pytest-django, start with `pytest --durations 20`.\n   - For Django's runner, use an existing slow-test plugin or a small custom runner only when the project does not already have one.\n\n4. Profile only after you know where the time goes.\n   - Use `py-spy` first for a low-overhead whole-run view.\n   - Use `cProfile` when you need exhaustive Python call data.\n\n5. Convert the result into a ranked action list.\n   - Identify whether the expensive part is startup, database creation, repeated setup, test data, query count, I\u002FO, cache\u002Ffile\u002Fstorage access, or a specific test body.\n   - Hand off to `django-test-performance`, `django-test-data`, or `django-test-parallelization` when the next step fits those skills.\n\n## Commands\n\n```bash\ntime python manage.py test\npython manage.py test --timing\npytest --durations 20\n```\n\nFor profiling command variants and interpretation guidance, read [profiler-commands.md](references\u002Fprofiler-commands.md).\n\n## Decision Rules\n\n- Treat shell timing as the authoritative user-visible duration.\n- Use Django `--timing` when database setup or teardown may dominate.\n- Optimize the slowest measured tests first, not the tests that look suspicious.\n- Put noisy duration reports in CI logs when they distract from normal local runs.\n- Use `py-spy --subprocesses` when the test runner uses child processes.\n- Sort cProfile by cumulative time first; inspect self-time only after you understand the caller chain.\n\n## Common Mistakes\n\n- Trusting a framework's final \"ran in X seconds\" line as the complete runtime.\n- Comparing Django runner timing and pytest timing as if they measure identical phases.\n- Profiling everything before finding slow tests.\n- Reading unsorted cProfile output and chasing import internals.\n- Expecting sampling profiles to catch every short hot path.\n- Optimizing a helper without checking how often it is reached by tests.\n\n## Verification\n\nBefore reporting findings, include:\n\n- The exact baseline command and measured wall-clock time.\n- The slowest tests or slowest phases.\n- The profiler used, if any, and why it was appropriate.\n- The top 3 practical next actions, ordered by expected impact.\n","# Django Test Profiling\n\nUse this skill before changing a Django test suite for speed. Measurement decides which optimization is worth doing; otherwise it is easy to spend time on harmless settings while the real cost sits in startup, database setup, fixture construction, or a small set of slow tests.\n\n## Measurement Workflow\n\n1. Capture a full wall-clock baseline.\n   - Prefer shell timing because it includes Python startup, Django import time, test discovery, database setup, and teardown.\n   - Record the exact command, environment, and repeat count.\n\n2. Separate framework phases when possible.\n   - For Django's runner, use `--timing` to see database setup and teardown.\n   - For pytest, compare shell timing with `pytest --durations`.\n\n3. Find the slowest tests.\n   - For pytest-django, start with `pytest --durations 20`.\n   - For Django's runner, use an existing slow-test plugin or a small custom runner only when the project does not already have one.\n\n4. Profile only after you know where the time goes.\n   - Use `py-spy` first for a low-overhead whole-run view.\n   - Use `cProfile` when you need exhaustive Python call data.\n\n5. Convert the result into a ranked action list.\n   - Identify whether the expensive part is startup, database creation, repeated setup, test data, query count, I\u002FO, cache\u002Ffile\u002Fstorage access, or a specific test body.\n   - Hand off to `django-test-performance`, `django-test-data`, or `django-test-parallelization` when the next step fits those skills.\n\n## Commands\n\n```bash\ntime python manage.py test\npython manage.py test --timing\npytest --durations 20\n```\n\nFor profiling command variants and interpretation guidance, read [profiler-commands.md](references\u002Fprofiler-commands.md).\n\n## Decision Rules\n\n- Treat shell timing as the authoritative user-visible duration.\n- Use Django `--timing` when database setup or teardown may dominate.\n- Optimize the slowest measured tests first, not the tests that look suspicious.\n- Put noisy duration reports in CI logs when they distract from normal local runs.\n- Use `py-spy --subprocesses` when the test runner uses child processes.\n- Sort cProfile by cumulative time first; inspect self-time only after you understand the caller chain.\n\n## Common Mistakes\n\n- Trusting a framework's final \"ran in X seconds\" line as the complete runtime.\n- Comparing Django runner timing and pytest timing as if they measure identical phases.\n- Profiling everything before finding slow tests.\n- Reading unsorted cProfile output and chasing import internals.\n- Expecting sampling profiles to catch every short hot path.\n- Optimizing a helper without checking how often it is reached by tests.\n\n## Verification\n\nBefore reporting findings, include:\n\n- The exact baseline command and measured wall-clock time.\n- The slowest tests or slowest phases.\n- The profiler used, if any, and why it was appropriate.\n- The top 3 practical next actions, ordered by expected impact.\n",{"name":5,"license":15,"metadata":53,"description":7,"compatibility":58},{"tags":54,"version":55,"category":56,"displayName":57},"django,testing,profiling,pytest,performance","0.1.0","Django","Django Test Profiling","Codex, Claude Code, and other Agent Skills-compatible clients.","main","2b63f856ce19c2a797929cacabd9e0fc936812fa","plugins\u002FLVTD-LLC\u002Fskills\u002Fskills\u002Fdjango-test-profiling",491,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins","https:\u002F\u002Fhol.org\u002Fplugins\u002Fbest-codex-plugins","https:\u002F\u002Fgithub.com\u002Fhashgraph-online","https:\u002F\u002Fhol.org","Open-source standards and developer tools for interoperable AI agents: discovery, identity, communication, payments, privacy and security.","2026-11-14 14:06:13",{"source":8,"skillName":5,"commands":70,"prompt":80,"zipAvailable":81},[71,74,77],{"tool":72,"command":73},"npx","npx skills add hashgraph-online\u002Fawesome-codex-plugins --skill django-test-profiling",{"tool":75,"command":76},"bunx","bunx skills add hashgraph-online\u002Fawesome-codex-plugins --skill django-test-profiling",{"tool":78,"command":79},"pnpm","pnpm dlx skills add hashgraph-online\u002Fawesome-codex-plugins --skill django-test-profiling","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FLVTD-LLC\u002Fskills\u002Fskills\u002Fdjango-test-profiling\u002FSKILL.md",true,[83],{"path":84,"resourceType":85,"resourceTypeDesc":86,"sizeBytes":87,"sourceHtmlUrl":88},"references\u002Fprofiler-commands.md","REFERENCE","参考文档",2286,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FLVTD-LLC\u002Fskills\u002Fskills\u002Fdjango-test-profiling\u002Freferences\u002Fprofiler-commands.md",[90,99,106,113,139,163],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":98},"01M746ZWACVKMZ1BJXJZHYJSSX","migrate-to-e2e","Moves an existing Playwright, Cypress, Selenium, Appium, Detox, Maestro, or TesterArmy suite to e2e one slice at a time, with the old suite running beside the new one until each ported test is proven. Keeps a MIGRATION.md progress file so any later session resumes where the last stopped. Optionally plants a defect to show both suites catch it. Use for \u002Fmigrate-to-e2e, \"migrate our tests to e2e\", \"port these Maestro flows\", \"move our TesterArmy tests\", or when a project has an e2e config and an older suite still running.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fmigrate-to-e2e\u002FSKILL.md",[],[],"2026-11-11 15:11:14",{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":98},"01M746ZPTAX1Q0FBKAB1CYND7E","e2e","Writes, runs, and debugs end-to-end tests for web and mobile apps with e2e, the agentic test runner, which mixes agent.act goals with exact locator assertions on a Playwright browser or an iOS or Android device. Also drives a project's running app live over the e2e MCP server to look at a screen, check a UI change, take a screenshot or record a video, and try a locator; and runs bug bashes, parallel e2e explore runs with each bug proven by a repro test. Use when a project depends on e2e or has an e2e.config.ts, when asked for end-to-end, browser, mobile, or agentic UI tests, to check a change in the running app, to QA or bug bash an app or branch, or when an e2e run fails.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fe2e\u002FSKILL.md",[],[],{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":98},"01M746ZJN784HVHMDP9MQGCSGG","create-verification-skill","Generate a project-local verify-\u003Capp> skill on top of e2e, so any coding agent can launch the app, check it is worth driving, exercise a feature the way a user does, keep evidence, and bug bash it. Writes the skill, a feature map with one explore charter per feature, and proves it once. Use for \u002Fcreate-verification-skill, \"make a verification skill for this repo\", or when a project has no scripted way to prove UI behavior.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fcreate-verification-skill\u002FSKILL.md",[],[],{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":48},"01M716A6ETNB9B1SQ3GXZC75VR","deja-search","deja-vu memory — search the user's past AI coding sessions with the deja CLI. Holds what they already settled and never wrote into the repo (naming rules, banned or already-tried tools, required checks before merge, preferred values, who owns what). Use before your first edit in a task, before you call a change done or ready to merge, before you recommend a tool, library, design or reviewer, before re-debugging an error that may already be solved, when they say 'didn't we fix this before', 'what did we decide about X' or 'I already have that', and before telling them something on this machine does not exist.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-search\u002FSKILL.md",[],[120,121,122,123,124,125,126,127,128,129,130,32,131,132,133,134,135,136,137,138],"search","deja search","never","error","ready","memory","re","decide","fix","design","debugging","you","done","reviewer","io","change","cli","merge","past",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":145,"publishedAt":48},"01M716A3J2W5SENSE9VGMXB375","deja-reflect","End-of-session reflection and memory curation with deja-vu. Review what was decided, what commands broke and what repaired them, and record durable project rules or decisions with deja remember so the next session starts with them.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-reflect\u002FSKILL.md",[],[146,147,148,134,149,150,151,152,153,154,155,156,157,158,125,159,39,160,161,162],"deja reflect","reflect","review","with","record","github","next","https","node","Rules","decisions","brew","remember","project rules","session","end","reflection",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":94,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":176,"publishedAt":48},"01M715T3RR4BAYSR57HPPTJ0PF","revid","Make, edit, export and post AI videos with Revid (revid.ai) through the Revid MCP server. Use whenever the user wants a short-form or long-form video made (from an idea, a script, a URL, an article, a PDF, a tweet, a product page, their own clips, or a song), wants to find what is going viral on TikTok, YouTube, Instagram or X before making something, wants to edit or re-export an existing Revid project, generate a standalone AI image or clip, make a series episode, or publish and schedule a finished video to connected social accounts. Covers setup (hosted MCP with OAuth, or an API key), the 36 tools, credits, polling and the rules for publishing. Routes to the more specific revid-* skills when one fits.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftmakersas\u002Frevid-skills\u002Fskills\u002Frevid\u002FSKILL.md",[169,172,173],{"categoryNo":170,"categoryName":171,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":174,"categoryName":175,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",[165,177,178,179,180,181,182,39,183,126,184,185,186,187,32,188,189,190,191,192],"URL","Video","short-form","standalone","PDF","viral","tiktok","short","social","MCP","song","image","mcp server","schedule","api","publish"]