[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71AWV2ZXZ3QXN94MBKSWN1C":3,"skill-same:01M71AWV2ZXZ3QXN94MBKSWN1C":86},{"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":16,"sourceHtmlUrl":17,"categories":18,"keywords":19,"publishedAt":40,"linkOnly":41,"markdownContent":42,"markdownBody":43,"frontMatter":44,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M71AWV2ZXZ3QXN94MBKSWN1C","atheris-fuzzing-current",null,"Build and qualify bounded coverage-guided Python fuzzing harnesses with Atheris. Use for parser or API fuzzing, structured inputs, crash replay and native extension campaign setup; preserve byte domains, target instrumentation and explicit sanitizer scope.","strmt7\u002Fai_skills_collection_benchmarked","strmt7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F28989754?v=4","01M71929P914SWKQ7QJV24NBBY","Stratos","01M71929Q9VGKQ7PWYR95VSQQQ",1,"CC-BY-SA-4.0","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002FSKILL.md",[],[20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],"fuzzing","atheris fuzzing current","atheris","qualify","python","target","preserve","for","sanitizer","harnesses","with","native","api","domains","coverage-guided","scope","replay","campaign","use","coverage","2026-11-10 10:12:30",false,"---\nname: atheris-fuzzing-current\ndescription: Build and qualify bounded coverage-guided Python fuzzing harnesses with Atheris. Use for parser or API fuzzing, structured inputs, crash replay and native extension campaign setup; preserve byte domains, target instrumentation and explicit sanitizer scope.\nlicense: CC-BY-SA-4.0\nmetadata:\n  status: experimental-unbenchmarked\n---\n\n# Atheris fuzzing\n\nDefine the target contract first: accepted bytes\u002Ftext\u002Ftyped inputs, documented\nrejections, invariants and independently specified wrong outcomes. Keep crash\nreplay, coverage, semantic correctness and native memory-safety results separate.\n\nVerify the latest stable release and platform artifacts before installation.\nAs qualified on 2026-10-02, Atheris 3.1.0 has Linux x86-64 wheels for Python\n3.12–3.14; its README also advertises source support for 3.11. Only Linux\u002FPython\n3.14.8 pure-Python execution was qualified here. Pin dependency digests and the\nexecution image; verify `importlib.metadata.version(\"atheris\")`. A newer source\nHEAD or supported-version statement is not proof of a matching release wheel.\n\nInstrument the actual Python target before importing it; instrument the wrapper\nwhen needed for initial coverage. Verify that executions reach target branches.\nCatch only its documented input-rejection exceptions. Preserve unexpected\nexceptions. Include empty and malformed inputs when the contract requires them.\nKeep harness state deterministic and reset mutable state between inputs.\n\nPass bytes directly when the API accepts bytes. For text APIs, decode according\nto the specified encoding\u002Ferror policy; do not silently drop invalid bytes unless\nthat normalization is explicitly the target. An HTTPResponse supplied with body\nbytes tests body reading, not HTTP message parsing. Choose the actual wire parser\nwhen status, headers, framing or request syntax is in scope.\n\nFor typed targets, use `FuzzedDataProvider` with bounded fields in a fixed order.\nTreat its schema as part of corpus provenance. Exhausted input yields defaults;\nmeasure meaningful target coverage, valid-domain reach and input diversity.\nRequire a minimum length only when the independently specified target requires it.\n\nRun in an owned disposable environment with explicit wall-clock, per-input,\nmemory, process, output, input-size and corpus\u002Fartifact bounds. Keep the target\noffline unless networking is explicitly required and isolated. Start with a\nqualified small corpus and a bounded run; `-atheris_runs=N` permits graceful\nPython coverage export, whereas libFuzzer's `-runs=N` does not guarantee it.\nRecord exact versions, flags, source\u002Fcorpus hashes, instrumentation, seed,\nresources, raw outputs and cleanup. Reproduce and minimize failures before\nclassifying them; known-seed replay does not establish new bug discovery.\n\nNative extensions need a separate qualification: a compatible Clang\u002FlibFuzzer\u002F\nsanitizer build, target instrumentation symbols, successful runtime startup and\nan observed known instrumented defect. Locate installed preload libraries with\n`atheris.path()` and verify the selected file, rather than hard-coding an\ninterpreter path or using the package's subdirectory. Do not preload globally.\nDocument interpreter accommodations and excluded leak\u002Fexception classes;\nallocation denial of service is not universally low impact. Preserve independent\nsemantic\u002Ferror tests alongside a narrowly scoped native campaign.\n\nSee [qualification boundaries](references\u002Fqualification.md). Original provenance\nand attribution accompany this overlay. No coding-agent improvement is established.\n","# Atheris fuzzing\n\nDefine the target contract first: accepted bytes\u002Ftext\u002Ftyped inputs, documented\nrejections, invariants and independently specified wrong outcomes. Keep crash\nreplay, coverage, semantic correctness and native memory-safety results separate.\n\nVerify the latest stable release and platform artifacts before installation.\nAs qualified on 2026-10-02, Atheris 3.1.0 has Linux x86-64 wheels for Python\n3.12–3.14; its README also advertises source support for 3.11. Only Linux\u002FPython\n3.14.8 pure-Python execution was qualified here. Pin dependency digests and the\nexecution image; verify `importlib.metadata.version(\"atheris\")`. A newer source\nHEAD or supported-version statement is not proof of a matching release wheel.\n\nInstrument the actual Python target before importing it; instrument the wrapper\nwhen needed for initial coverage. Verify that executions reach target branches.\nCatch only its documented input-rejection exceptions. Preserve unexpected\nexceptions. Include empty and malformed inputs when the contract requires them.\nKeep harness state deterministic and reset mutable state between inputs.\n\nPass bytes directly when the API accepts bytes. For text APIs, decode according\nto the specified encoding\u002Ferror policy; do not silently drop invalid bytes unless\nthat normalization is explicitly the target. An HTTPResponse supplied with body\nbytes tests body reading, not HTTP message parsing. Choose the actual wire parser\nwhen status, headers, framing or request syntax is in scope.\n\nFor typed targets, use `FuzzedDataProvider` with bounded fields in a fixed order.\nTreat its schema as part of corpus provenance. Exhausted input yields defaults;\nmeasure meaningful target coverage, valid-domain reach and input diversity.\nRequire a minimum length only when the independently specified target requires it.\n\nRun in an owned disposable environment with explicit wall-clock, per-input,\nmemory, process, output, input-size and corpus\u002Fartifact bounds. Keep the target\noffline unless networking is explicitly required and isolated. Start with a\nqualified small corpus and a bounded run; `-atheris_runs=N` permits graceful\nPython coverage export, whereas libFuzzer's `-runs=N` does not guarantee it.\nRecord exact versions, flags, source\u002Fcorpus hashes, instrumentation, seed,\nresources, raw outputs and cleanup. Reproduce and minimize failures before\nclassifying them; known-seed replay does not establish new bug discovery.\n\nNative extensions need a separate qualification: a compatible Clang\u002FlibFuzzer\u002F\nsanitizer build, target instrumentation symbols, successful runtime startup and\nan observed known instrumented defect. Locate installed preload libraries with\n`atheris.path()` and verify the selected file, rather than hard-coding an\ninterpreter path or using the package's subdirectory. Do not preload globally.\nDocument interpreter accommodations and excluded leak\u002Fexception classes;\nallocation denial of service is not universally low impact. Preserve independent\nsemantic\u002Ferror tests alongside a narrowly scoped native campaign.\n\nSee [qualification boundaries](references\u002Fqualification.md). Original provenance\nand attribution accompany this overlay. No coding-agent improvement is established.\n",{"name":5,"license":15,"metadata":45,"description":7},{"status":46},"experimental-unbenchmarked","main","5c95bcac4646c5aed06bd9aed5235cfc7985aafc","included\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current",0,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked","https:\u002F\u002Fgithub.com\u002Fstrmt7","2026-11-11 04:18:12",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add strmt7\u002Fai_skills_collection_benchmarked --skill atheris-fuzzing-current",{"tool":60,"command":61},"bunx","bunx skills add strmt7\u002Fai_skills_collection_benchmarked --skill atheris-fuzzing-current",{"tool":63,"command":64},"pnpm","pnpm dlx skills add strmt7\u002Fai_skills_collection_benchmarked --skill atheris-fuzzing-current","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002FSKILL.md",true,[68,72,78,82],{"path":69,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":71,"sourceHtmlUrl":16},"LICENSE","许可证",20131,{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"NOTICE.md","REFERENCE","参考文档",765,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002FNOTICE.md",{"path":79,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":80,"sourceHtmlUrl":81},"provenance\u002Foriginal-SKILL.md",14938,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002Fprovenance\u002Foriginal-SKILL.md",{"path":83,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fqualification.md",1009,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fimproved\u002Fskills\u002Fatheris-fuzzing-current\u002Freferences\u002Fqualification.md",[87,119,149,175,200,228],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":92,"sourceHtmlUrl":93,"categories":94,"keywords":103,"publishedAt":40},"01M71D4H3T6M57DFKN8HENAWRV","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fwebapp-testing\u002FSKILL.md",[95,100],{"categoryNo":96,"categoryName":97,"taxonomyType":98,"taxonomyTypeDesc":99},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":101,"categoryName":102,"taxonomyType":98,"taxonomyTypeDesc":99},"01JBSEEDCAT000000000000009","前端开发",[104,105,106,27,107,108,109,110,111,112,113,30,114,115,116,117,118],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","playwright","web","behavior","ui","screenshots",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":123,"sourceHtmlUrl":124,"categories":125,"keywords":129,"publishedAt":40},"01M71D4CQR2A2TB7GASCR5ZBG3","skill-creator","Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Fofficial-reference\u002Fskill-creator-anthropics\u002FSKILL.md",[126],{"categoryNo":127,"categoryName":128,"taxonomyType":98,"taxonomyTypeDesc":99},"01JBSEEDCAT000000000000023","Skill与智能体开发",[130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,27,148],"skill creator","creator","performance","improve","run evals","new","when","analysis","create","optimize","variance analysis","run","edit","benchmark","a skill","existing skill","evals","modify","accuracy",{"skillNo":150,"name":151,"nameZh":6,"description":152,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":153,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":158,"publishedAt":40},"01M71D488XHEZVXXSXFYP8ENMH","playwright-skill","Complete browser automation with Playwright. Auto-detects dev servers, writes reusable test scripts, and supports screenshots, responsive checks, UX validation, login flows, link checks, and arbitrary browser automation. Use when the user wants to test a website, automate browser interactions, validate web functionality, or perform browser-based testing.","MIT","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Ftesting-qa-benchmarking\u002Flatest-release-browser-automation\u002Fplaywright-skill\u002FSKILL.md",[156,157],{"categoryNo":96,"categoryName":97,"taxonomyType":98,"taxonomyTypeDesc":99},{"categoryNo":127,"categoryName":128,"taxonomyType":98,"taxonomyTypeDesc":99},[114,159,160,161,105,162,163,136,164,113,165,166,167,168,169,170,171,172,173,174],"playwright skill","browser automation","flows","auto","access","Bash","website","ux","login","scripts","read","write","node","install","network","responsive",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":179,"sourceHtmlUrl":180,"categories":181,"keywords":183,"publishedAt":40},"01M71CY25GM939M6RES91QSG3T","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Fweb-artifacts-builder\u002FSKILL.md",[182],{"categoryNo":101,"categoryName":102,"taxonomyType":98,"taxonomyTypeDesc":99},[184,185,186,115,187,188,189,27,190,191,109,192,38,193,194,195,196,197,198,199],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":201,"name":202,"nameZh":6,"description":203,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":91,"licenseFileUrl":204,"sourceHtmlUrl":205,"categories":206,"keywords":216,"publishedAt":40},"01M71CXZB60QJJ1H4S3NN94WMZ","frontend-design","Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML\u002FCSS layouts, or when styling\u002Fbeautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fsearch-retrieval-web-automation\u002Fofficial-reference\u002Ffrontend-design\u002FSKILL.md",[207,208,211],{"categoryNo":101,"categoryName":102,"taxonomyType":98,"taxonomyTypeDesc":99},{"categoryNo":209,"categoryName":210,"taxonomyType":98,"taxonomyTypeDesc":99},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":212,"categoryName":213,"taxonomyType":214,"taxonomyTypeDesc":215},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[109,217,218,189,219,220,221,107,222,223,38,136,186,224,194,225,195,226,227,30],"design","frontend design","ui design","generic","aesthetics","landing","pages","code","web ui","react components","examples",{"skillNo":229,"name":230,"nameZh":6,"description":231,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":153,"licenseFileUrl":6,"sourceHtmlUrl":232,"categories":233,"keywords":234,"publishedAt":40},"01M71CVZ54WFBTVA7R16PFY1ZE","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fzarr-python\u002FSKILL.md",[],[235,24,236,237,238,239,240,241,242,27,243,244,245,246,247,248,249,250],"zarr python","zarr","arrays","Cloud Storage","scientific","storage","parallel","dask","numpy","gcs","s3","integration","scientific computing","cloud","scale","pipelines"]