[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GVPVM013ERS08P58T6D2MF":3,"skill-same:01M6GVPVM013ERS08P58T6D2MF":91},{"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":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":66},"01M6GVPVM013ERS08P58T6D2MF","issue-flow",null,"Use when a GitHub issue should be driven through clarification recovery, spec-build-test-QA-acceptance, and enforced human review gates with quality gates.","Flow-Research\u002Fharnessy","Flow-Research","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F204254796?v=4","01M6GVJZH9ZV0XGZTVBJRNW5BQ","Flow Research","01M6GVJZNSWAHPXW43628F7X76",30,"AGPL-3.0","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"issue flow","flow","issue","question","true","number","URL","with","gates","human review","use","review","continue","Bash","recovery","acceptance","qa","quality gates","test","github","2026-11-10 10:12:30",false,"---\nname: issue-flow\ndescription: \"Use when a GitHub issue should be driven through clarification recovery, spec-build-test-QA-acceptance, and enforced human review gates with quality gates.\"\ndisable-model-invocation: true\nallowed-tools: Read, Write, ApplyPatch, Grep, Glob, Bash, Question\nargument-hint: \"[continue|status|issue \u003Cnumber-or-url>]\"\n---\n\n# Issue Flow\n\n## Purpose\nDrive one GitHub issue through the full Harnessy delivery lifecycle using the repository's existing skills, mandatory evaluation gates, explicit human review checkpoints, and strategy-aware intake when a standard `docs\u002Fstrategy\u002F` folder exists. GitHub Project metadata is optional enrichment, not a required intake dependency.\n\n## Inputs\n- Optional arguments: `continue`, `status`, or `issue \u003Cnumber-or-url>`\n\n- Template paths are resolved from `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002F`.\n\n## Steps\n1. Follow the command specification in `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002Fcommands\u002Fissue-flow.md` exactly.\n2. Use existing child skills rather than replacing them.\n3. Run each new issue cycle in the canonical project-container worktree root `projects\u002F\u003Cproject-name>\u002Fworktrees\u002F\u003Cissue_id>_\u003Cfriendly_name>` when viewed from the container, or `..\u002Fworktrees\u002F\u003Cissue_id>_\u003Cfriendly_name>` when invoked from `projects\u002F\u003Cproject-name>\u002Fdev\u002F`, derived at runtime via `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002Fscripts\u002Fissue_flow_git.py`.\n4. Persist and reconcile progress through `${SPEC_ROOT}\u002F\u003Cepic>\u002F.issue-flow-state.json` using portable git metadata only; never store machine-specific absolute worktree paths in tracked state.\n5. Do not advance phases when a required quality gate or human gate is unresolved.\n\n## Output\n- A phase-by-phase issue delivery run with artifacts, evidence, gate results, and GitHub status updates.\n","# Issue Flow\n\n## Purpose\nDrive one GitHub issue through the full Harnessy delivery lifecycle using the repository's existing skills, mandatory evaluation gates, explicit human review checkpoints, and strategy-aware intake when a standard `docs\u002Fstrategy\u002F` folder exists. GitHub Project metadata is optional enrichment, not a required intake dependency.\n\n## Inputs\n- Optional arguments: `continue`, `status`, or `issue \u003Cnumber-or-url>`\n\n- Template paths are resolved from `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002F`.\n\n## Steps\n1. Follow the command specification in `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002Fcommands\u002Fissue-flow.md` exactly.\n2. Use existing child skills rather than replacing them.\n3. Run each new issue cycle in the canonical project-container worktree root `projects\u002F\u003Cproject-name>\u002Fworktrees\u002F\u003Cissue_id>_\u003Cfriendly_name>` when viewed from the container, or `..\u002Fworktrees\u002F\u003Cissue_id>_\u003Cfriendly_name>` when invoked from `projects\u002F\u003Cproject-name>\u002Fdev\u002F`, derived at runtime via `${AGENTS_SKILLS_ROOT}\u002Fissue-flow\u002Fscripts\u002Fissue_flow_git.py`.\n4. Persist and reconcile progress through `${SPEC_ROOT}\u002F\u003Cepic>\u002F.issue-flow-state.json` using portable git metadata only; never store machine-specific absolute worktree paths in tracked state.\n5. Do not advance phases when a required quality gate or human gate is unresolved.\n\n## Output\n- A phase-by-phase issue delivery run with artifacts, evidence, gate results, and GitHub status updates.\n",{"name":5,"description":7,"allowed-tools":44,"argument-hint":45,"disable-model-invocation":46},"Read, Write, ApplyPatch, Grep, Glob, Bash, Question","[continue|status|issue \u003Cnumber-or-url>]",true,"main","bae3fdddd99eabe649d0d53cea5d2a0b501aa8b3","tools\u002Fflow-install\u002Fskills\u002Fissue-flow",7,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy","https:\u002F\u002Fgithub.com\u002FFlow-Research","2026-08-15 01:06:37",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":46},[56,59,62],{"tool":57,"command":58},"npx","npx skills add Flow-Research\u002Fharnessy --skill issue-flow",{"tool":60,"command":61},"bunx","bunx skills add Flow-Research\u002Fharnessy --skill issue-flow",{"tool":63,"command":64},"pnpm","pnpm dlx skills add Flow-Research\u002Fharnessy --skill issue-flow","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002FSKILL.md",[67,73,77,83,87],{"path":68,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":71,"sourceHtmlUrl":72},"commands\u002Fissue-flow.md","REFERENCE","参考文档",41831,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002Fcommands\u002Fissue-flow.md",{"path":74,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":75,"sourceHtmlUrl":76},"manifest.yaml",1970,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002Fmanifest.yaml",{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"scripts\u002Fissue_flow_git.py","SCRIPT","脚本",9580,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002Fscripts\u002Fissue_flow_git.py",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"scripts\u002Fissue_flow_state.py",9816,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002Fscripts\u002Fissue_flow_state.py",{"path":88,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":89,"sourceHtmlUrl":90},"scripts\u002Fissue_flow_validate_transition.py",9028,"https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fissue-flow\u002Fscripts\u002Fissue_flow_validate_transition.py",[92,121,149,174,195,210],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":103,"publishedAt":39},"01M6GVTWDZDG82G8GGGYXXCT5B","wiki-research","Autonomous research orchestrator for Jarvis Wiki domains. Spawns a Claude agent with web tools to find new sources, drops them into raw\u002F, runs the compile pipeline, and emits autoresearch traces for the autoflow ratchet.","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fwiki-research\u002FSKILL.md",[98],{"categoryNo":99,"categoryName":100,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[104,105,106,107,108,109,110,32,111,112,113,114,115,116,117,118,119,120,26,23],"research","wiki","wiki research","web","compile","autoresearch","pipeline","find","read","write","web tools","autonomous","orchestrator","domain","domains","sources","Autonomous 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rules.","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Ftest-quality-validator\u002FSKILL.md",[155],{"categoryNo":156,"categoryName":157,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000008","测试与质量",[37,159,160,161,35,162,163,32,164,112,113,165,166,167,168,169,170,171,172,173],"quality","validator","test quality validator","browser","api","regression","context","coverage","generated","only","delivery","green","false","canonical","hand",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":180,"publishedAt":39},"01M6GVTE4BYCYCFKK2PS83ATX4","tech-spec","Generate production-ready technical specifications from product specs.","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Ftech-spec\u002FSKILL.md",[],[181,182,183,30,184,185,186,187,188,112,113,189,190,191,23,192,193,194],"spec","tech spec","tech","generate","product","Production","grep","technical","ready","specifications","folder","websearch","path","production-ready",{"skillNo":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":201,"publishedAt":39},"01M6GVT9FPGF2ME475HPQWKPSC","tech-spec-review","Seven-lens engineering review for technical_spec.md files, including an explicit simplicity and architectural fitness gate.","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Ftech-spec-review\u002FSKILL.md",[],[30,181,202,182,183,203,204,187,188,112,113,205,206,207,208,209,23,192,193],"spec review","tech spec review","engineering","simplicity","files","gate","lens","quick",{"skillNo":211,"name":212,"nameZh":6,"description":213,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":214,"categories":215,"keywords":221,"publishedAt":39},"01M6GVT3XTZ4W3P2XQRDNBPZ4M","spec-to-regression","Generate browser and API regression scenarios from approved product and technical specs using the Harnessy delivery profile and regression artifact contract.","https:\u002F\u002Fgithub.com\u002FFlow-Research\u002Fharnessy\u002Fblob\u002Fmain\u002Ftools\u002Fflow-install\u002Fskills\u002Fspec-to-regression\u002FSKILL.md",[216],{"categoryNo":217,"categoryName":218,"taxonomyType":219,"taxonomyTypeDesc":220},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[181,164,222,184,162,185,20,163,32,223,187,188,112,113,169,224,225,171,146,226],"spec to regression","json","artifact","contract","EPIC"]