[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71BV46CWH99253223RBJJHB":3,"skill-same:01M71BV46CWH99253223RBJJHB":74},{"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":53,"commitSha":54,"skillDirectory":55,"forksCount":56,"repositoryHtmlUrl":57,"repositoryHomepageUrl":6,"ownerHtmlUrl":58,"ownerBlogUrl":6,"ownerDescription":59,"updatedAt":60,"install":61,"resources":73},"01M71BV46CWH99253223RBJJHB","organ-openprocess-pool",null,"Mathematical memory for started-but-unclosed work that ranks open tasks, research, ideas, todos, skills, bugs, experiments, and handoffs by open mass (status, staleness, dependency centrality, risk, and value). Use when you need a math-grounded answer to 'what did we start but not finish?', or when invoking openprocess-pool to surface and prioritize unclosed work across all lanes.","nexuslinkproductions\u002Fyuri-os","nexuslinkproductions","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F273246263?v=4","01M718YX9NZRCW50B59B8ZVDKN","Marcel Spatz","01M718YXAQ7530F4B1VKN6SFQV",2,"MIT","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Forgan-openprocess-pool\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"pool","organ openprocess pool","across","tasks","you","when","use","open","true","system","answer","for","memory","ideas","bugs","value","risk","usage","do","harness","2026-11-10 10:12:30",false,"---\nname: organ-openprocess-pool\ndescription: \"Mathematical memory for started-but-unclosed work that ranks open tasks, research, ideas, todos, skills, bugs, experiments, and handoffs by open mass (status, staleness, dependency centrality, risk, and value). Use when you need a math-grounded answer to 'what did we start but not finish?', or when invoking openprocess-pool to surface and prioritize unclosed work across all lanes.\"\ntriggers:\n  - \"organ-openprocess-pool\"\n  - \"how do I use openprocess-pool\"\n  - \"openprocess-pool usage\"\n  - \"openprocess-pool guide\"\n  - \"OpenProcess Sum Pool (mathematical memory for started-but-unclosed work)\"\ngenerated: true\nsource_node: \"openprocess-pool\"\nsource_file: \"_SYSTEM\u002FScripts\u002Fopenprocess-pool.mjs\"\nscope: harness\ninvocation: ability\n---\n\n\u003C!-- GENERATED from the canonical graph node \"openprocess-pool\" (mechanism.guide) by _SYSTEM\u002FScripts\u002Fyuri-guide-project.mjs.\n     DO NOT hand-edit — edit _SYSTEM\u002Forgan-guides.json, then run: node _SYSTEM\u002FScripts\u002Fyuri-guide-seed.mjs && node _SYSTEM\u002FScripts\u002Fyuri-guide-project.mjs -->\n\n# Organ Guide — OpenProcess Sum Pool (mathematical memory for started-but-unclosed work)\n\n**Module:** `_SYSTEM\u002FScripts\u002Fopenprocess-pool.mjs` · **Layer:** Memory & Subconscious · **Invocation:** both · **CLI:** none (import-only surface)\n\n**Purpose.** The OpenProcess Sum Pool — mathematical memory for started-but-unclosed work. Users + lanes start tasks\u002Fresearch\u002Fideas\u002Ftodos\u002Fskills\u002Fbugs\u002Fexperiments\u002Fhandoffs over days; many stay open and fall out of working memory. This ranks them by OPEN MASS (status + staleness hazard-decay + dependency centrality + risk + value) so 'what did we start but not finish?' gets a math-grounded answer, not a memory vibe. UI-agnostic and YURI-native (same across all lanes).\n\n## Exports\n- `OPEN_PROCESS_TYPES (frozen const)`\n  - in: —\n  - out: ['task','research','idea','todo','skill','bug','experiment','handoff']\n- `OPEN_PROCESS_STATES (frozen const)`\n  - in: —\n  - out: ['open','active','blocked','stale','closed']\n- `DEFAULT_WEIGHTS (frozen const)`\n  - in: —\n  - out: the default OpenMass term weights (status\u002Fage\u002Fdep\u002Frisk\u002Fvalue)\n- `staleness(proc)`\n  - in: an OpenProcess object\n  - out: a hazard-decay staleness score (stale-but-open rises back into attention)\n- `openMass(proc, opts = {})`\n  - in: an OpenProcess + optional { weights }\n  - out: the scalar OpenMass for that process\n- `rankPool(processes, opts = {})`\n  - in: array of processes + opts\n  - out: processes ranked by descending OpenMass\n- `poolTotal(processes, opts = {})`\n  - in: array of processes + opts\n  - out: the summed OpenMass over the pool\n- `categoryPools(processes, opts = {})`\n  - in: array of processes + opts\n  - out: OpenMass grouped\u002Fsummed by category\n- `whatIsUnfinished(processes, opts = {})`\n  - in: array of processes + { top, weights }\n  - out: the top-N highest-mass open processes with their next candidate action\n- `async navigateCentrality()`\n  - in: none\n  - out: dependency centrality per process via yuri-navigate.aggregateProcessCentrality\n\n## Security boundary\nPure \u002F read-only ranking math — computes OpenMass over process objects supplied by the caller; persists nothing itself. navigateCentrality reads the canonical graph via yuri-navigate (also read-only). No protected-path access. Deterministic (sorted, hazard-decay, no RNG).\n\n## When to use\nAnswering 'what did we start but not finish?', ranking open work by mass, summing pool\u002Fcategory load, or weighting a process by its dependency centrality. The math layer under the nervous system's afferent digest (yuri-nerve calls whatIsUnfinished).\n\n## Gotchas\n- Staleness uses hazard-decay: a stale-but-open item RISES back in rank over time — it is not penalized into invisibility.\n- navigateCentrality is async and depends on yuri-navigate over the canonical graph; a stale graph yields stale centrality.\n- The pool is data-in\u002Fscore-out — it does not own storage; the caller supplies the process objects (e.g. from the nerve store).\n\n## Session Notes\n\n### 2026-06-13\n- session: 40m | peak ctx: 0% | compacts: 0\n- tools: Bash×824, Read×163, Edit×17, StructuredOutput×16, Write×8, TodoWrite×4, ToolSearch×2, ScheduleWakeup×2, Workflow×1, mcp×1, AskUserQuestion×1\n- corrections: none\n- errors: none\n","\u003C!-- GENERATED from the canonical graph node \"openprocess-pool\" (mechanism.guide) by _SYSTEM\u002FScripts\u002Fyuri-guide-project.mjs.\n     DO NOT hand-edit — edit _SYSTEM\u002Forgan-guides.json, then run: node _SYSTEM\u002FScripts\u002Fyuri-guide-seed.mjs && node _SYSTEM\u002FScripts\u002Fyuri-guide-project.mjs -->\n\n# Organ Guide — OpenProcess Sum Pool (mathematical memory for started-but-unclosed work)\n\n**Module:** `_SYSTEM\u002FScripts\u002Fopenprocess-pool.mjs` · **Layer:** Memory & Subconscious · **Invocation:** both · **CLI:** none (import-only surface)\n\n**Purpose.** The OpenProcess Sum Pool — mathematical memory for started-but-unclosed work. Users + lanes start tasks\u002Fresearch\u002Fideas\u002Ftodos\u002Fskills\u002Fbugs\u002Fexperiments\u002Fhandoffs over days; many stay open and fall out of working memory. This ranks them by OPEN MASS (status + staleness hazard-decay + dependency centrality + risk + value) so 'what did we start but not finish?' gets a math-grounded answer, not a memory vibe. UI-agnostic and YURI-native (same across all lanes).\n\n## Exports\n- `OPEN_PROCESS_TYPES (frozen const)`\n  - in: —\n  - out: ['task','research','idea','todo','skill','bug','experiment','handoff']\n- `OPEN_PROCESS_STATES (frozen const)`\n  - in: —\n  - out: ['open','active','blocked','stale','closed']\n- `DEFAULT_WEIGHTS (frozen const)`\n  - in: —\n  - out: the default OpenMass term weights (status\u002Fage\u002Fdep\u002Frisk\u002Fvalue)\n- `staleness(proc)`\n  - in: an OpenProcess object\n  - out: a hazard-decay staleness score (stale-but-open rises back into attention)\n- `openMass(proc, opts = {})`\n  - in: an OpenProcess + optional { weights }\n  - out: the scalar OpenMass for that process\n- `rankPool(processes, opts = {})`\n  - in: array of processes + opts\n  - out: processes ranked by descending OpenMass\n- `poolTotal(processes, opts = {})`\n  - in: array of processes + opts\n  - out: the summed OpenMass over the pool\n- `categoryPools(processes, opts = {})`\n  - in: array of processes + opts\n  - out: OpenMass grouped\u002Fsummed by category\n- `whatIsUnfinished(processes, opts = {})`\n  - in: array of processes + { top, weights }\n  - out: the top-N highest-mass open processes with their next candidate action\n- `async navigateCentrality()`\n  - in: none\n  - out: dependency centrality per process via yuri-navigate.aggregateProcessCentrality\n\n## Security boundary\nPure \u002F read-only ranking math — computes OpenMass over process objects supplied by the caller; persists nothing itself. navigateCentrality reads the canonical graph via yuri-navigate (also read-only). No protected-path access. Deterministic (sorted, hazard-decay, no RNG).\n\n## When to use\nAnswering 'what did we start but not finish?', ranking open work by mass, summing pool\u002Fcategory load, or weighting a process by its dependency centrality. The math layer under the nervous system's afferent digest (yuri-nerve calls whatIsUnfinished).\n\n## Gotchas\n- Staleness uses hazard-decay: a stale-but-open item RISES back in rank over time — it is not penalized into invisibility.\n- navigateCentrality is async and depends on yuri-navigate over the canonical graph; a stale graph yields stale centrality.\n- The pool is data-in\u002Fscore-out — it does not own storage; the caller supplies the process objects (e.g. from the nerve store).\n\n## Session Notes\n\n### 2026-06-13\n- session: 40m | peak ctx: 0% | compacts: 0\n- tools: Bash×824, Read×163, Edit×17, StructuredOutput×16, Write×8, TodoWrite×4, ToolSearch×2, ScheduleWakeup×2, Workflow×1, mcp×1, AskUserQuestion×1\n- corrections: none\n- errors: none\n",{"name":5,"scope":38,"triggers":44,"generated":49,"invocation":50,"description":7,"source_file":51,"source_node":52},[5,45,46,47,48],"how do I use openprocess-pool","openprocess-pool usage","openprocess-pool guide","OpenProcess Sum Pool (mathematical memory for started-but-unclosed work)",true,"ability","_SYSTEM\u002FScripts\u002Fopenprocess-pool.mjs","openprocess-pool","main","4c6d8d65f3d6096e2fc25b0845e481dda73c2794",".claude\u002Fskills\u002Forgan-openprocess-pool",0,"https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions","Building deterministic AI governance and continuity systems. Workflow architect + visual storyteller","2026-11-11 16:42:59",{"source":8,"skillName":5,"commands":62,"prompt":72,"zipAvailable":49},[63,66,69],{"tool":64,"command":65},"npx","npx skills add nexuslinkproductions\u002Fyuri-os --skill organ-openprocess-pool",{"tool":67,"command":68},"bunx","bunx skills add nexuslinkproductions\u002Fyuri-os --skill organ-openprocess-pool",{"tool":70,"command":71},"pnpm","pnpm dlx skills add nexuslinkproductions\u002Fyuri-os --skill organ-openprocess-pool","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Forgan-openprocess-pool\u002FSKILL.md",[],[75,93,116,146,175,194],{"skillNo":76,"name":77,"nameZh":6,"description":78,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":79,"categories":80,"keywords":81,"publishedAt":39},"01M71CG1AME5WC0A79AE65WT0X","zoom-out","Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fzoom-out\u002FSKILL.md",[],[82,83,84,38,85,86,87,27,88,25,89,24,23,90,91,92],"zoom out","zoom","with","how","section","re","understand","perspective","code","it","context",{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":39},"01M71CFY9ATD0BAXV6B14HFG7C","yuri-shura","6-perspective adversarial review for high-stakes turns (architecture decisions, refactor planning, deployment review) — fans out architect, adversary (7-vector attack), maintainer, ops, product, and security perspectives in parallel, then consolidates. Use when user says 'review this decision', '\u002Fshura', 'adversarial review', 'what could go wrong', 'architecture review', or 'deployment review'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-shura\u002FSKILL.md",[],[100,101,38,102,103,30,104,105,106,107,108,25,109,24,110,111,112,113,114,115],"yuri shura","parallel","architecture review","planning","deployment","vector","strategic review","decision","strategic","ops","workflow","decisions","architecture","review","perspectives","adversarial",{"skillNo":117,"name":118,"nameZh":6,"description":119,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":120,"categories":121,"keywords":127,"publishedAt":39},"01M71CFTTYW1HA2MNX38EV1GJ5","yuri-sales-intelligence","Unified sales and outreach skill generating cold outreach openers, social selling sequences, objection rebuttals, and ad creative for any paid platform — multi-persona aware, adapting tone and offer frame to buyer type. Use when user says 'write a cold email', 'outreach sequence', 'objection handling', 'ad copy', or 'sales pitch'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-sales-intelligence\u002FSKILL.md",[122],{"categoryNo":123,"categoryName":124,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000005","邮件与沟通","SCENARIO","使用场景",[128,129,130,131,132,133,134,135,136,24,137,138,139,140,141,142,143,30,144,145],"intelligence","sales intelligence","yuri sales intelligence","sales","cold","paid","social","persona","pitch","cold email","ad creative","write","sequences","sequence","platform","email","cold outreach","frame",{"skillNo":147,"name":148,"nameZh":6,"description":149,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":160,"publishedAt":39},"01M71CFQMBFTFADJNGP0Z2WCYK","yuri-code-intelligence","Unified code quality intelligence layer that diagnoses code smells (Long Method, Feature Envy, design pattern issues), prescribes targeted Fowler refactoring techniques, and reviews code for security, performance, and clarity. Use when user says 'review this code', 'refactor this', 'what's wrong with this method', 'code smells', or 'clean this up'.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-code-intelligence\u002FSKILL.md",[152,155],{"categoryNo":153,"categoryName":154,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":156,"categoryName":157,"taxonomyType":158,"taxonomyTypeDesc":159},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[161,90,162,128,38,163,164,165,30,166,167,168,169,170,171,172,173,174,25,24],"yuri code intelligence","code intelligence","reviews","code quality","feature","performance","code review","long","up","issues","clean","techniques","improve","design",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":181,"publishedAt":39},"01M71CFP32RT6GD3GKNHCJP8VP","yuri-adw","Invoke when user asks to run the ADW loop \u002F agentic engineering loop \u002F software factory workflow.","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fyuri-adw\u002FSKILL.md",[],[182,183,184,185,186,187,188,189,190,24,191,110,192,193],"yuri adw","run","engineering loop","software factory","software","agentic engineering","factory","loop","invoke","engineering","agentic","user",{"skillNo":195,"name":196,"nameZh":6,"description":197,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":198,"categories":199,"keywords":212,"publishedAt":39},"01M71CFK4VPEKY6A73237P7RSN","writing-skills","Use when creating new skills, editing existing skills, or verifying skills work before deployment","https:\u002F\u002Fgithub.com\u002Fnexuslinkproductions\u002Fyuri-os\u002Fblob\u002Fmain\u002Fskills\u002Fwriting-skills\u002FSKILL.md",[200,203,206,209],{"categoryNo":201,"categoryName":202,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":204,"categoryName":205,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":207,"categoryName":208,"taxonomyType":125,"taxonomyTypeDesc":126},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":210,"categoryName":211,"taxonomyType":158,"taxonomyTypeDesc":159},"01JBSEEDCAT000000000000036","内容创作者",[213,214,215,24,110,216,38,217,104,25,218],"writing","writing skills","new","work","editing","Existing"]