[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G2ND6MCFTAYGMDV9PRWPMZ":3,"skill-same:01M6G2ND6MCFTAYGMDV9PRWPMZ":81},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":54,"install":55,"resources":68},"01M6G2ND6MCFTAYGMDV9PRWPMZ","context-budgeting",null,"Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences \"memory loss\" after compaction, or when aiming to reduce token costs and latency for long-running tasks.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fsarielwang93\u002Fcontext-budgeting\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"context budgeting","context","budgeting","optimize","near","limit","usage","information","via","long","latency","token","memory","session context","manage","use","session","lifecycle","compression","tasks","2026-11-10 10:12:30",false,"---\nname: context-budgeting\ndescription: Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences \"memory loss\" after compaction, or when aiming to reduce token costs and latency for long-running tasks.\n---\n\n# Context Budgeting Skill\n\nThis skill provides a systematic framework for managing the finite context window (RAM) of an OpenClaw agent.\n\n## Core Concepts\n\n### 1. Information Partitioning\n- **Objective\u002FGoal (10%)**: Core task instructions and active constraints.\n- **Short-term History (40%)**: Recent 5-10 turns of raw dialogue.\n- **Decision Logs (20%)**: Summarized outcomes of past steps (\"Tried X, failed because Y\").\n- **Background\u002FKnowledge (20%)**: High-relevance snippets from MEMORY.md.\n\n### 2. Pre-compression Checkpointing (Mandatory)\nBefore any compaction (manual or automatic), the agent MUST:\n1.  **Generate Checkpoint**: Update `memory\u002Fhot\u002FHOT_MEMORY.md` with:\n    - **Status**: Current task progress.\n    - **Key Decision**: Significant choices made.\n    - **Next Step**: Immediate action required.\n2.  **Run Automation**: Execute `scripts\u002Fgc_and_checkpoint.sh` to trigger the physical cleanup.\n\n## Automation Tool: `gc_and_checkpoint.sh`\nLocated at: `skills\u002Fcontext-budgeting\u002Fscripts\u002Fgc_and_checkpoint.sh`\n\n**Usage**: \n- Run this script after updating `HOT_MEMORY.md` to finalize the compaction process without restarting the session.\n\n## Integration with Heartbeat\nHeartbeat (every 30m) acts as the Garbage Collector (GC):\n1.  Check `\u002Fstatus`. If Context > 80%, trigger the **Checkpointing** procedure.\n2.  Clear raw data (e.g., multi-megabyte JSON outputs) once the summary is extracted.\n","# Context Budgeting Skill\n\nThis skill provides a systematic framework for managing the finite context window (RAM) of an OpenClaw agent.\n\n## Core Concepts\n\n### 1. Information Partitioning\n- **Objective\u002FGoal (10%)**: Core task instructions and active constraints.\n- **Short-term History (40%)**: Recent 5-10 turns of raw dialogue.\n- **Decision Logs (20%)**: Summarized outcomes of past steps (\"Tried X, failed because Y\").\n- **Background\u002FKnowledge (20%)**: High-relevance snippets from MEMORY.md.\n\n### 2. Pre-compression Checkpointing (Mandatory)\nBefore any compaction (manual or automatic), the agent MUST:\n1.  **Generate Checkpoint**: Update `memory\u002Fhot\u002FHOT_MEMORY.md` with:\n    - **Status**: Current task progress.\n    - **Key Decision**: Significant choices made.\n    - **Next Step**: Immediate action required.\n2.  **Run Automation**: Execute `scripts\u002Fgc_and_checkpoint.sh` to trigger the physical cleanup.\n\n## Automation Tool: `gc_and_checkpoint.sh`\nLocated at: `skills\u002Fcontext-budgeting\u002Fscripts\u002Fgc_and_checkpoint.sh`\n\n**Usage**: \n- Run this script after updating `HOT_MEMORY.md` to finalize the compaction process without restarting the session.\n\n## Integration with Heartbeat\nHeartbeat (every 30m) acts as the Garbage Collector (GC):\n1.  Check `\u002Fstatus`. If Context > 80%, trigger the **Checkpointing** procedure.\n2.  Clear raw data (e.g., multi-megabyte JSON outputs) once the summary is extracted.\n",{"name":5,"description":7},"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Fsarielwang93\u002Fcontext-budgeting",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add kbarbel640-del\u002Fskills --skill context-budgeting",{"tool":61,"command":62},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill context-budgeting",{"tool":64,"command":65},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill context-budgeting","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fsarielwang93\u002Fcontext-budgeting\u002FSKILL.md",true,[69,75],{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"_meta.json","REFERENCE","参考文档",292,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fsarielwang93\u002Fcontext-budgeting\u002F_meta.json",{"path":76,"resourceType":77,"resourceTypeDesc":78,"sizeBytes":79,"sourceHtmlUrl":80},"scripts\u002Fgc_and_checkpoint.sh","SCRIPT","脚本",917,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fsarielwang93\u002Fcontext-budgeting\u002Fscripts\u002Fgc_and_checkpoint.sh",[82,113,137,157,163,183],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":86,"categories":87,"keywords":93,"publishedAt":43},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[88],{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112],"crowd prompting","prompting","api","with","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":120,"publishedAt":43},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[119],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[121,96,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,101,38],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":146,"publishedAt":43},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[143],{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",[147,148,149,150,151,152,153,97,154,135,38,155,96,156,31],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http",{"skillNo":158,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":162,"publishedAt":43},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[161],{"categoryNo":144,"categoryName":145,"taxonomyType":20,"taxonomyTypeDesc":21},[150,149,148,147,31,152,153,97,151,135,38,154,155,96,156],{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":169,"publishedAt":43},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[170,171,172,173,174,175,176,177,178,179,180,181,182],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":193,"publishedAt":43},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[189,190],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":191,"categoryName":192,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000037","律师与法务",[194,195,196,197,97,198,199,48,200,155,201,202,203,204,205,110,206,207,208],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]