[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-muratcankoylan-latent-briefing-de":3,"guides-for-muratcankoylan-latent-briefing":631,"similar-k177vey9xnw010b18xbr84mea986nz00-de":632},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":243,"isFallback":240,"parentExtension":248,"providers":308,"relations":312,"repo":313,"tags":629,"workflow":630},1778694269038.67,"k177vey9xnw010b18xbr84mea986nz00",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"This skill should be used when the user asks to \"share memory between agents\", \"KV cache compaction for multi-agent\", \"orchestrator worker context\", \"latent briefing\", \"reduce worker tokens\", \"cross-agent memory without summarization\", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.",{"claudeCode":12},"muratcankoylan/Agent-Skills-for-Context-Engineering","latent-briefing","https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":224,"workflow":241},1778694530621.5566,"kn7fe9pka1e1sfmx6xe3bk083986mvpz","en",{"checks":20,"evaluatedAt":194,"extensionSummary":195,"features":196,"nonGoals":201,"promptVersionExtension":205,"promptVersionScoring":206,"purpose":207,"rationale":208,"score":209,"summary":210,"tags":211,"targetMarket":217,"tier":218,"useCases":219},[21,26,29,33,37,40,45,49,52,55,59,64,67,71,74,77,80,83,86,89,93,97,101,105,109,112,115,118,122,125,128,131,134,137,140,144,148,152,155,159,162,165,168,171,175,178,181,184,187,191],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly names the problem of sharing memory between agents and discusses KV cache compaction for multi-agent systems.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill offers a novel approach to context sharing at the representation level (KV cache) rather than text, going beyond simple summarization or RAG.",{"category":22,"check":30,"severity":31,"summary":32},"Production readiness","info","The skill outlines a detailed technical approach and use cases, but its readiness for production hinges on the user's ability to control the worker inference runtime for KV state manipulation.",{"category":34,"check":35,"severity":24,"summary":36},"Scope","Single responsibility principle","The skill focuses specifically on latent briefing and KV cache compaction for context engineering in multi-agent systems.",{"category":34,"check":38,"severity":24,"summary":39},"Description quality","The displayed description accurately reflects the skill's purpose of sharing memory between agents via KV cache compaction and provides relevant trigger phrases.",{"category":41,"check":42,"severity":43,"summary":44},"Invocation","Scoped tools","not_applicable","This skill does not expose individual tools; it is a self-contained skill that operates based on its SKILL.md instructions.",{"category":46,"check":47,"severity":43,"summary":48},"Documentation","Configuration & parameter reference","The skill does not appear to have configurable parameters or options beyond its core functionality.",{"category":34,"check":50,"severity":43,"summary":51},"Tool naming","This skill does not expose individual tools with specific names.",{"category":34,"check":53,"severity":43,"summary":54},"Minimal I/O surface","As a skill and not a tool, it does not have explicit parameter schemas or response shapes in the same way tools do.",{"category":56,"check":57,"severity":24,"summary":58},"License","License usability","The extension uses the MIT license, which is a permissive open-source license, clearly stated in the LICENSE file.",{"category":60,"check":61,"severity":62,"summary":63},"Maintenance","Commit recency","warning","The last commit was on 2026-04-14, over 3 months ago, suggesting potential unmaintained status.",{"category":60,"check":65,"severity":43,"summary":66},"Dependency Management","The skill does not appear to rely on third-party dependencies that require explicit management.",{"category":68,"check":69,"severity":43,"summary":70},"Security","Secret Management","The skill does not handle secrets.",{"category":68,"check":72,"severity":24,"summary":73},"Injection","The skill operates on provided context and does not fetch external data or run arbitrary code, mitigating injection risks.",{"category":68,"check":75,"severity":24,"summary":76},"Transitive Supply-Chain Grenades","The skill relies only on bundled documentation and does not fetch external content at runtime.",{"category":68,"check":78,"severity":24,"summary":79},"Sandbox Isolation","The skill operates on provided context and does not modify files outside its scope.",{"category":68,"check":81,"severity":24,"summary":82},"Sandbox escape primitives","The skill's instructions do not contain primitives for escaping sandbox environments.",{"category":68,"check":84,"severity":24,"summary":85},"Data Exfiltration","The skill does not perform any outbound calls or reference confidential data.",{"category":68,"check":87,"severity":24,"summary":88},"Hidden Text Tricks","The bundled content is free of hidden-steering tricks and uses clean printable ASCII.",{"category":90,"check":91,"severity":24,"summary":92},"Hooks","Opaque code execution","The skill's instructions are plain text and do not involve obfuscation or opaque code execution.",{"category":94,"check":95,"severity":24,"summary":96},"Portability","Structural Assumption","The skill focuses on conceptual explanation and does not make structural assumptions about the user's project layout.",{"category":98,"check":99,"severity":62,"summary":100},"Trust","Issues Attention","6 issues opened and 2 closed in the last 90 days, indicating a low closure rate (33%) and potentially slow maintainer response.",{"category":102,"check":103,"severity":24,"summary":104},"Versioning","Release Management","A version (1.1.0) is clearly indicated in the SKILL.md metadata.",{"category":106,"check":107,"severity":43,"summary":108},"Code Execution","Validation","The skill itself does not execute code or process structured output; it provides instructions.",{"category":68,"check":110,"severity":43,"summary":111},"Unguarded Destructive Operations","The skill is purely informational and does not perform any destructive operations.",{"category":106,"check":113,"severity":43,"summary":114},"Error Handling","As a skill providing instructions, it does not have error paths that need catching or reporting.",{"category":106,"check":116,"severity":43,"summary":117},"Logging","The skill does not perform actions that require logging.",{"category":119,"check":120,"severity":43,"summary":121},"Compliance","GDPR","The skill does not operate on personal data.",{"category":119,"check":123,"severity":24,"summary":124},"Target market","The skill's concepts are general and not tied to any specific geography or legal jurisdiction; it is global.",{"category":94,"check":126,"severity":24,"summary":127},"Runtime stability","The skill provides conceptual guidance and does not rely on specific runtime environments.",{"category":46,"check":129,"severity":24,"summary":130},"README","The README provides a comprehensive overview of the repository's purpose, skills, and usage.",{"category":34,"check":132,"severity":43,"summary":133},"Tool surface size","This is a skill, not a tool-based extension.",{"category":41,"check":135,"severity":43,"summary":136},"Overlapping near-synonym tools","This skill does not expose individual tools.",{"category":46,"check":138,"severity":24,"summary":139},"Phantom features","All advertised features and concepts in the SKILL.md and README are supported by explanations and references.",{"category":141,"check":142,"severity":24,"summary":143},"Install","Installation instruction","The README provides clear instructions for installing the marketplace and individual skills, including copy-paste examples.",{"category":145,"check":146,"severity":43,"summary":147},"Errors","Actionable error messages","The skill provides instructions, not executable code with error paths.",{"category":149,"check":150,"severity":43,"summary":151},"Execution","Pinned dependencies","The skill does not include scripts with dependencies.",{"category":34,"check":153,"severity":43,"summary":154},"Dry-run preview","The skill is informational and does not perform state-changing operations.",{"category":156,"check":157,"severity":43,"summary":158},"Protocol","Idempotent retry & timeouts","The skill does not involve remote calls or state-changing operations.",{"category":119,"check":160,"severity":43,"summary":161},"Telemetry opt-in","The skill does not emit telemetry.",{"category":41,"check":163,"severity":24,"summary":164},"Precise Purpose","The SKILL.md and displayed description clearly articulate the skill's purpose of sharing memory via KV cache compaction and specify when to use it.",{"category":41,"check":166,"severity":24,"summary":167},"Concise Frontmatter","The frontmatter in SKILL.md is concise and effectively summarizes the core capability with relevant trigger phrases.",{"category":46,"check":169,"severity":24,"summary":170},"Concise Body","The SKILL.md is well-structured, keeping the main body concise and delegating deeper material to referenced files like 'attention-matching-formulation.md'.",{"category":172,"check":173,"severity":24,"summary":174},"Context","Progressive Disclosure","The SKILL.md outlines the flow and links to a referenced document for deeper explanation of Attention Matching.",{"category":172,"check":176,"severity":43,"summary":177},"Forked exploration","This skill is informational and does not involve deep exploration requiring a forked context.",{"category":22,"check":179,"severity":24,"summary":180},"Usage examples","The SKILL.md includes a relevant example illustrating the orchestrator-worker trajectory scenario.",{"category":22,"check":182,"severity":24,"summary":183},"Edge cases","The SKILL.md includes a 'Gotchas' section detailing several limitations and workload-dependent tuning hypotheses.",{"category":106,"check":185,"severity":43,"summary":186},"Tool Fallback","The skill does not rely on external tools that would require fallback mechanisms.",{"category":188,"check":189,"severity":43,"summary":190},"Safety","Halt on unexpected state","This skill provides instructions and does not have executable code that would encounter unexpected states.",{"category":94,"check":192,"severity":24,"summary":193},"Cross-skill coupling","The SKILL.md explicitly cross-links to related skills in the collection, clarifying their scopes and relationships.",1778694530517,"This skill explains Latent Briefing, a technique for sharing memory between agents at the representation level (KV cache) rather than text, using Attention Matching (AM) for compaction. It targets scenarios where an orchestrator needs to efficiently pass its reasoning state to workers without incurring high token costs or information loss from summarization.",[197,198,199,200],"Explains representation-level memory sharing via KV cache compaction.","Details the adaptation of Attention Matching for multi-agent inference.","Discusses three inference-time modifications: task-guided queries, shared masks, and MAD thresholding.","Outlines infrastructure preconditions and decision frameworks for choosing memory sharing mechanisms.",[202,203,204],"Replacing text-based summarization or RAG where those methods are sufficient or preferable.","Providing a deployable tool; this skill is for conceptual understanding and implementation guidance.","Working with API-only stacks where KV state is inaccessible.","3.0.0","4.4.0","To provide a detailed explanation and implementation guidance for using Latent Briefing to optimize memory sharing and reduce token costs in hierarchical multi-agent systems.","The extension has a warning for commit recency and issues attention, indicating potential maintenance gaps.",75,"A well-documented skill addressing advanced context engineering for multi-agent systems.",[212,213,214,215,216],"multi-agent","kv-cache","compaction","context-engineering","orchestration","global","community",[220,221,222,223],"Designing orchestrator-worker systems needing to share prior state efficiently.","Evaluating KV cache compaction as an alternative to text summarization for cross-agent state transfer.","Debugging token explosion in recursive or hierarchical agent graphs.","Implementing or studying task-conditioned selective retention in LLM inference.",{"codeQuality":225,"collectedAt":227,"documentation":228,"maintenance":231,"security":237,"testCoverage":239},{"hasLockfile":226},false,1778694518311,{"descriptionLength":229,"readmeSize":230},362,13763,{"closedIssues90d":232,"forks":233,"hasChangelog":226,"openIssues90d":234,"pushedAt":235,"stars":236},2,1237,6,1776141908000,15630,{"hasNpmPackage":226,"license":238,"smitheryVerified":226},"MIT",{"hasCi":226,"hasTests":240},true,{"updatedAt":242},1778694530621,{"basePath":244,"githubOwner":245,"githubRepo":246,"locale":18,"slug":13,"type":247},"skills/latent-briefing","muratcankoylan","Agent-Skills-for-Context-Engineering","skill",{"_creationTime":249,"_id":250,"community":251,"display":252,"identity":256,"parentExtension":259,"providers":290,"relations":304,"tags":305,"workflow":306},1778694269038.6665,"k1754dy3wbsv2a5gr1a983zzs586njca",{"reviewCount":8},{"description":253,"installMethods":254,"name":255,"sourceUrl":14},"Comprehensive context engineering skills for building production-grade AI agent systems — covering fundamentals, degradation patterns, compression, optimization, latent briefing (KV sharing between agents), multi-agent coordination, memory systems, tool design, filesystem context, hosted agents, evaluation, advanced evaluation, project development, and cognitive architecture",{"claudeCode":246},"Agent Skills for Context Engineering",{"basePath":257,"githubOwner":245,"githubRepo":246,"locale":18,"slug":246,"type":258},"","plugin",{"_creationTime":260,"_id":261,"community":262,"display":263,"identity":266,"providers":268,"relations":284,"tags":286,"workflow":287},1778694269038.6663,"k1796gc85sm2bx753svn59gp5186mpz4",{"reviewCount":8},{"description":264,"installMethods":265,"name":255,"sourceUrl":14},"Context Engineering skills for building production-grade AI agent systems",{"claudeCode":12},{"basePath":257,"githubOwner":245,"githubRepo":246,"locale":18,"slug":246,"type":267},"marketplace",{"evaluate":269,"extract":277},{"promptVersionExtension":270,"promptVersionScoring":206,"score":209,"tags":271,"targetMarket":217,"tier":218},"3.1.0",[272,273,215,274,275,276],"ai","agent-skills","llm","development","architecture",{"commitSha":278,"license":238,"marketplace":279,"plugin":282},"HEAD",{"name":280,"pluginCount":281},"context-engineering-marketplace",1,{"mcpCount":8,"provider":283,"skillCount":8},"classify",{"repoId":285},"kd7f12maf5nxmx5xttjx7scfnx86m1tv",[273,272,276,215,275,274],{"evaluatedAt":288,"extractAt":289,"updatedAt":288},1778694283498,1778694269038,{"evaluate":291,"extract":301},{"promptVersionExtension":205,"promptVersionScoring":206,"score":292,"tags":293,"targetMarket":217,"tier":300},95,[215,294,295,296,297,298,299],"ai-agents","prompt-engineering","multi-agent-systems","llm-operations","agent-architecture","cognitive-architecture","verified",{"commitSha":278,"license":238,"plugin":302},{"mcpCount":8,"provider":283,"skillCount":303},14,{"parentExtensionId":261,"repoId":285},[298,294,299,215,297,296,295],{"evaluatedAt":307,"extractAt":289,"updatedAt":307},1778694291902,{"evaluate":309,"extract":311},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":310,"targetMarket":217,"tier":218},[212,213,214,215,216],{"commitSha":278},{"parentExtensionId":250,"repoId":285},{"_creationTime":314,"_id":285,"identity":315,"providers":316,"workflow":625},1778694264629.3296,{"githubOwner":245,"githubRepo":246,"sourceUrl":14},{"classify":317,"discover":619,"github":622},{"commitSha":278,"extensions":318},[319,332,340,367,390,411,425,443,459,471,483,495,507,519,530,542,549,561,573,587,601,609],{"basePath":257,"description":264,"displayName":280,"installMethods":320,"rationale":321,"selectedPaths":322,"source":331,"sourceLanguage":18,"type":267},{"claudeCode":12},"marketplace.json at .claude-plugin/marketplace.json",[323,326,328],{"path":324,"priority":325},".claude-plugin/marketplace.json","mandatory",{"path":327,"priority":325},"README.md",{"path":329,"priority":330},"LICENSE","high","rule",{"basePath":257,"description":253,"displayName":215,"installMethods":333,"rationale":334,"selectedPaths":335,"source":331,"sourceLanguage":18,"type":258},{"claudeCode":246},"inline plugin source from marketplace.json at / (coalesced with duplicate plugin at .plugin)",[336,337,338],{"path":327,"priority":325},{"path":329,"priority":330},{"path":339,"priority":330},"SKILL.md",{"basePath":341,"description":342,"displayName":343,"installMethods":344,"rationale":345,"selectedPaths":346,"source":331,"sourceLanguage":18,"type":247},"examples/book-sft-pipeline","This skill should be used when the user asks to \"fine-tune on books\", \"create SFT dataset\", \"train style model\", \"extract ePub text\", or mentions style transfer, LoRA training, book segmentation, or author voice replication.","book-sft-pipeline",{"claudeCode":12},"SKILL.md frontmatter at examples/book-sft-pipeline/SKILL.md",[347,348,349,352,354,356,358,361,363,365],{"path":339,"priority":325},{"path":327,"priority":330},{"path":350,"priority":351},"examples/gertrude-stein/README.md","low",{"path":353,"priority":351},"examples/gertrude-stein/dataset_sample.jsonl",{"path":355,"priority":351},"examples/gertrude-stein/sample_outputs.md",{"path":357,"priority":351},"examples/gertrude-stein/training_config.json",{"path":359,"priority":360},"references/segmentation-strategies.md","medium",{"path":362,"priority":360},"references/tinker-format.md",{"path":364,"priority":360},"references/tinker.txt",{"path":366,"priority":351},"scripts/pipeline_example.py",{"basePath":368,"description":369,"displayName":370,"installMethods":371,"rationale":372,"selectedPaths":373,"source":331,"sourceLanguage":18,"type":247},"examples/digital-brain-skill","This skill should be used when the user asks to \"write a post\", \"check my voice\", \"look up contact\", \"prepare for meeting\", \"weekly review\", \"track goals\", or mentions personal brand, content creation, network management, or voice consistency.","digital-brain",{"claudeCode":12},"SKILL.md frontmatter at examples/digital-brain-skill/SKILL.md",[374,375,376,378,380,382,384,386,388],{"path":339,"priority":325},{"path":327,"priority":330},{"path":377,"priority":360},"AGENT.md",{"path":379,"priority":360},"HOW-SKILLS-BUILT-THIS.md",{"path":381,"priority":360},"SKILLS-MAPPING.md",{"path":383,"priority":351},"examples/content-workflow.md",{"path":385,"priority":351},"examples/meeting-prep.md",{"path":387,"priority":360},"references/file-formats.md",{"path":389,"priority":351},"scripts/install.sh",{"basePath":391,"description":392,"displayName":393,"installMethods":394,"rationale":395,"selectedPaths":396,"source":331,"sourceLanguage":18,"type":247},"examples/interleaved-thinking","Debug and optimize AI agents by analyzing reasoning traces. Activates on 'debug agent', 'optimize prompt', 'analyze reasoning', 'why did the agent fail', 'improve agent performance', or when diagnosing agent failures and context degradation.","reasoning-trace-optimizer",{"claudeCode":12},"SKILL.md frontmatter at examples/interleaved-thinking/SKILL.md",[397,398,399,401,403,405,407,409],{"path":339,"priority":325},{"path":327,"priority":330},{"path":400,"priority":351},"docs/agentthinking.md",{"path":402,"priority":351},"docs/interleavedthinking.md",{"path":404,"priority":351},"docs/m2-1.md",{"path":406,"priority":351},"examples/01_basic_capture.py",{"path":408,"priority":351},"examples/02_tool_usage.py",{"path":410,"priority":351},"examples/03_full_optimization.py",{"basePath":412,"description":413,"displayName":414,"installMethods":415,"rationale":416,"selectedPaths":417,"source":331,"sourceLanguage":18,"type":247},"examples/interleaved-thinking/generated_skills/comprehensive-research-agent","Ensure thorough validation, error recovery, and transparent reasoning in research tasks with multiple tool calls","comprehensive-research-agent",{"claudeCode":12},"SKILL.md frontmatter at examples/interleaved-thinking/generated_skills/comprehensive-research-agent/SKILL.md",[418,419,421,423],{"path":339,"priority":325},{"path":420,"priority":360},"references/optimization_summary.json",{"path":422,"priority":360},"references/optimized_prompt.txt",{"path":424,"priority":360},"references/patterns_found.json",{"basePath":426,"description":427,"displayName":428,"installMethods":429,"rationale":430,"selectedPaths":431,"source":331,"sourceLanguage":18,"type":247},"skills/advanced-evaluation","This skill should be used when the user asks to \"implement LLM-as-judge\", \"compare model outputs\", \"create evaluation rubrics\", \"mitigate evaluation bias\", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.","advanced-evaluation",{"claudeCode":12},"SKILL.md frontmatter at skills/advanced-evaluation/SKILL.md",[432,433,435,437,439,441],{"path":339,"priority":325},{"path":434,"priority":360},"references/bias-mitigation.md",{"path":436,"priority":360},"references/evaluation-pipeline.md",{"path":438,"priority":360},"references/implementation-patterns.md",{"path":440,"priority":360},"references/metrics-guide.md",{"path":442,"priority":351},"scripts/evaluation_example.py",{"basePath":444,"description":445,"displayName":446,"installMethods":447,"rationale":448,"selectedPaths":449,"source":331,"sourceLanguage":18,"type":247},"skills/bdi-mental-states","This skill should be used when the user asks to \"model agent mental states\", \"implement BDI architecture\", \"create belief-desire-intention models\", \"transform RDF to beliefs\", \"build cognitive agent\", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.","bdi-mental-states",{"claudeCode":12},"SKILL.md frontmatter at skills/bdi-mental-states/SKILL.md",[450,451,453,455,457],{"path":339,"priority":325},{"path":452,"priority":360},"references/bdi-ontology-core.md",{"path":454,"priority":360},"references/framework-integration.md",{"path":456,"priority":360},"references/rdf-examples.md",{"path":458,"priority":360},"references/sparql-competency.md",{"basePath":460,"description":461,"displayName":462,"installMethods":463,"rationale":464,"selectedPaths":465,"source":331,"sourceLanguage":18,"type":247},"skills/context-compression","This skill should be used when the user asks to \"compress context\", \"summarize conversation history\", \"implement compaction\", \"reduce token usage\", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.","context-compression",{"claudeCode":12},"SKILL.md frontmatter at skills/context-compression/SKILL.md",[466,467,469],{"path":339,"priority":325},{"path":468,"priority":360},"references/evaluation-framework.md",{"path":470,"priority":351},"scripts/compression_evaluator.py",{"basePath":472,"description":473,"displayName":474,"installMethods":475,"rationale":476,"selectedPaths":477,"source":331,"sourceLanguage":18,"type":247},"skills/context-degradation","This skill should be used when the user asks to \"diagnose context problems\", \"fix lost-in-middle issues\", \"debug agent failures\", \"understand context poisoning\", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.","context-degradation",{"claudeCode":12},"SKILL.md frontmatter at skills/context-degradation/SKILL.md",[478,479,481],{"path":339,"priority":325},{"path":480,"priority":360},"references/patterns.md",{"path":482,"priority":351},"scripts/degradation_detector.py",{"basePath":484,"description":485,"displayName":486,"installMethods":487,"rationale":488,"selectedPaths":489,"source":331,"sourceLanguage":18,"type":247},"skills/context-fundamentals","This skill should be used when the user asks to \"understand context\", \"explain context windows\", \"design agent architecture\", \"debug context issues\", \"optimize context usage\", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.","context-fundamentals",{"claudeCode":12},"SKILL.md frontmatter at skills/context-fundamentals/SKILL.md",[490,491,493],{"path":339,"priority":325},{"path":492,"priority":360},"references/context-components.md",{"path":494,"priority":351},"scripts/context_manager.py",{"basePath":496,"description":497,"displayName":498,"installMethods":499,"rationale":500,"selectedPaths":501,"source":331,"sourceLanguage":18,"type":247},"skills/context-optimization","This skill should be used when the user asks to \"optimize context\", \"reduce token costs\", \"improve context efficiency\", \"implement KV-cache optimization\", \"partition context\", or mentions context limits, observation masking, context budgeting, or extending effective context capacity.","context-optimization",{"claudeCode":12},"SKILL.md frontmatter at skills/context-optimization/SKILL.md",[502,503,505],{"path":339,"priority":325},{"path":504,"priority":360},"references/optimization_techniques.md",{"path":506,"priority":351},"scripts/compaction.py",{"basePath":508,"description":509,"displayName":510,"installMethods":511,"rationale":512,"selectedPaths":513,"source":331,"sourceLanguage":18,"type":247},"skills/evaluation","This skill should be used when the user asks to \"evaluate agent performance\", \"build test framework\", \"measure agent quality\", \"create evaluation rubrics\", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.","evaluation",{"claudeCode":12},"SKILL.md frontmatter at skills/evaluation/SKILL.md",[514,515,517],{"path":339,"priority":325},{"path":516,"priority":360},"references/metrics.md",{"path":518,"priority":351},"scripts/evaluator.py",{"basePath":520,"description":521,"displayName":522,"installMethods":523,"rationale":524,"selectedPaths":525,"source":331,"sourceLanguage":18,"type":247},"skills/filesystem-context","This skill should be used when the user asks to \"offload context to files\", \"implement dynamic context discovery\", \"use filesystem for agent memory\", \"reduce context window bloat\", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.","filesystem-context",{"claudeCode":12},"SKILL.md frontmatter at skills/filesystem-context/SKILL.md",[526,527,528],{"path":339,"priority":325},{"path":438,"priority":360},{"path":529,"priority":351},"scripts/filesystem_context.py",{"basePath":531,"description":532,"displayName":533,"installMethods":534,"rationale":535,"selectedPaths":536,"source":331,"sourceLanguage":18,"type":247},"skills/hosted-agents","This skill should be used when the user asks to \"build background agent\", \"create hosted coding agent\", \"set up sandboxed execution\", \"implement multiplayer agent\", or mentions background agents, sandboxed VMs, agent infrastructure, Modal sandboxes, self-spawning agents, or remote coding environments.","hosted-agents",{"claudeCode":12},"SKILL.md frontmatter at skills/hosted-agents/SKILL.md",[537,538,540],{"path":339,"priority":325},{"path":539,"priority":360},"references/infrastructure-patterns.md",{"path":541,"priority":351},"scripts/sandbox_manager.py",{"basePath":244,"description":10,"displayName":13,"installMethods":543,"rationale":544,"selectedPaths":545,"source":331,"sourceLanguage":18,"type":247},{"claudeCode":12},"SKILL.md frontmatter at skills/latent-briefing/SKILL.md",[546,547],{"path":339,"priority":325},{"path":548,"priority":360},"references/attention-matching-formulation.md",{"basePath":550,"description":551,"displayName":552,"installMethods":553,"rationale":554,"selectedPaths":555,"source":331,"sourceLanguage":18,"type":247},"skills/memory-systems","Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to \"implement agent memory\", \"persist state across sessions\", \"build knowledge graph for agents\", \"track entities over time\", \"add long-term memory\", \"choose a memory framework\", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory or memory benchmarks (LoCoMo, LongMemEval).\n","memory-systems",{"claudeCode":12},"SKILL.md frontmatter at skills/memory-systems/SKILL.md",[556,557,559],{"path":339,"priority":325},{"path":558,"priority":360},"references/implementation.md",{"path":560,"priority":351},"scripts/memory_store.py",{"basePath":562,"description":563,"displayName":564,"installMethods":565,"rationale":566,"selectedPaths":567,"source":331,"sourceLanguage":18,"type":247},"skills/multi-agent-patterns","This skill should be used when the user asks to \"design multi-agent system\", \"implement supervisor pattern\", \"create swarm architecture\", \"coordinate multiple agents\", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.","multi-agent-patterns",{"claudeCode":12},"SKILL.md frontmatter at skills/multi-agent-patterns/SKILL.md",[568,569,571],{"path":339,"priority":325},{"path":570,"priority":360},"references/frameworks.md",{"path":572,"priority":351},"scripts/coordination.py",{"basePath":574,"description":575,"displayName":576,"installMethods":577,"rationale":578,"selectedPaths":579,"source":331,"sourceLanguage":18,"type":247},"skills/project-development","This skill should be used when the user asks to \"start an LLM project\", \"design batch pipeline\", \"evaluate task-model fit\", \"structure agent project\", or mentions pipeline architecture, agent-assisted development, cost estimation, or choosing between LLM and traditional approaches.","project-development",{"claudeCode":12},"SKILL.md frontmatter at skills/project-development/SKILL.md",[580,581,583,585],{"path":339,"priority":325},{"path":582,"priority":360},"references/case-studies.md",{"path":584,"priority":360},"references/pipeline-patterns.md",{"path":586,"priority":351},"scripts/pipeline_template.py",{"basePath":588,"description":589,"displayName":590,"installMethods":591,"rationale":592,"selectedPaths":593,"source":331,"sourceLanguage":18,"type":247},"skills/tool-design","This skill should be used when the user asks to \"design agent tools\", \"create tool descriptions\", \"reduce tool complexity\", \"implement MCP tools\", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces.","tool-design",{"claudeCode":12},"SKILL.md frontmatter at skills/tool-design/SKILL.md",[594,595,597,599],{"path":339,"priority":325},{"path":596,"priority":360},"references/architectural_reduction.md",{"path":598,"priority":360},"references/best_practices.md",{"path":600,"priority":351},"scripts/description_generator.py",{"basePath":602,"description":603,"displayName":604,"installMethods":605,"rationale":606,"selectedPaths":607,"source":331,"sourceLanguage":18,"type":247},"template","Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection.","skill-template",{"claudeCode":12},"SKILL.md frontmatter at template/SKILL.md",[608],{"path":339,"priority":325},{"basePath":391,"installMethods":610,"rationale":611,"selectedPaths":612,"source":331,"sourceLanguage":18,"type":618},{"pypi":393},"cli ecosystem detected at examples/interleaved-thinking",[613,615,616],{"path":614,"priority":325},"pyproject.toml",{"path":327,"priority":325},{"path":617,"priority":360},"reasoning_trace_optimizer/cli.py","cli",{"sources":620},[621],"manual",{"closedIssues90d":232,"description":623,"forks":233,"license":238,"openIssues90d":234,"pushedAt":235,"readmeSize":230,"stars":236,"topics":624},"A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.",[],{"classifiedAt":626,"discoverAt":627,"extractAt":628,"githubAt":628,"updatedAt":626},1778694268713,1778694264629,1778694266904,[214,215,213,212,216],{"evaluatedAt":242,"extractAt":289,"updatedAt":242},[],[633,652,681,700,731,760],{"_creationTime":634,"_id":635,"community":636,"display":637,"identity":639,"providers":640,"relations":648,"tags":649,"workflow":650},1778694269038.669,"k171pshmgmyv8he1yhep1nkths86mr39",{"reviewCount":8},{"description":497,"installMethods":638,"name":498,"sourceUrl":14},{"claudeCode":12},{"basePath":496,"githubOwner":245,"githubRepo":246,"locale":18,"slug":498,"type":247},{"evaluate":641,"extract":647},{"promptVersionExtension":205,"promptVersionScoring":206,"score":642,"tags":643,"targetMarket":217,"tier":300},100,[215,644,645,213,646],"prompt-optimization","llm-efficiency","token-reduction",{"commitSha":278},{"parentExtensionId":250,"repoId":285},[215,213,645,644,646],{"evaluatedAt":651,"extractAt":289,"updatedAt":651},1778694467379,{"_creationTime":653,"_id":654,"community":655,"display":656,"identity":662,"providers":666,"relations":675,"tags":677,"workflow":678},1778696691708.305,"k1761mn31xs3mqzhk5zspj7s2186n127",{"reviewCount":8},{"description":657,"installMethods":658,"name":660,"sourceUrl":661},"Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows",{"claudeCode":659},"ruvnet/ruflo","stream-chain","https://github.com/ruvnet/ruflo",{"basePath":663,"githubOwner":664,"githubRepo":665,"locale":18,"slug":660,"type":247},".claude/skills/stream-chain","ruvnet","ruflo",{"evaluate":667,"extract":674},{"promptVersionExtension":205,"promptVersionScoring":206,"score":668,"tags":669,"targetMarket":217,"tier":300},99,[670,216,212,671,672,673],"workflow","data-transformation","pipelines","automation",{"commitSha":278},{"repoId":676},"kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[673,671,212,216,672,670],{"evaluatedAt":679,"extractAt":680,"updatedAt":679},1778699330891,1778696691708,{"_creationTime":682,"_id":683,"community":684,"display":685,"identity":688,"providers":689,"relations":696,"tags":697,"workflow":698},1778694269038.6682,"k1752cypc448mke749yjbkc65186mg6f",{"reviewCount":8},{"description":461,"installMethods":686,"name":687,"sourceUrl":14},{"claudeCode":12},"Context Compression",{"basePath":460,"githubOwner":245,"githubRepo":246,"locale":18,"slug":462,"type":247},{"evaluate":690,"extract":695},{"promptVersionExtension":205,"promptVersionScoring":206,"score":642,"tags":691,"targetMarket":217,"tier":300},[215,274,692,693,694,510],"agent","summarization","compression",{"commitSha":278,"license":238},{"parentExtensionId":250,"repoId":285},[692,694,215,510,274,693],{"evaluatedAt":699,"extractAt":289,"updatedAt":699},1778694410149,{"_creationTime":701,"_id":702,"community":703,"display":704,"identity":710,"providers":715,"relations":723,"tags":726,"workflow":727},1778693183736.296,"k17dd7padzjhbx1jwdfx6458vd86m5aa",{"reviewCount":8},{"description":705,"installMethods":706,"name":708,"sourceUrl":709},"Erstellt, aktualisiert oder optimiert eine AGENTS.md-Datei für ein Repository mit minimalen, hochgradig aussagekräftigen Anweisungen, die nicht entdeckbare Codierungs-Konventionen, Eigenheiten der Werkzeuge, Workflow-Präferenzen und projektspezifische Regeln abdecken, die Agenten nicht aus dem Code ableiten können. Verwenden Sie dies beim Einrichten von Agent-Anweisungen oder der Claude-Konfiguration für ein neues Repository, wenn eine vorhandene AGENTS.md zu lang, generisch oder veraltet ist, wenn Agenten wiederholt vermeidbare Fehler machen oder wenn sich die Repository-Workflows geändert haben und die Agent-Konfiguration bereinigt werden muss. Wendet einen Entdeckbarkeitsfilter an – der alles weglässt, was Claude aus README, Code, Konfiguration oder Verzeichnisstruktur lernen kann – und ein Qualitätstor, um zu überprüfen, ob jede Zeile korrekt und betrieblich relevant bleibt.",{"claudeCode":707},"mcollina/skills","init","https://github.com/mcollina/skills",{"basePath":711,"githubOwner":712,"githubRepo":713,"locale":714,"slug":708,"type":247},"skills/init","mcollina","skills","de",{"evaluate":716,"extract":722},{"promptVersionExtension":205,"promptVersionScoring":206,"score":642,"tags":717,"targetMarket":217,"tier":300},[718,719,215,720,721],"initialization","agents","agents-md","maintenance",{"commitSha":278},{"repoId":724,"translatedFrom":725},"kd7e22d93dm7xdjcrsgq33f53d86mqm7","k17e8fgrjhgk34vzyxq9phbaad86m56g",[719,720,215,718,721],{"evaluatedAt":728,"extractAt":729,"updatedAt":730},1778692978251,1778692906303,1778693183736,{"_creationTime":732,"_id":733,"community":734,"display":735,"identity":741,"providers":745,"relations":753,"tags":756,"workflow":757},1778699234184.6135,"k175frmf44tn80mcd6gvw1c1th86ngq9",{"reviewCount":8},{"description":736,"installMethods":737,"name":739,"sourceUrl":740},"Invoke parallel document-specialist agents for external web searches and documentation lookup",{"claudeCode":738},"Yeachan-Heo/oh-my-claudecode","external-context","https://github.com/Yeachan-Heo/oh-my-claudecode",{"basePath":742,"githubOwner":743,"githubRepo":744,"locale":18,"slug":739,"type":247},"skills/external-context","Yeachan-Heo","oh-my-claudecode",{"evaluate":746,"extract":752},{"promptVersionExtension":205,"promptVersionScoring":206,"score":642,"tags":747,"targetMarket":217,"tier":300},[748,749,750,751,212],"search","documentation","research","information-retrieval",{"commitSha":278},{"parentExtensionId":754,"repoId":755},"k17brg5egdw1jbncj1j4wfv3fh86n639","kd74zv63fryf9prygtq7gf4es986n22y",[749,751,212,750,748],{"evaluatedAt":758,"extractAt":759,"updatedAt":758},1778699449790,1778699234184,{"_creationTime":761,"_id":762,"community":763,"display":764,"identity":768,"providers":770,"relations":779,"tags":780,"workflow":781},1778696691708.3054,"k17by7bzagajqkcvcetdw10cz586nxbj",{"reviewCount":8},{"description":765,"installMethods":766,"name":767,"sourceUrl":661},"Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.",{"claudeCode":659},"swarm-orchestration",{"basePath":769,"githubOwner":664,"githubRepo":665,"locale":18,"slug":767,"type":247},".claude/skills/swarm-orchestration",{"evaluate":771,"extract":778},{"promptVersionExtension":205,"promptVersionScoring":206,"score":642,"tags":772,"targetMarket":217,"tier":300},[773,212,774,775,776,777],"agent-orchestration","swarm","distributed-systems","coordination","ai-workflow",{"commitSha":278},{"repoId":676},[773,777,776,775,212,774],{"evaluatedAt":782,"extractAt":680,"updatedAt":782},1778699363559]