[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-muratcankoylan-context-optimization-de":3,"guides-for-muratcankoylan-context-optimization":630,"similar-k171pshmgmyv8he1yhep1nkths86mr39-de":631},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":241,"isFallback":238,"parentExtension":246,"providers":307,"relations":311,"repo":312,"tags":628,"workflow":629},1778694269038.669,"k171pshmgmyv8he1yhep1nkths86mr39",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"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.",{"claudeCode":12},"muratcankoylan/Agent-Skills-for-Context-Engineering","context-optimization","https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":222,"workflow":239},1778694467379.8333,"kn7f45b2jsh6ep5syad37k1njn86nmrm","en",{"checks":20,"evaluatedAt":191,"extensionSummary":192,"features":193,"nonGoals":199,"promptVersionExtension":203,"promptVersionScoring":204,"purpose":205,"rationale":206,"score":207,"summary":208,"tags":209,"targetMarket":215,"tier":216,"useCases":217},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,113,116,120,123,126,129,132,134,137,141,145,149,152,156,159,162,165,168,172,175,178,181,184,188],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly identifies user problems like 'optimize context', 'reduce token costs', and 'implement KV-cache optimization', directly aligning with the skill's purpose.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill offers specific context engineering techniques (compaction, masking, KV-cache optimization, partitioning) that go beyond default LLM behavior, providing significant value for managing token costs and efficiency.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill provides a comprehensive set of documented strategies and practical guidance for context optimization, covering the complete lifecycle of managing context in agent systems.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill focuses exclusively on context engineering techniques, such as compaction, masking, and KV-cache optimization, without venturing into unrelated domains.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The displayed description accurately reflects the skill's purpose and the specific techniques detailed in the SKILL.md, including various trigger phrases.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This check is not applicable as the skill does not expose specific tools but rather provides guidance and strategies for prompt engineering.",{"category":45,"check":46,"severity":42,"summary":47},"Documentation","Configuration & parameter reference","The skill does not expose configurable parameters or options that require explicit documentation.",{"category":33,"check":49,"severity":42,"summary":50},"Tool naming","This check is not applicable as the skill does not expose user-facing tools or commands.",{"category":33,"check":52,"severity":42,"summary":53},"Minimal I/O surface","This check is not applicable as the skill does not expose specific tools with input/output schemas.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The LICENSE file indicates the MIT license, which is a permissive open-source license and is usable.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The last commit was on April 14, 2026, which is within the last 3 months.",{"category":59,"check":63,"severity":42,"summary":64},"Dependency Management","The skill does not appear to have third-party dependencies that require management.",{"category":66,"check":67,"severity":42,"summary":68},"Security","Secret Management","The skill does not handle or expose secrets.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The skill provides guidance and does not load or execute external third-party data as instructions.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The skill does not fetch remote content at runtime or include external files that could be manipulated.",{"category":66,"check":76,"severity":42,"summary":77},"Sandbox Isolation","The skill does not perform file system operations or interact with the environment in a way that would require sandbox isolation.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","No detached-process spawns or deny-retry loops are present as the skill is purely instructional.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill provides guidance and does not contain instructions to read or submit confidential data to a third party.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content is free of hidden-steering tricks, and descriptions are clean.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The bundle includes only plain, readable Python code, with no obfuscation or runtime fetched scripts.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The skill provides Python pseudocode examples that are platform-agnostic and do not make assumptions about user-specific project organization.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","There are 6 open and 2 closed issues in the last 90 days, indicating good maintainer engagement with a closure rate of 25%.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","The SKILL.md frontmatter declares a meaningful semver version (2.0.0).",{"category":104,"check":105,"severity":42,"summary":106},"Code Execution","Validation","This check is not applicable as the skill does not execute code or process structured output that requires schema validation.",{"category":66,"check":108,"severity":42,"summary":109},"Unguarded Destructive Operations","The skill is read-only and analytical, and does not perform any destructive operations.",{"category":104,"check":111,"severity":42,"summary":112},"Error Handling","This check is not applicable as the skill is purely instructional and does not have executable code paths with user-facing errors.",{"category":104,"check":114,"severity":42,"summary":115},"Logging","This check is not applicable as the skill is read-only and does not perform actions that require logging.",{"category":117,"check":118,"severity":42,"summary":119},"Compliance","GDPR","The skill provides guidance and does not operate on personal data.",{"category":117,"check":121,"severity":24,"summary":122},"Target market","The skill's principles are universal and not tied to any specific geography or legal jurisdiction; targetMarket is set to global.",{"category":92,"check":124,"severity":24,"summary":125},"Runtime stability","The skill's Python pseudocode examples are designed to be platform-agnostic, and no specific runtime assumptions are made.",{"category":45,"check":127,"severity":24,"summary":128},"README","The README file exists and clearly states the extension's purpose and how to install and use it.",{"category":33,"check":130,"severity":42,"summary":131},"Tool surface size","This check is not applicable as the skill does not expose specific tools.",{"category":40,"check":133,"severity":42,"summary":50},"Overlapping near-synonym tools",{"category":45,"check":135,"severity":24,"summary":136},"Phantom features","All features advertised in the README and SKILL.md have corresponding implementations or detailed explanations in the provided documentation.",{"category":138,"check":139,"severity":24,"summary":140},"Install","Installation instruction","The README provides clear installation instructions for Claude Code, including command-line examples and a direct install option.",{"category":142,"check":143,"severity":42,"summary":144},"Errors","Actionable error messages","This check is not applicable as the skill is purely instructional and does not have user-facing error paths.",{"category":146,"check":147,"severity":42,"summary":148},"Execution","Pinned dependencies","The skill does not use third-party dependencies that require pinning, and bundled scripts are illustrative pseudocode.",{"category":33,"check":150,"severity":42,"summary":151},"Dry-run preview","This check is not applicable as the skill is purely read-only and analytical, offering guidance rather than performing actions.",{"category":153,"check":154,"severity":42,"summary":155},"Protocol","Idempotent retry & timeouts","This check is not applicable as the skill does not perform remote calls or state-changing operations.",{"category":117,"check":157,"severity":42,"summary":158},"Telemetry opt-in","The skill does not emit telemetry.",{"category":40,"check":160,"severity":24,"summary":161},"Precise Purpose","The SKILL.md clearly states what the skill does (context optimization techniques) and when to use it (context limits, cost reduction), naming artifacts (context) and user intents (optimize, reduce costs).",{"category":40,"check":163,"severity":24,"summary":164},"Concise Frontmatter","The frontmatter is concise, self-contained, and effectively summarizes the core capability and trigger phrases without excessive length.",{"category":45,"check":166,"severity":24,"summary":167},"Concise Body","The SKILL.md is well-structured, under 500 lines, and delegates deeper material to separate reference files.",{"category":169,"check":170,"severity":24,"summary":171},"Context","Progressive Disclosure","The SKILL.md outlines the flow and links to a detailed `references/optimization_techniques.md` file for specific patterns and code examples.",{"category":169,"check":173,"severity":42,"summary":174},"Forked exploration","This check is not applicable as the skill provides direct guidance and does not involve deep exploration or code review that would necessitate forked context.",{"category":22,"check":176,"severity":24,"summary":177},"Usage examples","The SKILL.md includes three practical Python pseudocode examples demonstrating compaction trigger, observation masking, and cache-friendly ordering.",{"category":22,"check":179,"severity":24,"summary":180},"Edge cases","The 'Gotchas' section in SKILL.md documents at least two failure modes (whitespace breaks KV-cache, timestamps in system prompts) with observable symptoms and implies recovery steps.",{"category":104,"check":182,"severity":42,"summary":183},"Tool Fallback","This check is not applicable as the skill does not rely on external tools like an MCP server and does not have a fallback path.",{"category":185,"check":186,"severity":24,"summary":187},"Safety","Halt on unexpected state","The 'Gotchas' section implicitly instructs to halt or reconsider actions (e.g., 'suspend masking for all error-related observations') when unexpected states arise, and the advice on prompt stability implies error reporting on drift.",{"category":92,"check":189,"severity":24,"summary":190},"Cross-skill coupling","The skill is self-contained and focuses on context engineering principles; it references other related skills explicitly in the 'Integration' and 'References' sections rather than implicitly relying on them.",1778694467278,"This skill provides detailed strategies and practical guidance for optimizing LLM context windows using techniques such as compaction, observation masking, KV-cache optimization, and context partitioning. It includes Python pseudocode examples and discusses potential pitfalls and performance targets.",[194,195,196,197,198],"Context compaction strategies","Observation masking for verbose outputs","KV-cache optimization for prompt stability","Context partitioning for large tasks","Token budget management and monitoring",[200,201,202],"Implementing specific LLM models or inference engines","Replacing prompt engineering; rather, it complements it","Providing a direct API for automated context manipulation (focus is on guidance)","3.0.0","4.4.0","To teach users how to maximize LLM effectiveness and reduce costs by intelligently managing and optimizing the information within the context window.","All checks passed with 'pass' or 'not_applicable' severity. Documentation is comprehensive and well-structured, with clear explanations and practical examples.",100,"A high-quality, well-documented skill for optimizing LLM context window usage through advanced techniques.",[210,211,212,213,214],"context-engineering","prompt-optimization","llm-efficiency","kv-cache","token-reduction","global","verified",[218,219,220,221],"Reducing token costs in long conversations or with large documents","Improving agent latency by optimizing context efficiency","Implementing production-grade agent systems at scale","Handling complex tasks that push context window limits",{"codeQuality":223,"collectedAt":225,"documentation":226,"maintenance":229,"security":235,"testCoverage":237},{"hasLockfile":224},false,1778694449690,{"descriptionLength":227,"readmeSize":228},284,13763,{"closedIssues90d":230,"forks":231,"hasChangelog":224,"openIssues90d":232,"pushedAt":233,"stars":234},2,1237,6,1776141908000,15630,{"hasNpmPackage":224,"license":236,"smitheryVerified":224},"MIT",{"hasCi":224,"hasTests":238},true,{"updatedAt":240},1778694467379,{"basePath":242,"githubOwner":243,"githubRepo":244,"locale":18,"slug":13,"type":245},"skills/context-optimization","muratcankoylan","Agent-Skills-for-Context-Engineering","skill",{"_creationTime":247,"_id":248,"community":249,"display":250,"identity":254,"parentExtension":257,"providers":290,"relations":303,"tags":304,"workflow":305},1778694269038.6665,"k1754dy3wbsv2a5gr1a983zzs586njca",{"reviewCount":8},{"description":251,"installMethods":252,"name":253,"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":244},"Agent Skills for Context Engineering",{"basePath":255,"githubOwner":243,"githubRepo":244,"locale":18,"slug":244,"type":256},"","plugin",{"_creationTime":258,"_id":259,"community":260,"display":261,"identity":264,"providers":266,"relations":284,"tags":286,"workflow":287},1778694269038.6663,"k1796gc85sm2bx753svn59gp5186mpz4",{"reviewCount":8},{"description":262,"installMethods":263,"name":253,"sourceUrl":14},"Context Engineering skills for building production-grade AI agent systems",{"claudeCode":12},{"basePath":255,"githubOwner":243,"githubRepo":244,"locale":18,"slug":244,"type":265},"marketplace",{"evaluate":267,"extract":277},{"promptVersionExtension":268,"promptVersionScoring":204,"score":269,"tags":270,"targetMarket":215,"tier":276},"3.1.0",75,[271,272,210,273,274,275],"ai","agent-skills","llm","development","architecture","community",{"commitSha":278,"license":236,"marketplace":279,"plugin":282},"HEAD",{"name":280,"pluginCount":281},"context-engineering-marketplace",1,{"mcpCount":8,"provider":283,"skillCount":8},"classify",{"repoId":285},"kd7f12maf5nxmx5xttjx7scfnx86m1tv",[272,271,275,210,274,273],{"evaluatedAt":288,"extractAt":289,"updatedAt":288},1778694283498,1778694269038,{"evaluate":291,"extract":300},{"promptVersionExtension":203,"promptVersionScoring":204,"score":292,"tags":293,"targetMarket":215,"tier":216},95,[210,294,295,296,297,298,299],"ai-agents","prompt-engineering","multi-agent-systems","llm-operations","agent-architecture","cognitive-architecture",{"commitSha":278,"license":236,"plugin":301},{"mcpCount":8,"provider":283,"skillCount":302},14,{"parentExtensionId":259,"repoId":285},[298,294,299,210,297,296,295],{"evaluatedAt":306,"extractAt":289,"updatedAt":306},1778694291902,{"evaluate":308,"extract":310},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":309,"targetMarket":215,"tier":216},[210,211,212,213,214],{"commitSha":278},{"parentExtensionId":248,"repoId":285},{"_creationTime":313,"_id":285,"identity":314,"providers":315,"workflow":624},1778694264629.3296,{"githubOwner":243,"githubRepo":244,"sourceUrl":14},{"classify":316,"discover":618,"github":621},{"commitSha":278,"extensions":317},[318,331,339,366,389,410,424,442,458,470,482,494,503,515,526,538,548,560,572,586,600,608],{"basePath":255,"description":262,"displayName":280,"installMethods":319,"rationale":320,"selectedPaths":321,"source":330,"sourceLanguage":18,"type":265},{"claudeCode":12},"marketplace.json at .claude-plugin/marketplace.json",[322,325,327],{"path":323,"priority":324},".claude-plugin/marketplace.json","mandatory",{"path":326,"priority":324},"README.md",{"path":328,"priority":329},"LICENSE","high","rule",{"basePath":255,"description":251,"displayName":210,"installMethods":332,"rationale":333,"selectedPaths":334,"source":330,"sourceLanguage":18,"type":256},{"claudeCode":244},"inline plugin source from marketplace.json at / (coalesced with duplicate plugin at .plugin)",[335,336,337],{"path":326,"priority":324},{"path":328,"priority":329},{"path":338,"priority":329},"SKILL.md",{"basePath":340,"description":341,"displayName":342,"installMethods":343,"rationale":344,"selectedPaths":345,"source":330,"sourceLanguage":18,"type":245},"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",[346,347,348,351,353,355,357,360,362,364],{"path":338,"priority":324},{"path":326,"priority":329},{"path":349,"priority":350},"examples/gertrude-stein/README.md","low",{"path":352,"priority":350},"examples/gertrude-stein/dataset_sample.jsonl",{"path":354,"priority":350},"examples/gertrude-stein/sample_outputs.md",{"path":356,"priority":350},"examples/gertrude-stein/training_config.json",{"path":358,"priority":359},"references/segmentation-strategies.md","medium",{"path":361,"priority":359},"references/tinker-format.md",{"path":363,"priority":359},"references/tinker.txt",{"path":365,"priority":350},"scripts/pipeline_example.py",{"basePath":367,"description":368,"displayName":369,"installMethods":370,"rationale":371,"selectedPaths":372,"source":330,"sourceLanguage":18,"type":245},"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",[373,374,375,377,379,381,383,385,387],{"path":338,"priority":324},{"path":326,"priority":329},{"path":376,"priority":359},"AGENT.md",{"path":378,"priority":359},"HOW-SKILLS-BUILT-THIS.md",{"path":380,"priority":359},"SKILLS-MAPPING.md",{"path":382,"priority":350},"examples/content-workflow.md",{"path":384,"priority":350},"examples/meeting-prep.md",{"path":386,"priority":359},"references/file-formats.md",{"path":388,"priority":350},"scripts/install.sh",{"basePath":390,"description":391,"displayName":392,"installMethods":393,"rationale":394,"selectedPaths":395,"source":330,"sourceLanguage":18,"type":245},"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",[396,397,398,400,402,404,406,408],{"path":338,"priority":324},{"path":326,"priority":329},{"path":399,"priority":350},"docs/agentthinking.md",{"path":401,"priority":350},"docs/interleavedthinking.md",{"path":403,"priority":350},"docs/m2-1.md",{"path":405,"priority":350},"examples/01_basic_capture.py",{"path":407,"priority":350},"examples/02_tool_usage.py",{"path":409,"priority":350},"examples/03_full_optimization.py",{"basePath":411,"description":412,"displayName":413,"installMethods":414,"rationale":415,"selectedPaths":416,"source":330,"sourceLanguage":18,"type":245},"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",[417,418,420,422],{"path":338,"priority":324},{"path":419,"priority":359},"references/optimization_summary.json",{"path":421,"priority":359},"references/optimized_prompt.txt",{"path":423,"priority":359},"references/patterns_found.json",{"basePath":425,"description":426,"displayName":427,"installMethods":428,"rationale":429,"selectedPaths":430,"source":330,"sourceLanguage":18,"type":245},"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",[431,432,434,436,438,440],{"path":338,"priority":324},{"path":433,"priority":359},"references/bias-mitigation.md",{"path":435,"priority":359},"references/evaluation-pipeline.md",{"path":437,"priority":359},"references/implementation-patterns.md",{"path":439,"priority":359},"references/metrics-guide.md",{"path":441,"priority":350},"scripts/evaluation_example.py",{"basePath":443,"description":444,"displayName":445,"installMethods":446,"rationale":447,"selectedPaths":448,"source":330,"sourceLanguage":18,"type":245},"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",[449,450,452,454,456],{"path":338,"priority":324},{"path":451,"priority":359},"references/bdi-ontology-core.md",{"path":453,"priority":359},"references/framework-integration.md",{"path":455,"priority":359},"references/rdf-examples.md",{"path":457,"priority":359},"references/sparql-competency.md",{"basePath":459,"description":460,"displayName":461,"installMethods":462,"rationale":463,"selectedPaths":464,"source":330,"sourceLanguage":18,"type":245},"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",[465,466,468],{"path":338,"priority":324},{"path":467,"priority":359},"references/evaluation-framework.md",{"path":469,"priority":350},"scripts/compression_evaluator.py",{"basePath":471,"description":472,"displayName":473,"installMethods":474,"rationale":475,"selectedPaths":476,"source":330,"sourceLanguage":18,"type":245},"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",[477,478,480],{"path":338,"priority":324},{"path":479,"priority":359},"references/patterns.md",{"path":481,"priority":350},"scripts/degradation_detector.py",{"basePath":483,"description":484,"displayName":485,"installMethods":486,"rationale":487,"selectedPaths":488,"source":330,"sourceLanguage":18,"type":245},"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",[489,490,492],{"path":338,"priority":324},{"path":491,"priority":359},"references/context-components.md",{"path":493,"priority":350},"scripts/context_manager.py",{"basePath":242,"description":10,"displayName":13,"installMethods":495,"rationale":496,"selectedPaths":497,"source":330,"sourceLanguage":18,"type":245},{"claudeCode":12},"SKILL.md frontmatter at skills/context-optimization/SKILL.md",[498,499,501],{"path":338,"priority":324},{"path":500,"priority":359},"references/optimization_techniques.md",{"path":502,"priority":350},"scripts/compaction.py",{"basePath":504,"description":505,"displayName":506,"installMethods":507,"rationale":508,"selectedPaths":509,"source":330,"sourceLanguage":18,"type":245},"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",[510,511,513],{"path":338,"priority":324},{"path":512,"priority":359},"references/metrics.md",{"path":514,"priority":350},"scripts/evaluator.py",{"basePath":516,"description":517,"displayName":518,"installMethods":519,"rationale":520,"selectedPaths":521,"source":330,"sourceLanguage":18,"type":245},"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",[522,523,524],{"path":338,"priority":324},{"path":437,"priority":359},{"path":525,"priority":350},"scripts/filesystem_context.py",{"basePath":527,"description":528,"displayName":529,"installMethods":530,"rationale":531,"selectedPaths":532,"source":330,"sourceLanguage":18,"type":245},"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",[533,534,536],{"path":338,"priority":324},{"path":535,"priority":359},"references/infrastructure-patterns.md",{"path":537,"priority":350},"scripts/sandbox_manager.py",{"basePath":539,"description":540,"displayName":541,"installMethods":542,"rationale":543,"selectedPaths":544,"source":330,"sourceLanguage":18,"type":245},"skills/latent-briefing","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.","latent-briefing",{"claudeCode":12},"SKILL.md frontmatter at skills/latent-briefing/SKILL.md",[545,546],{"path":338,"priority":324},{"path":547,"priority":359},"references/attention-matching-formulation.md",{"basePath":549,"description":550,"displayName":551,"installMethods":552,"rationale":553,"selectedPaths":554,"source":330,"sourceLanguage":18,"type":245},"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",[555,556,558],{"path":338,"priority":324},{"path":557,"priority":359},"references/implementation.md",{"path":559,"priority":350},"scripts/memory_store.py",{"basePath":561,"description":562,"displayName":563,"installMethods":564,"rationale":565,"selectedPaths":566,"source":330,"sourceLanguage":18,"type":245},"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",[567,568,570],{"path":338,"priority":324},{"path":569,"priority":359},"references/frameworks.md",{"path":571,"priority":350},"scripts/coordination.py",{"basePath":573,"description":574,"displayName":575,"installMethods":576,"rationale":577,"selectedPaths":578,"source":330,"sourceLanguage":18,"type":245},"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",[579,580,582,584],{"path":338,"priority":324},{"path":581,"priority":359},"references/case-studies.md",{"path":583,"priority":359},"references/pipeline-patterns.md",{"path":585,"priority":350},"scripts/pipeline_template.py",{"basePath":587,"description":588,"displayName":589,"installMethods":590,"rationale":591,"selectedPaths":592,"source":330,"sourceLanguage":18,"type":245},"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",[593,594,596,598],{"path":338,"priority":324},{"path":595,"priority":359},"references/architectural_reduction.md",{"path":597,"priority":359},"references/best_practices.md",{"path":599,"priority":350},"scripts/description_generator.py",{"basePath":601,"description":602,"displayName":603,"installMethods":604,"rationale":605,"selectedPaths":606,"source":330,"sourceLanguage":18,"type":245},"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",[607],{"path":338,"priority":324},{"basePath":390,"installMethods":609,"rationale":610,"selectedPaths":611,"source":330,"sourceLanguage":18,"type":617},{"pypi":392},"cli ecosystem detected at examples/interleaved-thinking",[612,614,615],{"path":613,"priority":324},"pyproject.toml",{"path":326,"priority":324},{"path":616,"priority":359},"reasoning_trace_optimizer/cli.py","cli",{"sources":619},[620],"manual",{"closedIssues90d":230,"description":622,"forks":231,"license":236,"openIssues90d":232,"pushedAt":233,"readmeSize":228,"stars":234,"topics":623},"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":625,"discoverAt":626,"extractAt":627,"githubAt":627,"updatedAt":625},1778694268713,1778694264629,1778694266904,[210,213,212,211,214],{"evaluatedAt":240,"extractAt":289,"updatedAt":240},[],[632,650,669,700,719,740],{"_creationTime":633,"_id":634,"community":635,"display":636,"identity":638,"providers":639,"relations":646,"tags":647,"workflow":648},1778694269038.67,"k177vey9xnw010b18xbr84mea986nz00",{"reviewCount":8},{"description":540,"installMethods":637,"name":541,"sourceUrl":14},{"claudeCode":12},{"basePath":539,"githubOwner":243,"githubRepo":244,"locale":18,"slug":541,"type":245},{"evaluate":640,"extract":645},{"promptVersionExtension":203,"promptVersionScoring":204,"score":269,"tags":641,"targetMarket":215,"tier":276},[642,213,643,210,644],"multi-agent","compaction","orchestration",{"commitSha":278},{"parentExtensionId":248,"repoId":285},[643,210,213,642,644],{"evaluatedAt":649,"extractAt":289,"updatedAt":649},1778694530621,{"_creationTime":651,"_id":652,"community":653,"display":654,"identity":657,"providers":658,"relations":665,"tags":666,"workflow":667},1778694269038.6682,"k1752cypc448mke749yjbkc65186mg6f",{"reviewCount":8},{"description":460,"installMethods":655,"name":656,"sourceUrl":14},{"claudeCode":12},"Context Compression",{"basePath":459,"githubOwner":243,"githubRepo":244,"locale":18,"slug":461,"type":245},{"evaluate":659,"extract":664},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":660,"targetMarket":215,"tier":216},[210,273,661,662,663,506],"agent","summarization","compression",{"commitSha":278,"license":236},{"parentExtensionId":248,"repoId":285},[661,663,210,506,273,662],{"evaluatedAt":668,"extractAt":289,"updatedAt":668},1778694410149,{"_creationTime":670,"_id":671,"community":672,"display":673,"identity":679,"providers":684,"relations":692,"tags":695,"workflow":696},1778693183736.296,"k17dd7padzjhbx1jwdfx6458vd86m5aa",{"reviewCount":8},{"description":674,"installMethods":675,"name":677,"sourceUrl":678},"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":676},"mcollina/skills","init","https://github.com/mcollina/skills",{"basePath":680,"githubOwner":681,"githubRepo":682,"locale":683,"slug":677,"type":245},"skills/init","mcollina","skills","de",{"evaluate":685,"extract":691},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":686,"targetMarket":215,"tier":216},[687,688,210,689,690],"initialization","agents","agents-md","maintenance",{"commitSha":278},{"repoId":693,"translatedFrom":694},"kd7e22d93dm7xdjcrsgq33f53d86mqm7","k17e8fgrjhgk34vzyxq9phbaad86m56g",[688,689,210,687,690],{"evaluatedAt":697,"extractAt":698,"updatedAt":699},1778692978251,1778692906303,1778693183736,{"_creationTime":701,"_id":702,"community":703,"display":704,"identity":706,"providers":707,"relations":715,"tags":716,"workflow":717},1778694269038.6711,"k17482zgbqqtx5ee19mxpscjvn86mqmd",{"reviewCount":8},{"description":602,"installMethods":705,"name":603,"sourceUrl":14},{"claudeCode":12},{"basePath":601,"githubOwner":243,"githubRepo":244,"locale":18,"slug":601,"type":245},{"evaluate":708,"extract":714},{"promptVersionExtension":203,"promptVersionScoring":204,"score":709,"tags":710,"targetMarket":215,"tier":216},99,[601,711,210,712,713],"skill-creation","documentation","ai-agent",{"commitSha":278},{"repoId":285},[713,210,712,711,601],{"evaluatedAt":718,"extractAt":289,"updatedAt":718},1778694602630,{"_creationTime":720,"_id":721,"community":722,"display":723,"identity":726,"providers":728,"relations":736,"tags":737,"workflow":738},1778694269038.667,"k17b7wd19vrarjetttm1ggnx2n86n73r",{"reviewCount":8},{"description":368,"installMethods":724,"name":725,"sourceUrl":14},{"claudeCode":12},"Digital Brain",{"basePath":367,"githubOwner":243,"githubRepo":244,"locale":18,"slug":727,"type":245},"digital-brain-skill",{"evaluate":729,"extract":735},{"promptVersionExtension":203,"promptVersionScoring":204,"score":709,"tags":730,"targetMarket":215,"tier":216},[731,732,733,734,210],"personal-knowledge-management","content-creation","productivity","automation",{"commitSha":278,"license":236},{"repoId":285},[734,732,210,731,733],{"evaluatedAt":739,"extractAt":289,"updatedAt":739},1778694330628,{"_creationTime":741,"_id":742,"community":743,"display":744,"identity":750,"providers":754,"relations":760,"tags":764,"workflow":765},1778696887416.8103,"k174q6jqr70bhac19gxkqxr1th86nkfa",{"reviewCount":8},{"description":745,"installMethods":746,"name":748,"sourceUrl":749},"Kostensensible Claude Code-Modus. Reduziert Ausgabetokens um 40-70 % und Gesamtkosten um 30-60 %, indem prägnante Antworten, intelligentes Modell-Routing und effiziente Workflow-Muster durchgesetzt werden. Behält die volle technische Genauigkeit bei. Aktivieren Sie mit /cost-mode oder „enable cost mode“. Automatische Auslösung bei Erwähnung von Budget, Kosten, Tokens oder Ausgaben.\n",{"claudeCode":747},"Sagargupta16/claude-cost-optimizer","cost-mode","https://github.com/Sagargupta16/claude-cost-optimizer",{"basePath":751,"githubOwner":752,"githubRepo":753,"locale":683,"slug":748,"type":245},"skills/cost-mode","Sagargupta16","claude-cost-optimizer",{"evaluate":755,"extract":759},{"promptVersionExtension":203,"promptVersionScoring":204,"score":709,"tags":756,"targetMarket":215,"tier":216},[757,212,295,758],"cost-optimization","claude-code",{"commitSha":278},{"parentExtensionId":761,"repoId":762,"translatedFrom":763},"k1752jjawz8vy49fxchx4f3fyx86nfkd","kd7001v1z5cqn8kbm748zh0x4n86nrmc","k17bqyyps2cdpq2yaw8zpb9gy186nm8t",[758,757,212,295],{"evaluatedAt":766,"extractAt":767,"updatedAt":768},1778696832772,1778696773814,1778696887416]