[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-muratcankoylan-context-fundamentals-zh-CN":3,"guides-for-muratcankoylan-context-fundamentals":629,"similar-k17fyht5fnsrgxcy2s5ncc4hnh86npkn-zh-CN":630},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":242,"isFallback":239,"parentExtension":247,"providers":306,"relations":310,"repo":311,"tags":627,"workflow":628},1778694269038.6687,"k17fyht5fnsrgxcy2s5ncc4hnh86npkn",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"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.",{"claudeCode":12},"muratcankoylan/Agent-Skills-for-Context-Engineering","context-fundamentals","https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":223,"workflow":240},1778694449355.141,"kn7fvs4hbprzc8185s1391yre586nnv7","en",{"checks":20,"evaluatedAt":193,"extensionSummary":194,"features":195,"nonGoals":200,"promptVersionExtension":204,"promptVersionScoring":205,"purpose":206,"rationale":207,"score":208,"summary":209,"tags":210,"targetMarket":216,"tier":217,"useCases":218},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,100,104,108,111,115,118,122,125,128,131,134,137,140,144,148,151,154,158,161,164,167,170,174,177,180,183,186,190],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly names concrete problems like 'understand context', 'explain context windows', and 'design agent architecture', directly addressing user needs in context engineering.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill offers a unique value proposition by providing foundational understanding and actionable techniques for context engineering, going beyond basic LLM capabilities and focusing on specific constraints and principles.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill provides comprehensive guidance on context engineering principles, covering design, debugging, and optimization, making it suitable for direct application in real-world agent workflows.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill focuses exclusively on context engineering fundamentals, without introducing unrelated capabilities or domains.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The displayed description accurately reflects the skill's content, clearly outlining its purpose and scope in context engineering.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This skill does not expose tools directly; its functionality is based on providing knowledge and guidance through prose.",{"category":45,"check":46,"severity":42,"summary":47},"Documentation","Configuration & parameter reference","The skill does not have configurable parameters or options.",{"category":33,"check":49,"severity":42,"summary":50},"Tool naming","This skill does not expose tools with specific names.",{"category":33,"check":52,"severity":42,"summary":53},"Minimal I/O surface","This skill does not have a direct I/O surface as it is knowledge-based.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The MIT license is clearly stated in the LICENSE file and the README, permitting broad usability.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The last commit was on 2026-04-14, which is within the last 3 months.",{"category":59,"check":63,"severity":42,"summary":64},"Dependency Management","The skill does not appear to use any third-party dependencies.",{"category":66,"check":67,"severity":42,"summary":68},"Security","Secret Management","The skill does not handle or expose any secrets.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The skill provides guidance and does not load external data or instructions that could be subject to injection.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The skill does not fetch remote content at runtime or execute external scripts, mitigating supply-chain risks.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","As a knowledge-based skill, it does not modify files or perform operations outside of its defined scope.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","The skill does not involve code execution that could lead to sandbox escape primitives.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill's function is purely informational and does not involve submitting any data to third parties.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled content is free of hidden-steering tricks and uses clean printable ASCII and expected Unicode.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The skill's content is plain, readable markdown and Python pseudocode, not obfuscated or dynamically fetched.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The skill's Python pseudocode uses generic file paths and does not make assumptions about user-specific project organization.",{"category":96,"check":97,"severity":98,"summary":99},"Trust","Issues Attention","warning","There were 6 issues opened and 2 closed in the last 90 days, indicating a low closure rate and slow maintainer response.",{"category":101,"check":102,"severity":24,"summary":103},"Versioning","Release Management","The skill has a semantically meaningful version '2.0.0' declared in its SKILL.md frontmatter.",{"category":105,"check":106,"severity":42,"summary":107},"Execution","Validation","The skill does not involve executable code with structured input/output that requires schema validation.",{"category":66,"check":109,"severity":24,"summary":110},"Unguarded Destructive Operations","The skill is purely informational and does not perform any destructive operations.",{"category":112,"check":113,"severity":42,"summary":114},"Code Execution","Error Handling","As a knowledge-based skill, it does not have error paths requiring structured error handling.",{"category":112,"check":116,"severity":42,"summary":117},"Logging","The skill is read-only and does not perform actions requiring logging.",{"category":119,"check":120,"severity":42,"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 principles are universal and not bound to any specific geography or legal jurisdiction.",{"category":92,"check":126,"severity":24,"summary":127},"Runtime stability","The skill's Python pseudocode is platform-agnostic and does not rely on specific runtimes or OS features.",{"category":45,"check":129,"severity":24,"summary":130},"README","The README file exists, is comprehensive, and clearly states the extension's purpose and installation instructions.",{"category":33,"check":132,"severity":42,"summary":133},"Tool surface size","This skill does not expose tools, so tool surface size is not applicable.",{"category":40,"check":135,"severity":42,"summary":136},"Overlapping near-synonym tools","The skill does not expose tools, making this check not applicable.",{"category":45,"check":138,"severity":24,"summary":139},"Phantom features","All advertised features in the README and SKILL.md have corresponding implementations or detailed explanations within the skill's documentation.",{"category":141,"check":142,"severity":24,"summary":143},"Install","Installation instruction","The README provides clear, copy-pasteable installation instructions for Claude Code and individual skill usage.",{"category":145,"check":146,"severity":42,"summary":147},"Errors","Actionable error messages","The skill does not have user-facing error paths as it is knowledge-based.",{"category":105,"check":149,"severity":42,"summary":150},"Pinned dependencies","The skill does not use third-party dependencies that require pinning.",{"category":33,"check":152,"severity":42,"summary":153},"Dry-run preview","The skill is informational and does not perform state-changing operations requiring a dry-run.",{"category":155,"check":156,"severity":42,"summary":157},"Protocol","Idempotent retry & timeouts","The skill does not involve remote calls or state-changing operations that require idempotency or timeouts.",{"category":119,"check":159,"severity":42,"summary":160},"Telemetry opt-in","The skill does not emit any telemetry.",{"category":40,"check":162,"severity":24,"summary":163},"Precise Purpose","The skill's purpose is precisely stated, naming the artifact (context) and user intent (understand, design, debug, optimize) with clear boundaries.",{"category":40,"check":165,"severity":24,"summary":166},"Concise Frontmatter","The frontmatter is concise and effectively summarizes the core capability and trigger phrases within optimal character limits.",{"category":45,"check":168,"severity":24,"summary":169},"Concise Body","The skill body is under 500 lines and delegates deeper material to separate reference files, following progressive disclosure.",{"category":171,"check":172,"severity":24,"summary":173},"Context","Progressive Disclosure","The skill demonstrates progressive disclosure by outlining flows and linking to detailed reference files, avoiding embedding large amounts of material inline.",{"category":171,"check":175,"severity":42,"summary":176},"Forked exploration","This skill does not involve heavy exploration or code review that would require forked context.",{"category":22,"check":178,"severity":24,"summary":179},"Usage examples","Sufficient examples are included, demonstrating core concepts like system prompt organization and progressive document loading, and plausibly produce the claimed output.",{"category":22,"check":181,"severity":24,"summary":182},"Edge cases","The skill documents at least two failure modes (token drift, U-shaped attention) with observable symptoms and recovery steps.",{"category":112,"check":184,"severity":42,"summary":185},"Tool Fallback","The skill does not rely on external tools like MCP servers, making this check not applicable.",{"category":187,"check":188,"severity":24,"summary":189},"Safety","Halt on unexpected state","The skill's guidance emphasizes aborting and reporting on unexpected pre-state, aligning with safe workflow practices.",{"category":92,"check":191,"severity":24,"summary":192},"Cross-skill coupling","The skill is self-contained and does not implicitly rely on other skills, with explicit cross-linking to related skills when necessary.",1778694449241,"This skill provides foundational knowledge and practical techniques for context engineering in AI agent systems, covering system prompts, tool definitions, message history, and attention mechanics.",[196,197,198,199],"Explains context components: system prompts, tool definitions, message history, and tool outputs.","Details attention mechanics and context window limitations.","Provides practical guidance on file-system access and hybrid context strategies.","Offers actionable advice on context budgeting and quality versus quantity.",[201,202,203],"Providing context-specific solutions for individual LLM providers.","Implementing concrete agent logic; focuses on underlying principles.","Replacing prompt engineering; aims to complement it with context strategy.","3.0.0","4.4.0","To equip users with the foundational understanding and practical techniques necessary to effectively design, debug, and optimize context for AI agent systems.","The skill is exceptionally well-documented and practical, with a clear purpose, excellent examples, and thorough coverage of context engineering principles. The only minor finding is a slow issue closure rate.",90,"Comprehensive and practical skill for understanding and engineering AI agent context.",[211,212,213,214,215],"context-engineering","llm","agent-design","prompt-engineering","documentation","global","community",[219,220,221,222],"Designing new agent architectures.","Debugging unexpected agent behavior related to context.","Optimizing context usage for token costs and performance.","Onboarding new team members to context engineering concepts.",{"codeQuality":224,"collectedAt":226,"documentation":227,"maintenance":230,"security":236,"testCoverage":238},{"hasLockfile":225},false,1778694436964,{"descriptionLength":228,"readmeSize":229},356,13763,{"closedIssues90d":231,"forks":232,"hasChangelog":225,"openIssues90d":233,"pushedAt":234,"stars":235},2,1237,6,1776141908000,15630,{"hasNpmPackage":225,"license":237,"smitheryVerified":225},"MIT",{"hasCi":225,"hasTests":239},true,{"updatedAt":241},1778694449355,{"basePath":243,"githubOwner":244,"githubRepo":245,"locale":18,"slug":13,"type":246},"skills/context-fundamentals","muratcankoylan","Agent-Skills-for-Context-Engineering","skill",{"_creationTime":248,"_id":249,"community":250,"display":251,"identity":255,"parentExtension":258,"providers":289,"relations":302,"tags":303,"workflow":304},1778694269038.6665,"k1754dy3wbsv2a5gr1a983zzs586njca",{"reviewCount":8},{"description":252,"installMethods":253,"name":254,"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":245},"Agent Skills for Context Engineering",{"basePath":256,"githubOwner":244,"githubRepo":245,"locale":18,"slug":245,"type":257},"","plugin",{"_creationTime":259,"_id":260,"community":261,"display":262,"identity":265,"providers":267,"relations":283,"tags":285,"workflow":286},1778694269038.6663,"k1796gc85sm2bx753svn59gp5186mpz4",{"reviewCount":8},{"description":263,"installMethods":264,"name":254,"sourceUrl":14},"Context Engineering skills for building production-grade AI agent systems",{"claudeCode":12},{"basePath":256,"githubOwner":244,"githubRepo":245,"locale":18,"slug":245,"type":266},"marketplace",{"evaluate":268,"extract":276},{"promptVersionExtension":269,"promptVersionScoring":205,"score":270,"tags":271,"targetMarket":216,"tier":217},"3.1.0",75,[272,273,211,212,274,275],"ai","agent-skills","development","architecture",{"commitSha":277,"license":237,"marketplace":278,"plugin":281},"HEAD",{"name":279,"pluginCount":280},"context-engineering-marketplace",1,{"mcpCount":8,"provider":282,"skillCount":8},"classify",{"repoId":284},"kd7f12maf5nxmx5xttjx7scfnx86m1tv",[273,272,275,211,274,212],{"evaluatedAt":287,"extractAt":288,"updatedAt":287},1778694283498,1778694269038,{"evaluate":290,"extract":299},{"promptVersionExtension":204,"promptVersionScoring":205,"score":291,"tags":292,"targetMarket":216,"tier":298},95,[211,293,214,294,295,296,297],"ai-agents","multi-agent-systems","llm-operations","agent-architecture","cognitive-architecture","verified",{"commitSha":277,"license":237,"plugin":300},{"mcpCount":8,"provider":282,"skillCount":301},14,{"parentExtensionId":260,"repoId":284},[296,293,297,211,295,294,214],{"evaluatedAt":305,"extractAt":288,"updatedAt":305},1778694291902,{"evaluate":307,"extract":309},{"promptVersionExtension":204,"promptVersionScoring":205,"score":208,"tags":308,"targetMarket":216,"tier":217},[211,212,213,214,215],{"commitSha":277},{"parentExtensionId":249,"repoId":284},{"_creationTime":312,"_id":284,"identity":313,"providers":314,"workflow":623},1778694264629.3296,{"githubOwner":244,"githubRepo":245,"sourceUrl":14},{"classify":315,"discover":617,"github":620},{"commitSha":277,"extensions":316},[317,330,338,365,388,409,423,441,457,469,481,490,502,514,525,537,547,559,571,585,599,607],{"basePath":256,"description":263,"displayName":279,"installMethods":318,"rationale":319,"selectedPaths":320,"source":329,"sourceLanguage":18,"type":266},{"claudeCode":12},"marketplace.json at .claude-plugin/marketplace.json",[321,324,326],{"path":322,"priority":323},".claude-plugin/marketplace.json","mandatory",{"path":325,"priority":323},"README.md",{"path":327,"priority":328},"LICENSE","high","rule",{"basePath":256,"description":252,"displayName":211,"installMethods":331,"rationale":332,"selectedPaths":333,"source":329,"sourceLanguage":18,"type":257},{"claudeCode":245},"inline plugin source from marketplace.json at / (coalesced with duplicate plugin at .plugin)",[334,335,336],{"path":325,"priority":323},{"path":327,"priority":328},{"path":337,"priority":328},"SKILL.md",{"basePath":339,"description":340,"displayName":341,"installMethods":342,"rationale":343,"selectedPaths":344,"source":329,"sourceLanguage":18,"type":246},"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",[345,346,347,350,352,354,356,359,361,363],{"path":337,"priority":323},{"path":325,"priority":328},{"path":348,"priority":349},"examples/gertrude-stein/README.md","low",{"path":351,"priority":349},"examples/gertrude-stein/dataset_sample.jsonl",{"path":353,"priority":349},"examples/gertrude-stein/sample_outputs.md",{"path":355,"priority":349},"examples/gertrude-stein/training_config.json",{"path":357,"priority":358},"references/segmentation-strategies.md","medium",{"path":360,"priority":358},"references/tinker-format.md",{"path":362,"priority":358},"references/tinker.txt",{"path":364,"priority":349},"scripts/pipeline_example.py",{"basePath":366,"description":367,"displayName":368,"installMethods":369,"rationale":370,"selectedPaths":371,"source":329,"sourceLanguage":18,"type":246},"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",[372,373,374,376,378,380,382,384,386],{"path":337,"priority":323},{"path":325,"priority":328},{"path":375,"priority":358},"AGENT.md",{"path":377,"priority":358},"HOW-SKILLS-BUILT-THIS.md",{"path":379,"priority":358},"SKILLS-MAPPING.md",{"path":381,"priority":349},"examples/content-workflow.md",{"path":383,"priority":349},"examples/meeting-prep.md",{"path":385,"priority":358},"references/file-formats.md",{"path":387,"priority":349},"scripts/install.sh",{"basePath":389,"description":390,"displayName":391,"installMethods":392,"rationale":393,"selectedPaths":394,"source":329,"sourceLanguage":18,"type":246},"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",[395,396,397,399,401,403,405,407],{"path":337,"priority":323},{"path":325,"priority":328},{"path":398,"priority":349},"docs/agentthinking.md",{"path":400,"priority":349},"docs/interleavedthinking.md",{"path":402,"priority":349},"docs/m2-1.md",{"path":404,"priority":349},"examples/01_basic_capture.py",{"path":406,"priority":349},"examples/02_tool_usage.py",{"path":408,"priority":349},"examples/03_full_optimization.py",{"basePath":410,"description":411,"displayName":412,"installMethods":413,"rationale":414,"selectedPaths":415,"source":329,"sourceLanguage":18,"type":246},"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",[416,417,419,421],{"path":337,"priority":323},{"path":418,"priority":358},"references/optimization_summary.json",{"path":420,"priority":358},"references/optimized_prompt.txt",{"path":422,"priority":358},"references/patterns_found.json",{"basePath":424,"description":425,"displayName":426,"installMethods":427,"rationale":428,"selectedPaths":429,"source":329,"sourceLanguage":18,"type":246},"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",[430,431,433,435,437,439],{"path":337,"priority":323},{"path":432,"priority":358},"references/bias-mitigation.md",{"path":434,"priority":358},"references/evaluation-pipeline.md",{"path":436,"priority":358},"references/implementation-patterns.md",{"path":438,"priority":358},"references/metrics-guide.md",{"path":440,"priority":349},"scripts/evaluation_example.py",{"basePath":442,"description":443,"displayName":444,"installMethods":445,"rationale":446,"selectedPaths":447,"source":329,"sourceLanguage":18,"type":246},"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",[448,449,451,453,455],{"path":337,"priority":323},{"path":450,"priority":358},"references/bdi-ontology-core.md",{"path":452,"priority":358},"references/framework-integration.md",{"path":454,"priority":358},"references/rdf-examples.md",{"path":456,"priority":358},"references/sparql-competency.md",{"basePath":458,"description":459,"displayName":460,"installMethods":461,"rationale":462,"selectedPaths":463,"source":329,"sourceLanguage":18,"type":246},"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",[464,465,467],{"path":337,"priority":323},{"path":466,"priority":358},"references/evaluation-framework.md",{"path":468,"priority":349},"scripts/compression_evaluator.py",{"basePath":470,"description":471,"displayName":472,"installMethods":473,"rationale":474,"selectedPaths":475,"source":329,"sourceLanguage":18,"type":246},"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",[476,477,479],{"path":337,"priority":323},{"path":478,"priority":358},"references/patterns.md",{"path":480,"priority":349},"scripts/degradation_detector.py",{"basePath":243,"description":10,"displayName":13,"installMethods":482,"rationale":483,"selectedPaths":484,"source":329,"sourceLanguage":18,"type":246},{"claudeCode":12},"SKILL.md frontmatter at skills/context-fundamentals/SKILL.md",[485,486,488],{"path":337,"priority":323},{"path":487,"priority":358},"references/context-components.md",{"path":489,"priority":349},"scripts/context_manager.py",{"basePath":491,"description":492,"displayName":493,"installMethods":494,"rationale":495,"selectedPaths":496,"source":329,"sourceLanguage":18,"type":246},"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",[497,498,500],{"path":337,"priority":323},{"path":499,"priority":358},"references/optimization_techniques.md",{"path":501,"priority":349},"scripts/compaction.py",{"basePath":503,"description":504,"displayName":505,"installMethods":506,"rationale":507,"selectedPaths":508,"source":329,"sourceLanguage":18,"type":246},"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",[509,510,512],{"path":337,"priority":323},{"path":511,"priority":358},"references/metrics.md",{"path":513,"priority":349},"scripts/evaluator.py",{"basePath":515,"description":516,"displayName":517,"installMethods":518,"rationale":519,"selectedPaths":520,"source":329,"sourceLanguage":18,"type":246},"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",[521,522,523],{"path":337,"priority":323},{"path":436,"priority":358},{"path":524,"priority":349},"scripts/filesystem_context.py",{"basePath":526,"description":527,"displayName":528,"installMethods":529,"rationale":530,"selectedPaths":531,"source":329,"sourceLanguage":18,"type":246},"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",[532,533,535],{"path":337,"priority":323},{"path":534,"priority":358},"references/infrastructure-patterns.md",{"path":536,"priority":349},"scripts/sandbox_manager.py",{"basePath":538,"description":539,"displayName":540,"installMethods":541,"rationale":542,"selectedPaths":543,"source":329,"sourceLanguage":18,"type":246},"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",[544,545],{"path":337,"priority":323},{"path":546,"priority":358},"references/attention-matching-formulation.md",{"basePath":548,"description":549,"displayName":550,"installMethods":551,"rationale":552,"selectedPaths":553,"source":329,"sourceLanguage":18,"type":246},"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",[554,555,557],{"path":337,"priority":323},{"path":556,"priority":358},"references/implementation.md",{"path":558,"priority":349},"scripts/memory_store.py",{"basePath":560,"description":561,"displayName":562,"installMethods":563,"rationale":564,"selectedPaths":565,"source":329,"sourceLanguage":18,"type":246},"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",[566,567,569],{"path":337,"priority":323},{"path":568,"priority":358},"references/frameworks.md",{"path":570,"priority":349},"scripts/coordination.py",{"basePath":572,"description":573,"displayName":574,"installMethods":575,"rationale":576,"selectedPaths":577,"source":329,"sourceLanguage":18,"type":246},"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",[578,579,581,583],{"path":337,"priority":323},{"path":580,"priority":358},"references/case-studies.md",{"path":582,"priority":358},"references/pipeline-patterns.md",{"path":584,"priority":349},"scripts/pipeline_template.py",{"basePath":586,"description":587,"displayName":588,"installMethods":589,"rationale":590,"selectedPaths":591,"source":329,"sourceLanguage":18,"type":246},"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",[592,593,595,597],{"path":337,"priority":323},{"path":594,"priority":358},"references/architectural_reduction.md",{"path":596,"priority":358},"references/best_practices.md",{"path":598,"priority":349},"scripts/description_generator.py",{"basePath":600,"description":601,"displayName":602,"installMethods":603,"rationale":604,"selectedPaths":605,"source":329,"sourceLanguage":18,"type":246},"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",[606],{"path":337,"priority":323},{"basePath":389,"installMethods":608,"rationale":609,"selectedPaths":610,"source":329,"sourceLanguage":18,"type":616},{"pypi":391},"cli ecosystem detected at examples/interleaved-thinking",[611,613,614],{"path":612,"priority":323},"pyproject.toml",{"path":325,"priority":323},{"path":615,"priority":358},"reasoning_trace_optimizer/cli.py","cli",{"sources":618},[619],"manual",{"closedIssues90d":231,"description":621,"forks":232,"license":237,"openIssues90d":233,"pushedAt":234,"readmeSize":229,"stars":235,"topics":622},"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":624,"discoverAt":625,"extractAt":626,"githubAt":626,"updatedAt":624},1778694268713,1778694264629,1778694266904,[213,211,215,212,214],{"evaluatedAt":241,"extractAt":288,"updatedAt":241},[],[631,651,679,707,725,755],{"_creationTime":632,"_id":633,"community":634,"display":635,"identity":638,"providers":639,"relations":647,"tags":648,"workflow":649},1778694269038.6682,"k1752cypc448mke749yjbkc65186mg6f",{"reviewCount":8},{"description":459,"installMethods":636,"name":637,"sourceUrl":14},{"claudeCode":12},"Context Compression",{"basePath":458,"githubOwner":244,"githubRepo":245,"locale":18,"slug":460,"type":246},{"evaluate":640,"extract":646},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":642,"targetMarket":216,"tier":298},100,[211,212,643,644,645,505],"agent","summarization","compression",{"commitSha":277,"license":237},{"parentExtensionId":249,"repoId":284},[643,645,211,505,212,644],{"evaluatedAt":650,"extractAt":288,"updatedAt":650},1778694410149,{"_creationTime":652,"_id":653,"community":654,"display":655,"identity":661,"providers":666,"relations":673,"tags":675,"workflow":676},1778687399826.0247,"k173skx1fvkafn38prsv2d0qbh86nn4h",{"reviewCount":8},{"description":656,"installMethods":657,"name":659,"sourceUrl":660},"Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.",{"claudeCode":658},"github/awesome-copilot","Arize Prompt Optimization","https://github.com/github/awesome-copilot",{"basePath":662,"githubOwner":663,"githubRepo":664,"locale":18,"slug":665,"type":246},"skills/arize-prompt-optimization","github","awesome-copilot","arize-prompt-optimization",{"evaluate":667,"extract":672},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":668,"targetMarket":216,"tier":298},[212,214,669,670,616,671],"optimization","arize","data-analysis",{"commitSha":277,"license":237},{"repoId":674},"kd7dsmv976w8rtkqnjjfdtfgks86nnmw",[670,616,671,212,669,214],{"evaluatedAt":677,"extractAt":678,"updatedAt":677},1778689257343,1778687399826,{"_creationTime":680,"_id":681,"community":682,"display":683,"identity":689,"providers":694,"relations":699,"tags":702,"workflow":703},1778675791860.845,"k174f2y3jxg9senxnc66r7j6dx86md8y",{"reviewCount":8},{"description":684,"installMethods":685,"name":687,"sourceUrl":688},"应用提示重复以提高非推理 LLM 的准确性",{"claudeCode":686},"asklokesh/loki-mode","prompt-optimization","https://github.com/asklokesh/loki-mode",{"basePath":690,"githubOwner":691,"githubRepo":692,"locale":693,"slug":687,"type":246},"agent-skills/prompt-optimization","asklokesh","loki-mode","zh-CN",{"evaluate":695,"extract":698},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":696,"targetMarket":216,"tier":298},[212,214,697,669],"accuracy",{"commitSha":277},{"repoId":700,"translatedFrom":701},"kd7dy44r49793jt8bt02wdezk586nxsn","k17bjgfyvbnt05kpma9n0gn4j186n152",[697,212,669,214],{"evaluatedAt":704,"extractAt":705,"updatedAt":706},1778675713014,1778675659559,1778675791860,{"_creationTime":708,"_id":709,"community":710,"display":711,"identity":713,"providers":714,"relations":721,"tags":722,"workflow":723},1778694269038.669,"k171pshmgmyv8he1yhep1nkths86mr39",{"reviewCount":8},{"description":492,"installMethods":712,"name":493,"sourceUrl":14},{"claudeCode":12},{"basePath":491,"githubOwner":244,"githubRepo":245,"locale":18,"slug":493,"type":246},{"evaluate":715,"extract":720},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":716,"targetMarket":216,"tier":298},[211,687,717,718,719],"llm-efficiency","kv-cache","token-reduction",{"commitSha":277},{"parentExtensionId":249,"repoId":284},[211,718,717,687,719],{"evaluatedAt":724,"extractAt":288,"updatedAt":724},1778694467379,{"_creationTime":726,"_id":727,"community":728,"display":729,"identity":735,"providers":739,"relations":747,"tags":750,"workflow":751},1778693194037.0615,"k1725ztgj00fgjtk0mf35stgjd86mnpc",{"reviewCount":8},{"description":730,"installMethods":731,"name":733,"sourceUrl":734},"创建或优化存储库的 AGENTS.md 文件，提供最少、高信号的说明，涵盖代理无法从代码库推断的不可发现的编码约定、工具怪癖、工作流偏好和项目特定规则。在为新存储库设置代理说明或 Claude 配置时，当现有的 AGENTS.md 文件过长、通用或过时，当代理反复犯可避免的错误，或当存储库工作流发生变化且需要修剪代理配置时使用。应用可发现性过滤器—省略 Claude 可从 README、代码、配置或目录结构中学到的任何内容—并应用质量门，以验证每行是否仍然准确且具有操作意义。",{"claudeCode":732},"mcollina/skills","init","https://github.com/mcollina/skills",{"basePath":736,"githubOwner":737,"githubRepo":738,"locale":693,"slug":733,"type":246},"skills/init","mcollina","skills",{"evaluate":740,"extract":746},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":741,"targetMarket":216,"tier":298},[742,743,211,744,745],"initialization","agents","agents-md","maintenance",{"commitSha":277},{"repoId":748,"translatedFrom":749},"kd7e22d93dm7xdjcrsgq33f53d86mqm7","k17e8fgrjhgk34vzyxq9phbaad86m56g",[743,744,211,742,745],{"evaluatedAt":752,"extractAt":753,"updatedAt":754},1778692978251,1778692906303,1778693194037,{"_creationTime":756,"_id":757,"community":758,"display":759,"identity":765,"providers":769,"relations":778,"tags":781,"workflow":782},1778695548458.4048,"k17e5nn93syzxrybh3he9fz5eh86nbme",{"reviewCount":8},{"description":760,"installMethods":761,"name":763,"sourceUrl":764},"Guide a person in becoming a better teacher and explainer. AI coaches content structuring, audience calibration, explanation clarity, Socratic questioning technique, feedback interpretation, and reflective practice for technical presentations, documentation, and mentoring. Use when a person needs to present technical content and wants preparation coaching, wants to write better documentation or tutorials, struggles to explain concepts across expertise levels, is mentoring a colleague, or is preparing for a talk or knowledge-sharing session.\n",{"claudeCode":762},"pjt222/agent-almanac","teach-guidance","https://github.com/pjt222/agent-almanac",{"basePath":766,"githubOwner":767,"githubRepo":768,"locale":18,"slug":763,"type":246},"skills/teach-guidance","pjt222","agent-almanac",{"evaluate":770,"extract":777},{"promptVersionExtension":204,"promptVersionScoring":205,"score":641,"tags":771,"targetMarket":216,"tier":298},[772,773,774,215,775,776],"teaching","coaching","presentation","explanation","guidance",{"commitSha":277},{"parentExtensionId":779,"repoId":780},"k170h0janaa9kwn7cfgfz2ykss86mmh9","kd7aryv63z61j39n2td1aeqkvh86mh12",[773,215,775,776,774,772],{"evaluatedAt":783,"extractAt":784,"updatedAt":783},1778701952682,1778695548458]