[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-lllllllama-minimal-run-and-audit-zh-CN":3,"guides-for-lllllllama-minimal-run-and-audit":505,"similar-k1745c75pw18shtjfgm186w7zn86mb7q-zh-CN":506},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":244,"isFallback":229,"parentExtension":249,"providers":250,"relations":256,"repo":259,"tags":501,"workflow":502},1778692707070.0664,"k1745c75pw18shtjfgm186w7zn86mb7q",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"用于 README 优先的 AI 代码库进行可信执行和报告的技能。当任务是专门从选定的 smoke test 或已文档化的推理或评估命令捕获或标准化证据，并写入标准化的 `repro_outputs/` 文件（包括在存储库文件更改时生成补丁说明）时使用。请勿用于训练执行、初始代码库引入、通用环境设置、论文查找、目标选择或单独的端到端编排。",{"claudeCode":12},"lllllllama/ai-paper-reproduction-skill","minimal-run-and-audit","https://github.com/lllllllama/ai-paper-reproduction-skill",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":227,"workflow":242},1778692707070.0667,"kn7eyc0gxmgejy429btw9q2e9x86mg5w","zh-CN",{"checks":20,"evaluatedAt":195,"extensionSummary":196,"features":197,"nonGoals":203,"promptVersionExtension":209,"promptVersionScoring":210,"purpose":211,"rationale":212,"score":213,"summary":214,"tags":215,"tier":221,"useCases":222},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,113,116,120,123,126,129,132,135,138,142,146,150,153,157,160,163,166,169,173,176,179,182,185,188,192],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","描述清楚地说明了从 README 复现 AI 研究工件的问题，并指出了目标用户（维护 AI 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中进行了文档化。",{"category":33,"check":49,"severity":24,"summary":50},"Tool naming","主入口点命名良好（`minimal-run-and-audit`），其关联脚本（`run_command.py`）对其功能具有描述性。",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","脚本 `run_command.py` 捕获与目的相关的特定执行详细信息（返回码、stdout、stderr、文件更改），而不过度进行诊断转储。",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","该存储库根据 MIT 许可证授权，这是一个宽松的开源许可证，并在 LICENSE 文件中明确标明。",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","最近的提交发生在 2026 年 5 月 9 日，在过去 90 天内，表明维护活跃。",{"category":59,"check":63,"severity":42,"summary":64},"Dependency Management","提供的脚本似乎使用了标准的 Python 库和 git，没有需要复杂管理的显式第三方依赖项。",{"category":66,"check":67,"severity":24,"summary":68},"Security","Secret Management","脚本 `run_command.py` 在代码库上下文中执行提供的命令，并且似乎不处理或暴露秘密。",{"category":66,"check":70,"severity":24,"summary":71},"Injection","脚本 `run_command.py` 使用 `shlex.split` 解析命令，并使用 subprocess 执行它们，从而减轻了直接注入的风险。Git 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Use when the user wants an end-to-end, minimal-trustworthy reproduction flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, or broad research assistance outside repository-grounded reproduction.","ai-research-reproduction",{"claudeCode":12},"SKILL.md frontmatter at skills/ai-research-reproduction/SKILL.md",[350,351,353,355,357,359,361,363,365,367,369,371],{"path":273,"priority":274},{"path":352,"priority":290},"assets/COMMANDS.template.md",{"path":354,"priority":290},"assets/LOG.template.md",{"path":356,"priority":290},"assets/PATCHES.template.md",{"path":358,"priority":290},"assets/SUMMARY.template.md",{"path":360,"priority":290},"assets/status.template.json",{"path":362,"priority":277},"references/architecture.md",{"path":364,"priority":277},"references/language-policy.md",{"path":366,"priority":277},"references/output-spec.md",{"path":368,"priority":277},"references/patch-policy.md",{"path":370,"priority":277},"references/research-safety-principles.md",{"path":372,"priority":290},"scripts/orchestrate_repro.py",{"basePath":374,"description":375,"displayName":376,"installMethods":377,"rationale":378,"selectedPaths":379,"source":341,"sourceLanguage":342,"type":248},"skills/analyze-project","Trusted-lane analysis skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.","analyze-project",{"claudeCode":12},"SKILL.md frontmatter at skills/analyze-project/SKILL.md",[380,381,383],{"path":273,"priority":274},{"path":382,"priority":277},"references/analysis-policy.md",{"path":384,"priority":290},"scripts/analyze_project.py",{"basePath":386,"description":387,"displayName":388,"installMethods":389,"rationale":390,"selectedPaths":391,"source":341,"sourceLanguage":342,"type":248},"skills/env-and-assets-bootstrap","Environment and assets sub-skill for README-first AI repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.","env-and-assets-bootstrap",{"claudeCode":12},"SKILL.md frontmatter at skills/env-and-assets-bootstrap/SKILL.md",[392,393,395,397,399,401,403],{"path":273,"priority":274},{"path":394,"priority":277},"references/assets-policy.md",{"path":396,"priority":277},"references/env-policy.md",{"path":398,"priority":290},"scripts/bootstrap_env.py",{"path":400,"priority":290},"scripts/bootstrap_env.sh",{"path":402,"priority":290},"scripts/plan_setup.py",{"path":404,"priority":290},"scripts/prepare_assets.py",{"basePath":406,"description":407,"displayName":408,"installMethods":409,"rationale":410,"selectedPaths":411,"source":341,"sourceLanguage":342,"type":248},"skills/explore-code","Explore-lane code adaptation skill for deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together low-risk migration ideas with summary-only records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, or default repository analysis.","explore-code",{"claudeCode":12},"SKILL.md frontmatter at skills/explore-code/SKILL.md",[412,413,415,417],{"path":273,"priority":274},{"path":414,"priority":277},"references/explore-policy.md",{"path":416,"priority":290},"scripts/plan_code_changes.py",{"path":340,"priority":290},{"basePath":419,"description":420,"displayName":421,"installMethods":422,"rationale":423,"selectedPaths":424,"source":341,"sourceLanguage":342,"type":248},"skills/explore-run","Explore-lane experimental execution skill for deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with results summarized in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, or implicit experimentation.","explore-run",{"claudeCode":12},"SKILL.md frontmatter at skills/explore-run/SKILL.md",[425,426,428,430],{"path":273,"priority":274},{"path":427,"priority":277},"references/execution-policy.md",{"path":429,"priority":290},"scripts/plan_variants.py",{"path":340,"priority":290},{"basePath":245,"description":432,"displayName":13,"installMethods":433,"rationale":434,"selectedPaths":435,"source":341,"sourceLanguage":342,"type":248},"Trusted-lane execution and reporting skill for README-first AI repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, or end-to-end orchestration by itself.",{"claudeCode":12},"SKILL.md frontmatter at skills/minimal-run-and-audit/SKILL.md",[436,437,439,441],{"path":273,"priority":274},{"path":438,"priority":277},"references/reporting-policy.md",{"path":440,"priority":290},"scripts/run_command.py",{"path":340,"priority":290},{"basePath":443,"description":444,"displayName":445,"installMethods":446,"rationale":447,"selectedPaths":448,"source":341,"sourceLanguage":342,"type":248},"skills/paper-context-resolver","Optional narrow helper skill for README-first AI repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.","paper-context-resolver",{"claudeCode":12},"SKILL.md frontmatter at skills/paper-context-resolver/SKILL.md",[449,450],{"path":273,"priority":274},{"path":451,"priority":277},"references/paper-assisted-reproduction.md",{"basePath":453,"description":454,"displayName":455,"installMethods":456,"rationale":457,"selectedPaths":458,"source":341,"sourceLanguage":342,"type":248},"skills/repo-intake-and-plan","Narrow helper skill for README-first AI repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.","repo-intake-and-plan",{"claudeCode":12},"SKILL.md frontmatter at skills/repo-intake-and-plan/SKILL.md",[459,460,462,464],{"path":273,"priority":274},{"path":461,"priority":277},"references/repo-scan-rules.md",{"path":463,"priority":290},"scripts/extract_commands.py",{"path":465,"priority":290},"scripts/scan_repo.py",{"basePath":467,"description":468,"displayName":469,"installMethods":470,"rationale":471,"selectedPaths":472,"source":341,"sourceLanguage":342,"type":248},"skills/run-train","Trusted-lane training execution skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with status, checkpoint, and metric capture written to standardized `train_outputs/`. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.","run-train",{"claudeCode":12},"SKILL.md frontmatter at skills/run-train/SKILL.md",[473,474,476,478],{"path":273,"priority":274},{"path":475,"priority":277},"references/training-policy.md",{"path":477,"priority":290},"scripts/run_training.py",{"path":340,"priority":290},{"basePath":480,"description":481,"displayName":482,"installMethods":483,"rationale":484,"selectedPaths":485,"source":341,"sourceLanguage":342,"type":248},"skills/safe-debug","Trusted-lane debug skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.","safe-debug",{"claudeCode":12},"SKILL.md frontmatter at skills/safe-debug/SKILL.md",[486,487,489],{"path":273,"priority":274},{"path":488,"priority":277},"references/debug-policy.md",{"path":490,"priority":290},"scripts/safe_debug.py",{"sources":492},[493],"manual",{"closedIssues90d":8,"description":495,"forks":235,"license":240,"openIssues90d":8,"pushedAt":237,"readmeSize":233,"stars":238,"topics":496},"",[],{"classifiedAt":498,"discoverAt":499,"extractAt":500,"githubAt":500,"updatedAt":498},1778692395631,1778692391648,1778692393876,[219,220,218,216,217],{"evaluatedAt":503,"extractAt":504,"updatedAt":243},1778692567369,1778692396032,[],[507,541,571,600,627,656],{"_creationTime":508,"_id":509,"community":510,"display":511,"identity":517,"providers":522,"relations":532,"tags":536,"workflow":537},1778693811536.0796,"k17d38avrb81ktefmtwcx0302186nv5b",{"reviewCount":8},{"description":512,"installMethods":513,"name":515,"sourceUrl":516},"从 GitHub 更新 context-mode 并修复 hooks/settings。\n拉取最新代码，构建，安装，更新 npm 全局包，配置 hooks。\n触发器：/context-mode:ctx-upgrade\n",{"claudeCode":514},"mksglu/context-mode","Context Mode","https://github.com/mksglu/context-mode",{"basePath":518,"githubOwner":519,"githubRepo":520,"locale":18,"slug":521,"type":248},"skills/ctx-upgrade","mksglu","context-mode","ctx-upgrade",{"evaluate":523,"extract":530},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":524,"targetMarket":253,"tier":221},[525,526,219,527,528,529],"context-management","llm-ops","session-continuity","productivity","mcp",{"commitSha":255,"license":531},"NOASSERTION",{"parentExtensionId":533,"repoId":534,"translatedFrom":535},"k17ezy748es7sfnbnp9phht43h86m53y","kd764b2fctbqg4b8j8y6xvmkvs86m29m","k17fqs996gpd2bggec9k1qbbns86nh4g",[219,525,526,529,528,527],{"evaluatedAt":538,"extractAt":539,"updatedAt":540},1778693713738,1778693511416,1778693811536,{"_creationTime":542,"_id":543,"community":544,"display":545,"identity":551,"providers":556,"relations":565,"tags":567,"workflow":568},1778696691708.3035,"k17br1j5s86ae90zqeyd7zcg2586mkwr",{"reviewCount":8},{"description":546,"installMethods":547,"name":549,"sourceUrl":550},"Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms\n",{"claudeCode":548},"ruvnet/ruflo","Performance Analysis","https://github.com/ruvnet/ruflo",{"basePath":552,"githubOwner":553,"githubRepo":554,"locale":342,"slug":555,"type":248},".claude/skills/performance-analysis","ruvnet","ruflo","performance-analysis",{"evaluate":557,"extract":564},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":558,"targetMarket":253,"tier":221},[559,560,561,562,563,218],"performance","analysis","optimization","claude-flow","bottleneck-detection",{"commitSha":255,"license":240},{"repoId":566},"kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[560,563,562,561,559,218],{"evaluatedAt":569,"extractAt":570,"updatedAt":569},1778699217174,1778696691708,{"_creationTime":572,"_id":573,"community":574,"display":575,"identity":581,"providers":585,"relations":593,"tags":596,"workflow":597},1778698144006.2202,"k172517ana4f5vj79mb22xzwsx86mksv",{"reviewCount":8},{"description":576,"installMethods":577,"name":579,"sourceUrl":580},"Audit and consolidate HubSpot reporting dashboards. Identifies unused, duplicate, or outdated dashboards. Must be performed manually — no dashboard API is available.",{"claudeCode":578},"TomGranot/hubspot-admin-skills","cleanup-dashboards","https://github.com/TomGranot/hubspot-admin-skills",{"basePath":582,"githubOwner":583,"githubRepo":584,"locale":342,"slug":579,"type":248},"skills/cleanup-dashboards","TomGranot","hubspot-admin-skills",{"evaluate":586,"extract":592},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":587,"targetMarket":253,"tier":221},[588,589,590,218,591],"hubspot","crm","maintenance","cleanup",{"commitSha":255},{"parentExtensionId":594,"repoId":595},"k17c3p8t0thc73pbc8egtz31y986mwr0","kd75kpec7arn6z2wz641vfaj8n86nab6",[591,589,588,590,218],{"evaluatedAt":598,"extractAt":599,"updatedAt":598},1778698268281,1778698144006,{"_creationTime":601,"_id":602,"community":603,"display":604,"identity":610,"providers":614,"relations":620,"tags":623,"workflow":624},1778694480889.9524,"k17cem4hc58gq77dezte6rz8mx86nkpf",{"reviewCount":8},{"description":605,"installMethods":606,"name":608,"sourceUrl":609},"Display the current state of the FPF knowledge base",{"claudeCode":607},"NeoLabHQ/context-engineering-kit","status","https://github.com/NeoLabHQ/context-engineering-kit",{"basePath":611,"githubOwner":612,"githubRepo":613,"locale":342,"slug":608,"type":248},"plugins/fpf/skills/status","NeoLabHQ","context-engineering-kit",{"evaluate":615,"extract":619},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":616,"targetMarket":253,"tier":221},[617,608,218,618],"knowledge-base","fpf",{"commitSha":255},{"parentExtensionId":621,"repoId":622},"k170dd9j7raacsjs3ta67k8cw986m50s","kd7a3rj13ezgx1wgm0jfh08hsx86n0sz",[618,617,218,608],{"evaluatedAt":625,"extractAt":626,"updatedAt":625},1778695034738,1778694480890,{"_creationTime":628,"_id":629,"community":630,"display":631,"identity":637,"providers":641,"relations":649,"tags":652,"workflow":653},1778692726926.7627,"k17dhmskz6t7wpxvd9ygy7fvsh86n695",{"reviewCount":8},{"description":632,"installMethods":633,"name":635,"sourceUrl":636},"End-of-quarter strategic review in narrative style with a bets scorecard. Use when someone says \"quarter review\", \"strategic review\", \"what happened last quarter\", \"quarterly retro\", \"bets scorecard\", \"review our bets\", \"end of quarter report\".\n",{"claudeCode":634},"marfoerst/the-pragmatic-pm","pm-strategic-review","https://github.com/marfoerst/the-pragmatic-pm",{"basePath":638,"githubOwner":639,"githubRepo":640,"locale":342,"slug":635,"type":248},"skills/pm-strategic-review","marfoerst","the-pragmatic-pm",{"evaluate":642,"extract":648},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":643,"targetMarket":253,"tier":221},[644,645,218,646,647],"product-management","strategy","review","scorecard",{"commitSha":255},{"parentExtensionId":650,"repoId":651},"k17ehawghqbe3ff7rxmq9cq1xs86nm21","kd731k864fr1ezp8r85ecbhz9986mzz7",[644,218,646,647,645],{"evaluatedAt":654,"extractAt":655,"updatedAt":654},1778693621016,1778692726926,{"_creationTime":657,"_id":658,"community":659,"display":660,"identity":666,"providers":670,"relations":679,"tags":682,"workflow":683},1778692306427.1023,"k17f0vqhj9x3ee4773kq2m8fph86n5ct",{"reviewCount":8},{"description":661,"installMethods":662,"name":664,"sourceUrl":665},"Revenue and costs tracker. AWS spend via aws ce, credits tracker, project revenue stages. Shows burn rate, runway estimate, credits expiring.",{"claudeCode":663},"Lifecycle-Innovations-Limited/claude-ops","ops-revenue","https://github.com/Lifecycle-Innovations-Limited/claude-ops",{"basePath":667,"githubOwner":668,"githubRepo":669,"locale":342,"slug":664,"type":248},"claude-ops/skills/ops-revenue","Lifecycle-Innovations-Limited","claude-ops",{"evaluate":671,"extract":678},{"promptVersionExtension":209,"promptVersionScoring":210,"score":213,"tags":672,"targetMarket":253,"tier":221},[673,674,675,676,218,677],"finance","aws","cost-tracking","revenue","dashboard",{"commitSha":255},{"parentExtensionId":680,"repoId":681},"k17d0t6ns7y6t377pfprg128hd86nm89","kd7d52tcek2e34r805zs06b10d86n39v",[674,675,677,673,218,676],{"evaluatedAt":684,"extractAt":685,"updatedAt":684},1778692873720,1778692306427]