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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",[347,348,350,352,354,356,358,360,362,364,366,368],{"path":270,"priority":271},{"path":349,"priority":287},"assets/COMMANDS.template.md",{"path":351,"priority":287},"assets/LOG.template.md",{"path":353,"priority":287},"assets/PATCHES.template.md",{"path":355,"priority":287},"assets/SUMMARY.template.md",{"path":357,"priority":287},"assets/status.template.json",{"path":359,"priority":274},"references/architecture.md",{"path":361,"priority":274},"references/language-policy.md",{"path":363,"priority":274},"references/output-spec.md",{"path":365,"priority":274},"references/patch-policy.md",{"path":367,"priority":274},"references/research-safety-principles.md",{"path":369,"priority":287},"scripts/orchestrate_repro.py",{"basePath":371,"description":372,"displayName":373,"installMethods":374,"rationale":375,"selectedPaths":376,"source":338,"sourceLanguage":339,"type":245},"skills/analyze-project","Trusted-lane analysis skill for deep learning research repositories. 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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",[389,390,392,394,396,398,400],{"path":270,"priority":271},{"path":391,"priority":274},"references/assets-policy.md",{"path":393,"priority":274},"references/env-policy.md",{"path":395,"priority":287},"scripts/bootstrap_env.py",{"path":397,"priority":287},"scripts/bootstrap_env.sh",{"path":399,"priority":287},"scripts/plan_setup.py",{"path":401,"priority":287},"scripts/prepare_assets.py",{"basePath":403,"description":404,"displayName":405,"installMethods":406,"rationale":407,"selectedPaths":408,"source":338,"sourceLanguage":339,"type":245},"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",[409,410,412,414],{"path":270,"priority":271},{"path":411,"priority":274},"references/explore-policy.md",{"path":413,"priority":287},"scripts/plan_code_changes.py",{"path":337,"priority":287},{"basePath":416,"description":417,"displayName":418,"installMethods":419,"rationale":420,"selectedPaths":421,"source":338,"sourceLanguage":339,"type":245},"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",[422,423,425,427],{"path":270,"priority":271},{"path":424,"priority":274},"references/execution-policy.md",{"path":426,"priority":287},"scripts/plan_variants.py",{"path":337,"priority":287},{"basePath":429,"description":430,"displayName":431,"installMethods":432,"rationale":433,"selectedPaths":434,"source":338,"sourceLanguage":339,"type":245},"skills/minimal-run-and-audit","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.","minimal-run-and-audit",{"claudeCode":12},"SKILL.md frontmatter at skills/minimal-run-and-audit/SKILL.md",[435,436,438,440],{"path":270,"priority":271},{"path":437,"priority":274},"references/reporting-policy.md",{"path":439,"priority":287},"scripts/run_command.py",{"path":337,"priority":287},{"basePath":442,"description":443,"displayName":444,"installMethods":445,"rationale":446,"selectedPaths":447,"source":338,"sourceLanguage":339,"type":245},"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",[448,449],{"path":270,"priority":271},{"path":450,"priority":274},"references/paper-assisted-reproduction.md",{"basePath":452,"description":453,"displayName":454,"installMethods":455,"rationale":456,"selectedPaths":457,"source":338,"sourceLanguage":339,"type":245},"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",[458,459,461,463],{"path":270,"priority":271},{"path":460,"priority":274},"references/repo-scan-rules.md",{"path":462,"priority":287},"scripts/extract_commands.py",{"path":464,"priority":287},"scripts/scan_repo.py",{"basePath":466,"description":467,"displayName":468,"installMethods":469,"rationale":470,"selectedPaths":471,"source":338,"sourceLanguage":339,"type":245},"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",[472,473,475,477],{"path":270,"priority":271},{"path":474,"priority":274},"references/training-policy.md",{"path":476,"priority":287},"scripts/run_training.py",{"path":337,"priority":287},{"basePath":242,"description":479,"displayName":13,"installMethods":480,"rationale":481,"selectedPaths":482,"source":338,"sourceLanguage":339,"type":245},"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.",{"claudeCode":12},"SKILL.md frontmatter at skills/safe-debug/SKILL.md",[483,484,486],{"path":270,"priority":271},{"path":485,"priority":274},"references/debug-policy.md",{"path":487,"priority":287},"scripts/safe_debug.py",{"sources":489},[490],"manual",{"closedIssues90d":8,"description":492,"forks":232,"license":237,"openIssues90d":8,"pushedAt":234,"readmeSize":230,"stars":235,"topics":493},"",[],{"classifiedAt":495,"discoverAt":496,"extractAt":497,"githubAt":497,"updatedAt":495},1778692395631,1778692391648,1778692393876,[212,213,215,214,216],{"evaluatedAt":500,"extractAt":501,"updatedAt":240},1778692636476,1778692396032,[],[504,532,563,583,612,642],{"_creationTime":505,"_id":506,"community":507,"display":508,"identity":514,"providers":518,"relations":524,"tags":527,"workflow":528},1778692960723.3638,"k17c5vqzwrdc90g7jdcqg5m1nh86mgyy",{"reviewCount":8},{"description":509,"installMethods":510,"name":512,"sourceUrl":513},"对失败的代理轨迹进行事后诊断。将第一个无法恢复的步骤分类为九种失败类别之一（计划遵循性、幻觉信息、无效工具调用、误读工具输出、意图-计划不匹配、意图不明确、意图不支持、护栏触发、系统故障），并生成有证据支持的根本原因报告。",{"claudeCode":511},"majiayu000/vibeguard","trajectory-review","https://github.com/majiayu000/vibeguard",{"basePath":515,"githubOwner":516,"githubRepo":517,"locale":18,"slug":512,"type":245},"skills/trajectory-review","majiayu000","vibeguard",{"evaluate":519,"extract":523},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":520,"targetMarket":250,"tier":217},[212,216,521,215,522],"agent-performance","trajectory-analysis",{"commitSha":252},{"repoId":525,"translatedFrom":526},"kd7b0vh258xpbyerk68bk3e1ks86mk58","k1797wq7825nd9yhz5q538asgn86nq05",[521,212,215,522,216],{"evaluatedAt":529,"extractAt":530,"updatedAt":531},1778692729089,1778692607327,1778692960723,{"_creationTime":533,"_id":534,"community":535,"display":536,"identity":542,"providers":547,"relations":557,"tags":559,"workflow":560},1778697652123.895,"k179x649dvyg7xswjx2h5a199n86m32x",{"reviewCount":8},{"description":537,"installMethods":538,"name":540,"sourceUrl":541},"Diagnose OpenClaw Android, iOS, or macOS node pairing, QR/setup code, route, auth, and connection failures.",{"claudeCode":539},"steipete/clawdis","Node Connect","https://github.com/steipete/clawdis",{"basePath":543,"githubOwner":544,"githubRepo":545,"locale":339,"slug":546,"type":245},"skills/node-connect","steipete","clawdis","node-connect",{"evaluate":548,"extract":556},{"promptVersionExtension":205,"promptVersionScoring":206,"score":549,"tags":550,"targetMarket":250,"tier":217},100,[212,551,552,553,554,216,555],"networking","android","ios","macos","openclaws",{"commitSha":252,"license":237},{"repoId":558},"kd738npxg9yh3xf3vddzy9fyfh86nhng",[552,212,553,554,551,555,216],{"evaluatedAt":561,"extractAt":562,"updatedAt":561},1778698735523,1778697652123,{"_creationTime":564,"_id":565,"community":566,"display":567,"identity":571,"providers":573,"relations":579,"tags":580,"workflow":581},1778697652123.8813,"k175pymk0vm7xrcjj2p0jf904186nae7",{"reviewCount":8},{"description":568,"installMethods":569,"name":570,"sourceUrl":541},"Debug OpenClaw model, provider, tool-surface, code-mode, streaming, and live/Crabbox behavior by choosing the right logs, probes, and proof path before changing code.",{"claudeCode":539},"openclaw-debugging",{"basePath":572,"githubOwner":544,"githubRepo":545,"locale":339,"slug":570,"type":245},".agents/skills/openclaw-debugging",{"evaluate":574,"extract":578},{"promptVersionExtension":205,"promptVersionScoring":206,"score":549,"tags":575,"targetMarket":250,"tier":217},[212,555,576,216,577],"cli","development",{"commitSha":252},{"repoId":558},[576,212,577,555,216],{"evaluatedAt":582,"extractAt":562,"updatedAt":582},1778697754713,{"_creationTime":584,"_id":585,"community":586,"display":587,"identity":593,"providers":598,"relations":606,"tags":608,"workflow":609},1778683190010.284,"k1757t8mrzzrf8yabxrtp82mg586m6nf",{"reviewCount":8},{"description":588,"installMethods":589,"name":591,"sourceUrl":592},"Systematic debugging methodology emphasizing root cause analysis over quick fixes",{"claudeCode":590},"bobmatnyc/claude-mpm-skills","Systematic Debugging","https://github.com/bobmatnyc/claude-mpm-skills",{"basePath":594,"githubOwner":595,"githubRepo":596,"locale":339,"slug":597,"type":245},"universal/debugging/systematic-debugging","bobmatnyc","claude-mpm-skills","systematic-debugging",{"evaluate":599,"extract":604},{"promptVersionExtension":205,"promptVersionScoring":206,"score":549,"tags":600,"targetMarket":250,"tier":217},[212,216,601,602,603],"root-cause-analysis","methodology","problem-solving",{"commitSha":252,"license":605},"Apache-2.0",{"repoId":607},"kd72g55e5qeqs90bk1bvkt8wbx86nkn3",[212,602,603,601,216],{"evaluatedAt":610,"extractAt":611,"updatedAt":610},1778686304588,1778683190010,{"_creationTime":613,"_id":614,"community":615,"display":616,"identity":621,"providers":625,"relations":633,"tags":637,"workflow":638},1778684074950.4968,"k17a2p5tj2n738wj5cs7gerp2s86mvsp",{"reviewCount":8},{"description":617,"installMethods":618,"name":216,"sourceUrl":620},"使用 Chrome DevTools MCP 和文档来排查连接和目标问题。当 list_pages、new_page 或 navigate_page 失败，或服务器初始化失败时，触发此技能。",{"claudeCode":619},"ChromeDevTools/chrome-devtools-mcp","https://github.com/ChromeDevTools/chrome-devtools-mcp",{"basePath":622,"githubOwner":623,"githubRepo":624,"locale":18,"slug":216,"type":245},"skills/troubleshooting","ChromeDevTools","chrome-devtools-mcp",{"evaluate":626,"extract":632},{"promptVersionExtension":205,"promptVersionScoring":206,"score":549,"tags":627,"targetMarket":250,"tier":217},[628,629,216,212,630,631],"devtools","chrome","automation","mcp",{"commitSha":252},{"parentExtensionId":634,"repoId":635,"translatedFrom":636},"k17evynnzmmag96rw4rpybyydx86m0py","kd7an8ppnz1q2np9tc5yw4qenn86mg6h","k1709q7z5grftph7kb93c569qh86n56a",[630,629,212,628,631,216],{"evaluatedAt":639,"extractAt":640,"updatedAt":641},1778683958622,1778683762612,1778684074950,{"_creationTime":643,"_id":644,"community":645,"display":646,"identity":652,"providers":656,"relations":663,"tags":666,"workflow":667},1778694480889.9556,"k17cw5h9amytcw2kg63ygtqqxn86nsp8",{"reviewCount":8},{"description":647,"installMethods":648,"name":650,"sourceUrl":651},"Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior",{"claudeCode":649},"NeoLabHQ/context-engineering-kit","root-cause-tracing","https://github.com/NeoLabHQ/context-engineering-kit",{"basePath":653,"githubOwner":654,"githubRepo":655,"locale":339,"slug":650,"type":245},"plugins/kaizen/skills/root-cause-tracing","NeoLabHQ","context-engineering-kit",{"evaluate":657,"extract":662},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":658,"targetMarket":250,"tier":217},[212,216,659,660,661],"code-analysis","developer-tools","call-stack",{"commitSha":252},{"parentExtensionId":664,"repoId":665},"k17884m6t3p8517a1d2zjp8zbd86n13x","kd7a3rj13ezgx1wgm0jfh08hsx86n0sz",[661,659,212,660,216],{"evaluatedAt":668,"extractAt":669,"updatedAt":668},1778695268236,1778694480890]