[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-lllllllama-safe-debug-de":3,"guides-for-lllllllama-safe-debug":501,"similar-k17c3ck7krn096k417s4pb2bwn86nsgs-de":502},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":240,"isFallback":225,"parentExtension":245,"providers":246,"relations":252,"repo":255,"tags":497,"workflow":498},1778692747074.0698,"k17c3ck7krn096k417s4pb2bwn86nsgs",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Vertrauenswürdiger Debugging-Skill für die Deep-Learning-Forschungsarbeit. Verwenden Sie ihn, wenn der Benutzer einen Traceback, einen Terminalfehler, einen CUDA OOM, ein fehlgeschlagenes Laden eines Checkpoints, eine Shape-Fehlübereinstimmung, ein NaN-Loss-Symptom oder ein Trainingsversagen einfügt und eine konservative Diagnose vor jeglicher Fehlerbehebung wünscht. Nicht für allgemeine Refaktorierungen, spekulative Anpassungen, automatisches exploratives Patchen oder allgemeine Repository-Vertrautheit verwenden.",{"claudeCode":12},"lllllllama/ai-paper-reproduction-skill","safe-debug","https://github.com/lllllllama/ai-paper-reproduction-skill",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":223,"workflow":238},1778692747074.07,"kn75s6s0thvn5eawekf6edakqd86mtpd","de",{"checks":20,"evaluatedAt":191,"extensionSummary":192,"features":193,"nonGoals":199,"promptVersionExtension":204,"promptVersionScoring":205,"purpose":206,"rationale":207,"score":208,"summary":209,"tags":210,"tier":216,"useCases":217},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,114,117,121,124,127,130,133,136,139,143,147,150,153,157,160,163,166,169,173,176,179,182,185,188],{"category":22,"check":23,"severity":24,"summary":25},"Praktischer Nutzen","Relevanz des Problems","pass","Die Beschreibung nennt klar das Problem des Debuggens von Fehlern in der Deep-Learning-Forschung und erwähnt speziell Tracebacks, OOM-Fehler und Trainingsfehler, was einen konkreten Schwachpunkt darstellt.",{"category":22,"check":27,"severity":24,"summary":28},"Einzigartiges Verkaufsargument","Der Skill bietet einen konservativen, genehmigungsbasierten Debugging-Workflow, der über eine einfache LLM-Analyse hinausgeht, indem er Sicherheit, Diagnose vor dem Patchen und minimale Modifikationen betont und einen Mehrwert gegenüber direkter LLM-Interaktion bietet.",{"category":22,"check":30,"severity":24,"summary":31},"Produktionsreife","Der Skill ist für die Forschung-Fehlersuche konzipiert und bietet Diagnose- und Patch-Vorschläge mit expliziten Genehmigungsgates, die den vollständigen Diagnoselebenszyklus abdecken.",{"category":33,"check":34,"severity":24,"summary":35},"Umfang","Prinzip der einzigen Verantwortung","Der Skill konzentriert sich ausschließlich auf das konservative Debuggen von Fehlern in der Deep-Learning-Forschung, wie sein Name, seine Beschreibung und seine expliziten Nicht-Ziele anzeigen.",{"category":33,"check":37,"severity":24,"summary":38},"Qualität der Beschreibung","Die Beschreibung spiegelt genau den Zweck des Skills wider, eine konservative Diagnose für Fehler in der Deep-Learning-Forschung bereitzustellen, und umreißt klar seine Nutzungseinschränkungen.",{"category":40,"check":41,"severity":42,"summary":43},"Aufruf","Abgegrenzte Werkzeuge","not_applicable","Dieser Skill stellt keine Werkzeuge im traditionellen Sinne bereit; es handelt sich um ein monolithisches Skript, das eine bestimmte Aufgabe bearbeitet.",{"category":45,"check":46,"severity":24,"summary":47},"Dokumentation","Konfigurations- & Parameterreferenz","Die Kommandozeilenargumente des Skripts für Eingabe von Fehlern und Ausgabeverzeichnis sind dokumentiert und Standardwerte sind angegeben.",{"category":33,"check":49,"severity":42,"summary":50},"Werkzeugbenennung","Der Skill stellt keine mehreren Werkzeuge mit benutzersichtbaren Namen bereit.",{"category":33,"check":52,"severity":24,"summary":53},"Minimale I/O-Oberfläche","Das Skript akzeptiert Fehlertext oder einen Dateipfad und gibt Diagnose und Patch-Plan aus, ohne unnötige Informationen.",{"category":55,"check":56,"severity":24,"summary":57},"Lizenz","Lizenznutzbarkeit","Das Repository enthält eine Standard-MIT-Lizenzdatei.",{"category":59,"check":60,"severity":24,"summary":61},"Wartung","Aktualität des Commits","Der letzte Commit war am 9. Mai 2026, was innerhalb der letzten 90 Tage liegt.",{"category":59,"check":63,"severity":42,"summary":64},"Abhängigkeitsmanagement","Das Python-Skript des Skills hat keine externen Abhängigkeiten außer der Standardbibliothek.",{"category":66,"check":67,"severity":24,"summary":68},"Sicherheit","Geheimnisverwaltung","Der Skill verarbeitet oder exponiert keine Geheimnisse; er analysiert nur den bereitgestellten Fehlertext.",{"category":66,"check":70,"severity":24,"summary":71},"Injektion","Der Skill analysiert bereitgestellten Text und führt keinen externen Code aus oder lädt keine nicht vertrauenswürdigen Daten.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Lieferketten-Granaten","Der Skill verarbeitet nur lokale Texteingaben und ruft zur Laufzeit keine externen Inhalte ab.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox-Isolation","Das Skript schreibt nur in ein angegebenes Ausgabeverzeichnis und modifiziert keine Dateien außerhalb davon.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox-Escape-Primitive","Das Skript enthält keine abgekoppelten Prozessstarts oder keine Retry-Schleifen.",{"category":66,"check":82,"severity":24,"summary":83},"Datenexfiltration","Der Skill analysiert nur lokale Eingaben und führt keine ausgehenden Netzwerkaufrufe durch.",{"category":66,"check":85,"severity":24,"summary":86},"Versteckte Texttricks","Das gebündelte Skript und die Markdown-Dateien enthalten keine versteckten Texttricks oder bösartigen Unicode-Zeichen.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opake Codeausführung","Das Python-Skript ist einfacher, lesbarer Quellcode und verwendet keine Obskurationstechniken.",{"category":92,"check":93,"severity":24,"summary":94},"Portabilität","Strukturelle Annahme","Das Skript trifft keine Annahmen über die Projektstruktur des Benutzers, sondern benötigt nur eine Fehler-Eingabe und ein Ausgabeverzeichnis.",{"category":96,"check":97,"severity":24,"summary":98},"Vertrauen","Aufmerksamkeit für Issues","Es gibt 0 offene und 0 geschlossene Issues in den letzten 90 Tagen, was keine recente Aktivität oder Probleme anzeigt.",{"category":100,"check":101,"severity":24,"summary":102},"Versionierung","Release-Management","Das Repository hat einen aktuellen Commit (2026-05-09) und eine MIT-Lizenzdatei, was auf aktive Wartung und klare Lizenzierung hinweist.",{"category":104,"check":105,"severity":24,"summary":106},"Ausführung","Validierung","Eingabeargumente werden mit argparse geparst und der Fehlertest wird zur Klassifizierung verarbeitet.",{"category":66,"check":108,"severity":24,"summary":109},"Ungeschützte destruktive Operationen","Der Skill ist in seiner Operation schreibgeschützt und analysiert nur bereitgestellten Text und schreibt in ein Ausgabeverzeichnis.",{"category":111,"check":112,"severity":24,"summary":113},"Codeausführung","Fehlerbehandlung","Das Skript behandelt potenzielle Fehler wie fehlende Eingabedateien und verfügt über eine strukturierte Fehlerklassifizierung und -ausgabe.",{"category":111,"check":115,"severity":42,"summary":116},"Protokollierung","Der Skill ist schreibgeschützt und führt keine destruktiven Aktionen oder ausgehenden Aufrufe durch, die eine lokale Audit-Protokollierung erfordern würden.",{"category":118,"check":119,"severity":24,"summary":120},"Compliance","DSGVO","Der Skill analysiert nur bereitgestellten Fehlertext und verarbeitet keine personenbezogenen Daten.",{"category":118,"check":122,"severity":24,"summary":123},"Zielmarkt","Der Skill ist ein allgemeines Debugging-Werkzeug ohne regionale oder gerichtliche Logik, was ihn global anwendbar macht.",{"category":92,"check":125,"severity":24,"summary":126},"Laufzeitstabilität","Das Skript verwendet Standard-Python-3-Funktionen und argparse, was es portabel auf POSIX-ähnlichen und Windows-Umgebungen macht.",{"category":45,"check":128,"severity":24,"summary":129},"README","Die README-Datei existiert und bietet einen umfassenden Überblick über die Skills des Repositorys, Installation und Nutzung.",{"category":33,"check":131,"severity":42,"summary":132},"Größe der Werkzeugoberfläche","Dies ist ein einzelner Skill ohne exponierte Werkzeuge oder Befehle über sein primäres Skript hinaus.",{"category":40,"check":134,"severity":42,"summary":135},"Überlappende, fast synonyme Werkzeuge","Der Skill ist eine einzelne Einheit und exponiert keine mehreren Werkzeuge mit überlappender Funktionalität.",{"category":45,"check":137,"severity":24,"summary":138},"Phantom-Features","Alle im README und SKILL.md beschriebenen Features sind in den bereitgestellten Skripten implementiert.",{"category":140,"check":141,"severity":24,"summary":142},"Installation","Installationsanleitung","Das README bietet klare `npx`-Installationsanweisungen und Beispielaufrufe für die Verwendung des `safe-debug`-Skills.",{"category":144,"check":145,"severity":24,"summary":146},"Fehler","Handlungsfähige Fehlermeldungen","Das Skript bietet strukturierte Fehlerklassifizierung, vorgeschlagene Aktionen und klare Ausgabedateien für Diagnose und Patching.",{"category":104,"check":148,"severity":24,"summary":149},"Angepinnte Abhängigkeiten","Das Skript verwendet nur die Standardbibliothek von Python und stützt sich nicht auf externe Abhängigkeiten, die angepinnt oder gesperrt werden müssten.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-Run-Vorschau","Der Skill ist rein analytisch und führt keine zustandsverändernden Operationen oder ausgehenden Datenversand durch.",{"category":154,"check":155,"severity":42,"summary":156},"Protokoll","Idempotente Wiederholung & Timeouts","Der Skill arbeitet mit lokalen Eingaben und hat keine Remote-Aufrufe oder zustandsverändernden Operationen, die Idempotenz oder Timeouts erfordern würden.",{"category":118,"check":158,"severity":24,"summary":159},"Telemetrie-Opt-in","Der Skill sendet keine Telemetrie.",{"category":40,"check":161,"severity":24,"summary":162},"Präziser Zweck","Der Zweck des Skills ist präzise definiert, indem angegeben wird, dass er für das Debuggen von Deep-Learning-Forschung bestimmt ist, wann er verwendet werden soll (Tracebacks, OOM) und wann nicht (Refactoring, Exploration).",{"category":40,"check":164,"severity":24,"summary":165},"Prägnante Frontmatter","Die SKILL.md Frontmatter ist prägnant und gibt klar den Zweck des Skills an und liefert Auslöserphrasen innerhalb einer angemessenen Zeichenbegrenzung.",{"category":45,"check":167,"severity":24,"summary":168},"Prägnanter Textteil","Der SKILL.md Textteil ist prägnant und umreißt die Funktionsprinzipien und Notizen, wobei tiefergehende Materialien an referenzierte Dateien delegiert werden.",{"category":170,"check":171,"severity":24,"summary":172},"Kontext","Progressive Offenlegung","Die SKILL.md verweist auf externe Dateien wie `references/agent-operating-principles.md` und `references/debug-policy.md`, was eine progressive Offenlegung zeigt.",{"category":170,"check":174,"severity":42,"summary":175},"Gabelnde Exploration","Dieser Skill konzentriert sich auf Analyse und Diagnose, nicht auf tiefe Exploration oder Code-Überprüfung, daher ist `context: fork` nicht anwendbar.",{"category":22,"check":177,"severity":24,"summary":178},"Nutzungsbeispiele","Das README liefert klare Beispiel-Prompts für die Verwendung des `safe-debug`-Skills und demonstriert seine vorgesehene Verwendung.",{"category":22,"check":180,"severity":24,"summary":181},"Randfälle","Das Skript behandelt verschiedene Fehlerkategorien und schlägt Wiederherstellungsmaßnahmen vor, wodurch potenzielle Fehlerfälle angegangen werden.",{"category":111,"check":183,"severity":42,"summary":184},"Werkzeug-Fallback","Der Skill stützt sich nicht auf externe Werkzeuge wie MCP-Server und verwendet nur Standard-Python-Bibliotheken.",{"category":66,"check":186,"severity":24,"summary":187},"Halten bei unerwartetem Zustand","Die Klassifizierungslogik und Fehlerbehandlung des Skripts stellen sicher, dass es anhält und berichtet, wenn die Eingabe unerwartet ist oder nicht klassifiziert werden kann.",{"category":92,"check":189,"severity":24,"summary":190},"Querverbindung von Skills","Der `safe-debug`-Skill arbeitet unabhängig und ist nicht auf die gleichzeitige Ausführung anderer Skills angewiesen.",1778692636337,"Dieser Skill fungiert als vertrauenswürdige Lane für die Fehlersuche bei Deep-Learning-Forschungsproblemen. Er analysiert bereitgestellte Fehlermeldungen, Tracebacks oder Symptome, um die Ursachen zu identifizieren und konservative, minimale Korrekturen vorzuschlagen, die vor jeglicher Codeänderung explizit vom Benutzer genehmigt werden müssen.",[194,195,196,197,198],"Konservative Fehlerdiagnose für DL-Forschungsfehler","Klassifiziert Fehler in Kategorien (CUDA OOM, Checkpoint-Fehlanpassung usw.)","Schlägt minimale, sichere Korrekturen und Wiederherstellungsschritte vor","Erfordert explizite Benutzergenehmigung vor dem Patchen von Code","Gibt detaillierte Diagnose- und Patch-Pläne aus",[200,201,202,203],"Durchführung breiter Repository-Refactorings","Automatisches exploratives Patchen","Allgemeine Repository-Vertrautheit ohne Symptome eines Fehlers","Spekulative Codeanpassung","3.0.0","4.4.0","Ein sicheres und konservatives Debugging-Erlebnis für die Deep-Learning-Forschung zu bieten, um sicherzustellen, dass Diagnosen gründlich sind und alle vorgeschlagenen Codeänderungen minimal und explizit genehmigt werden.","Der Skill ist außergewöhnlich gut dokumentiert und robust, mit klarem Zweck, Nutzung und Sicherheitsfunktionen. Er erfüllt seine spezialisierte Debugging-Aufgabe effektiv und konservativ. Der einzige kleine Punkt ist das Fehlen eines expliziten `context: fork`, was hier nicht zutreffend ist.",99,"Ein qualitativ hochwertiger, sicherer und gut dokumentierter Skill zur Diagnose von Fehlern in der Deep-Learning-Forschung.",[211,212,213,214,215],"debugging","deep-learning","research","error-analysis","troubleshooting","verified",[218,219,220,221,222],"Diagnose von CUDA Out Of Memory-Fehlern","Analyse von Fehlern beim Laden von Checkpoints","Fehlersuche bei Shape-Fehlübereinstimmungen in Modell-Tensoren","Untersuchung von NaN-Loss-Symptomen während des Trainings","Verständnis von Terminalfehlern und Tracebacks",{"codeQuality":224,"collectedAt":226,"documentation":227,"maintenance":230,"security":235,"testCoverage":237},{"hasLockfile":225},false,1778692621031,{"descriptionLength":228,"readmeSize":229},383,22701,{"closedIssues90d":8,"forks":231,"hasChangelog":232,"openIssues90d":8,"pushedAt":233,"stars":234},4,true,1778347974000,75,{"hasNpmPackage":225,"license":236,"smitheryVerified":225},"MIT",{"hasCi":232,"hasTests":232},{"updatedAt":239},1778692747074,{"basePath":241,"githubOwner":242,"githubRepo":243,"locale":18,"slug":13,"type":244},"skills/safe-debug","lllllllama","ai-paper-reproduction-skill","skill",null,{"evaluate":247,"extract":250},{"promptVersionExtension":204,"promptVersionScoring":205,"score":208,"tags":248,"targetMarket":249,"tier":216},[211,212,213,214,215],"global",{"commitSha":251},"HEAD",{"repoId":253,"translatedFrom":254},"kd7629v5mqesxwwe9w7qtfgp7d86n6re","k179dznar9vdfw1akjwqm4081186nxj2",{"_creationTime":256,"_id":253,"identity":257,"providers":258,"workflow":493},1778692391648.3123,{"githubOwner":242,"githubRepo":243,"sourceUrl":14},{"classify":259,"discover":487,"github":490},{"commitSha":251,"extensions":260},[261,339,369,381,401,414,427,440,450,464,477],{"basePath":262,"description":263,"displayName":264,"installMethods":265,"rationale":266,"selectedPaths":267,"source":337,"sourceLanguage":338,"type":244},"skills/ai-research-explore","Explore-lane end-to-end orchestrator for the third research scenario: the researcher has already chosen the task family, dataset, benchmark, evaluation method, and provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, or implicit experimentation.","ai-research-explore",{"claudeCode":12},"SKILL.md frontmatter at skills/ai-research-explore/SKILL.md",[268,271,274,276,278,280,282,284,287,289,291,293,295,297,299,301,303,305,307,309,311,313,315,317,319,321,323,325,327,329,331,333,335],{"path":269,"priority":270},"SKILL.md","mandatory",{"path":272,"priority":273},"references/ai-research-explore-policy.md","medium",{"path":275,"priority":273},"references/idea-evaluation-framework.md",{"path":277,"priority":273},"references/research-campaign-spec.md",{"path":279,"priority":273},"references/smoke-validation-policy.md",{"path":281,"priority":273},"references/source-mapping-policy.md",{"path":283,"priority":273},"references/sources-naming-policy.md",{"path":285,"priority":286},"scripts/lookup/__init__.py","low",{"path":288,"priority":286},"scripts/lookup/cache_store.py",{"path":290,"priority":286},"scripts/lookup/inventory_writer.py",{"path":292,"priority":286},"scripts/lookup/normalizers.py",{"path":294,"priority":286},"scripts/lookup/providers/__init__.py",{"path":296,"priority":286},"scripts/lookup/providers/arxiv_provider.py",{"path":298,"priority":286},"scripts/lookup/providers/base.py",{"path":300,"priority":286},"scripts/lookup/providers/doi_provider.py",{"path":302,"priority":286},"scripts/lookup/providers/github_provider.py",{"path":304,"priority":286},"scripts/lookup/providers/optional_provider.py",{"path":306,"priority":286},"scripts/lookup/providers/url_provider.py",{"path":308,"priority":286},"scripts/lookup/record_schema.py",{"path":310,"priority":286},"scripts/lookup/repo_extractors.py",{"path":312,"priority":286},"scripts/lookup/source_support.py",{"path":314,"priority":286},"scripts/orchestrate_explore.py",{"path":316,"priority":286},"scripts/passes/__init__.py",{"path":318,"priority":286},"scripts/passes/atomic_idea_decomposition.py",{"path":320,"priority":286},"scripts/passes/candidate_idea_generation.py",{"path":322,"priority":286},"scripts/passes/execution_feasibility.py",{"path":324,"priority":286},"scripts/passes/idea_cards.py",{"path":326,"priority":286},"scripts/passes/idea_ranking.py",{"path":328,"priority":286},"scripts/passes/implementation_fidelity.py",{"path":330,"priority":286},"scripts/passes/improvement_bank.py",{"path":332,"priority":286},"scripts/passes/lookup_sources.py",{"path":334,"priority":286},"scripts/passes/source_mapping.py",{"path":336,"priority":286},"scripts/write_outputs.py","rule","en",{"basePath":340,"description":341,"displayName":342,"installMethods":343,"rationale":344,"selectedPaths":345,"source":337,"sourceLanguage":338,"type":244},"skills/ai-research-reproduction","Main orchestrator for README-first AI repo reproduction. 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",[346,347,349,351,353,355,357,359,361,363,365,367],{"path":269,"priority":270},{"path":348,"priority":286},"assets/COMMANDS.template.md",{"path":350,"priority":286},"assets/LOG.template.md",{"path":352,"priority":286},"assets/PATCHES.template.md",{"path":354,"priority":286},"assets/SUMMARY.template.md",{"path":356,"priority":286},"assets/status.template.json",{"path":358,"priority":273},"references/architecture.md",{"path":360,"priority":273},"references/language-policy.md",{"path":362,"priority":273},"references/output-spec.md",{"path":364,"priority":273},"references/patch-policy.md",{"path":366,"priority":273},"references/research-safety-principles.md",{"path":368,"priority":286},"scripts/orchestrate_repro.py",{"basePath":370,"description":371,"displayName":372,"installMethods":373,"rationale":374,"selectedPaths":375,"source":337,"sourceLanguage":338,"type":244},"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",[376,377,379],{"path":269,"priority":270},{"path":378,"priority":273},"references/analysis-policy.md",{"path":380,"priority":286},"scripts/analyze_project.py",{"basePath":382,"description":383,"displayName":384,"installMethods":385,"rationale":386,"selectedPaths":387,"source":337,"sourceLanguage":338,"type":244},"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",[388,389,391,393,395,397,399],{"path":269,"priority":270},{"path":390,"priority":273},"references/assets-policy.md",{"path":392,"priority":273},"references/env-policy.md",{"path":394,"priority":286},"scripts/bootstrap_env.py",{"path":396,"priority":286},"scripts/bootstrap_env.sh",{"path":398,"priority":286},"scripts/plan_setup.py",{"path":400,"priority":286},"scripts/prepare_assets.py",{"basePath":402,"description":403,"displayName":404,"installMethods":405,"rationale":406,"selectedPaths":407,"source":337,"sourceLanguage":338,"type":244},"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",[408,409,411,413],{"path":269,"priority":270},{"path":410,"priority":273},"references/explore-policy.md",{"path":412,"priority":286},"scripts/plan_code_changes.py",{"path":336,"priority":286},{"basePath":415,"description":416,"displayName":417,"installMethods":418,"rationale":419,"selectedPaths":420,"source":337,"sourceLanguage":338,"type":244},"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",[421,422,424,426],{"path":269,"priority":270},{"path":423,"priority":273},"references/execution-policy.md",{"path":425,"priority":286},"scripts/plan_variants.py",{"path":336,"priority":286},{"basePath":428,"description":429,"displayName":430,"installMethods":431,"rationale":432,"selectedPaths":433,"source":337,"sourceLanguage":338,"type":244},"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",[434,435,437,439],{"path":269,"priority":270},{"path":436,"priority":273},"references/reporting-policy.md",{"path":438,"priority":286},"scripts/run_command.py",{"path":336,"priority":286},{"basePath":441,"description":442,"displayName":443,"installMethods":444,"rationale":445,"selectedPaths":446,"source":337,"sourceLanguage":338,"type":244},"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",[447,448],{"path":269,"priority":270},{"path":449,"priority":273},"references/paper-assisted-reproduction.md",{"basePath":451,"description":452,"displayName":453,"installMethods":454,"rationale":455,"selectedPaths":456,"source":337,"sourceLanguage":338,"type":244},"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",[457,458,460,462],{"path":269,"priority":270},{"path":459,"priority":273},"references/repo-scan-rules.md",{"path":461,"priority":286},"scripts/extract_commands.py",{"path":463,"priority":286},"scripts/scan_repo.py",{"basePath":465,"description":466,"displayName":467,"installMethods":468,"rationale":469,"selectedPaths":470,"source":337,"sourceLanguage":338,"type":244},"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",[471,472,474,476],{"path":269,"priority":270},{"path":473,"priority":273},"references/training-policy.md",{"path":475,"priority":286},"scripts/run_training.py",{"path":336,"priority":286},{"basePath":241,"description":478,"displayName":13,"installMethods":479,"rationale":480,"selectedPaths":481,"source":337,"sourceLanguage":338,"type":244},"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",[482,483,485],{"path":269,"priority":270},{"path":484,"priority":273},"references/debug-policy.md",{"path":486,"priority":286},"scripts/safe_debug.py",{"sources":488},[489],"manual",{"closedIssues90d":8,"description":491,"forks":231,"license":236,"openIssues90d":8,"pushedAt":233,"readmeSize":229,"stars":234,"topics":492},"",[],{"classifiedAt":494,"discoverAt":495,"extractAt":496,"githubAt":496,"updatedAt":494},1778692395631,1778692391648,1778692393876,[211,212,214,213,215],{"evaluatedAt":499,"extractAt":500,"updatedAt":239},1778692636476,1778692396032,[],[503,531,562,582,611,641],{"_creationTime":504,"_id":505,"community":506,"display":507,"identity":513,"providers":517,"relations":523,"tags":526,"workflow":527},1778692960518.947,"k1726cxg3j2a07dk7jqjrq807986ms6e",{"reviewCount":8},{"description":508,"installMethods":509,"name":511,"sourceUrl":512},"Post-hoc-Diagnose von fehlgeschlagenen Agenten-Trajektorien. Klassifiziert den ersten nicht behebbaren Schritt in eine von neun Fehlerkategorien (Plan-Konformität, halluzinierte Informationen, ungültiger Tool-Aufruf, falsch gelesener Tool-Output, Absicht-Plan-Fehlanpassung, unzureichend spezifizierte Absicht, nicht unterstützte Absicht, Auslösen von Schutzmaßnahmen, Systemfehler) und erstellt einen beweisgestützten Bericht über die Grundursache.",{"claudeCode":510},"majiayu000/vibeguard","trajectory-review","https://github.com/majiayu000/vibeguard",{"basePath":514,"githubOwner":515,"githubRepo":516,"locale":18,"slug":511,"type":244},"skills/trajectory-review","majiayu000","vibeguard",{"evaluate":518,"extract":522},{"promptVersionExtension":204,"promptVersionScoring":205,"score":208,"tags":519,"targetMarket":249,"tier":216},[211,215,520,214,521],"agent-performance","trajectory-analysis",{"commitSha":251},{"repoId":524,"translatedFrom":525},"kd7b0vh258xpbyerk68bk3e1ks86mk58","k1797wq7825nd9yhz5q538asgn86nq05",[520,211,214,521,215],{"evaluatedAt":528,"extractAt":529,"updatedAt":530},1778692729089,1778692607327,1778692960519,{"_creationTime":532,"_id":533,"community":534,"display":535,"identity":541,"providers":546,"relations":556,"tags":558,"workflow":559},1778697652123.895,"k179x649dvyg7xswjx2h5a199n86m32x",{"reviewCount":8},{"description":536,"installMethods":537,"name":539,"sourceUrl":540},"Diagnose OpenClaw Android, iOS, or macOS node pairing, QR/setup code, route, auth, and connection failures.",{"claudeCode":538},"steipete/clawdis","Node Connect","https://github.com/steipete/clawdis",{"basePath":542,"githubOwner":543,"githubRepo":544,"locale":338,"slug":545,"type":244},"skills/node-connect","steipete","clawdis","node-connect",{"evaluate":547,"extract":555},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":549,"targetMarket":249,"tier":216},100,[211,550,551,552,553,215,554],"networking","android","ios","macos","openclaws",{"commitSha":251,"license":236},{"repoId":557},"kd738npxg9yh3xf3vddzy9fyfh86nhng",[551,211,552,553,550,554,215],{"evaluatedAt":560,"extractAt":561,"updatedAt":560},1778698735523,1778697652123,{"_creationTime":563,"_id":564,"community":565,"display":566,"identity":570,"providers":572,"relations":578,"tags":579,"workflow":580},1778697652123.8813,"k175pymk0vm7xrcjj2p0jf904186nae7",{"reviewCount":8},{"description":567,"installMethods":568,"name":569,"sourceUrl":540},"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":538},"openclaw-debugging",{"basePath":571,"githubOwner":543,"githubRepo":544,"locale":338,"slug":569,"type":244},".agents/skills/openclaw-debugging",{"evaluate":573,"extract":577},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":574,"targetMarket":249,"tier":216},[211,554,575,215,576],"cli","development",{"commitSha":251},{"repoId":557},[575,211,576,554,215],{"evaluatedAt":581,"extractAt":561,"updatedAt":581},1778697754713,{"_creationTime":583,"_id":584,"community":585,"display":586,"identity":592,"providers":597,"relations":605,"tags":607,"workflow":608},1778683190010.284,"k1757t8mrzzrf8yabxrtp82mg586m6nf",{"reviewCount":8},{"description":587,"installMethods":588,"name":590,"sourceUrl":591},"Systematic debugging methodology emphasizing root cause analysis over quick fixes",{"claudeCode":589},"bobmatnyc/claude-mpm-skills","Systematic Debugging","https://github.com/bobmatnyc/claude-mpm-skills",{"basePath":593,"githubOwner":594,"githubRepo":595,"locale":338,"slug":596,"type":244},"universal/debugging/systematic-debugging","bobmatnyc","claude-mpm-skills","systematic-debugging",{"evaluate":598,"extract":603},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":599,"targetMarket":249,"tier":216},[211,215,600,601,602],"root-cause-analysis","methodology","problem-solving",{"commitSha":251,"license":604},"Apache-2.0",{"repoId":606},"kd72g55e5qeqs90bk1bvkt8wbx86nkn3",[211,601,602,600,215],{"evaluatedAt":609,"extractAt":610,"updatedAt":609},1778686304588,1778683190010,{"_creationTime":612,"_id":613,"community":614,"display":615,"identity":620,"providers":624,"relations":632,"tags":636,"workflow":637},1778684076699.9136,"k178ee2hp7d9knjarhk35h425x86nhab",{"reviewCount":8},{"description":616,"installMethods":617,"name":215,"sourceUrl":619},"Verwendet Chrome DevTools MCP und Dokumentation zur Fehlerbehebung bei Verbindungs- und Zielproblemen. Rufen Sie diese Fähigkeit auf, wenn list_pages, new_page oder navigate_page fehlschlagen oder wenn die Serverinitialisierung fehlschlägt.",{"claudeCode":618},"ChromeDevTools/chrome-devtools-mcp","https://github.com/ChromeDevTools/chrome-devtools-mcp",{"basePath":621,"githubOwner":622,"githubRepo":623,"locale":18,"slug":215,"type":244},"skills/troubleshooting","ChromeDevTools","chrome-devtools-mcp",{"evaluate":625,"extract":631},{"promptVersionExtension":204,"promptVersionScoring":205,"score":548,"tags":626,"targetMarket":249,"tier":216},[627,628,215,211,629,630],"devtools","chrome","automation","mcp",{"commitSha":251},{"parentExtensionId":633,"repoId":634,"translatedFrom":635},"k17evynnzmmag96rw4rpybyydx86m0py","kd7an8ppnz1q2np9tc5yw4qenn86mg6h","k1709q7z5grftph7kb93c569qh86n56a",[629,628,211,627,630,215],{"evaluatedAt":638,"extractAt":639,"updatedAt":640},1778683958622,1778683762612,1778684076699,{"_creationTime":642,"_id":643,"community":644,"display":645,"identity":651,"providers":655,"relations":662,"tags":665,"workflow":666},1778694480889.9556,"k17cw5h9amytcw2kg63ygtqqxn86nsp8",{"reviewCount":8},{"description":646,"installMethods":647,"name":649,"sourceUrl":650},"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":648},"NeoLabHQ/context-engineering-kit","root-cause-tracing","https://github.com/NeoLabHQ/context-engineering-kit",{"basePath":652,"githubOwner":653,"githubRepo":654,"locale":338,"slug":649,"type":244},"plugins/kaizen/skills/root-cause-tracing","NeoLabHQ","context-engineering-kit",{"evaluate":656,"extract":661},{"promptVersionExtension":204,"promptVersionScoring":205,"score":208,"tags":657,"targetMarket":249,"tier":216},[211,215,658,659,660],"code-analysis","developer-tools","call-stack",{"commitSha":251},{"parentExtensionId":663,"repoId":664},"k17884m6t3p8517a1d2zjp8zbd86n13x","kd7a3rj13ezgx1wgm0jfh08hsx86n0sz",[660,658,211,659,215],{"evaluatedAt":667,"extractAt":668,"updatedAt":667},1778695268236,1778694480890]