[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-lllllllama-safe-debug-en":3,"guides-for-lllllllama-safe-debug":499,"similar-k179dznar9vdfw1akjwqm4081186nxj2-en":500},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":242,"isFallback":227,"parentExtension":247,"providers":248,"relations":253,"repo":255,"tags":495,"workflow":496},1778692396032.779,"k179dznar9vdfw1akjwqm4081186nxj2",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"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},"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":225,"workflow":240},1778692636476.5193,"kn7bgp55zp96vzkztt623d0ew586nyaw","en",{"checks":20,"evaluatedAt":192,"extensionSummary":193,"features":194,"nonGoals":200,"promptVersionExtension":205,"promptVersionScoring":206,"purpose":207,"rationale":208,"score":209,"summary":210,"tags":211,"targetMarket":217,"tier":218,"useCases":219},[21,26,29,32,36,39,44,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,114,117,121,124,127,130,133,136,139,143,147,150,153,157,160,163,166,169,173,176,179,182,185,189],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","The description clearly states the problem of debugging deep learning research failures, specifically mentioning tracebacks, OOM errors, and training failures, which is a concrete pain point.",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","The skill offers a conservative, approval-based debugging workflow that goes beyond a simple LLM analysis by emphasizing safety, diagnosis before patching, and minimal modifications, providing value over direct LLM interaction.",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","The skill is designed for research debugging, providing diagnosis and patch suggestions with explicit approval gates, covering the complete diagnostic lifecycle.",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","The skill focuses solely on conservative debugging of deep learning research errors, as indicated by its name, description, and explicit non-goals.",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","The description accurately reflects the skill's purpose of providing conservative diagnosis for deep learning research errors and clearly outlines its usage constraints.",{"category":40,"check":41,"severity":42,"summary":43},"Invocation","Scoped tools","not_applicable","This skill does not expose tools in the traditional sense; it is a monolithic script that handles a specific task.",{"category":45,"check":46,"severity":24,"summary":47},"Documentation","Configuration & parameter reference","The script's command-line arguments for error input and output directory are documented, and defaults are provided.",{"category":33,"check":49,"severity":42,"summary":50},"Tool naming","The skill does not expose multiple tools with user-facing names.",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","The script accepts error text or a file path and outputs diagnosis, patch plan, and status, with no extraneous information.",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","The repository includes a standard MIT license file.",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","The latest commit was on May 9, 2026, which is within the last 90 days.",{"category":59,"check":63,"severity":42,"summary":64},"Dependency Management","The skill's Python script has no external dependencies beyond the standard library.",{"category":66,"check":67,"severity":24,"summary":68},"Security","Secret Management","The skill does not handle or expose secrets; it only analyzes provided error text.",{"category":66,"check":70,"severity":24,"summary":71},"Injection","The skill analyzes provided text and does not execute any external code or load untrusted data.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","The skill only processes local text input and does not fetch external content at runtime.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","The script only writes to a specified output directory and does not modify files outside of it.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","The script does not contain any detached process spawns or deny-retry loops.",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","The skill only analyzes local input and does not make any outbound network calls.",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","The bundled script and markdown files do not contain hidden text tricks or malicious Unicode characters.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","The Python script is plain, readable source code and does not use obfuscation techniques.",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","The script makes no assumptions about the user's project structure, only requiring an error input and an output directory.",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","There are 0 issues opened and 0 closed in the last 90 days, indicating no recent activity or issues.",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","The repository has a recent commit (2026-05-09) and a MIT license file, indicating active maintenance and clear licensing.",{"category":104,"check":105,"severity":24,"summary":106},"Execution","Validation","Input arguments are parsed using argparse, and the error text is processed for classification.",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","The skill is read-only in its operation, only analyzing provided text and writing to an output directory.",{"category":111,"check":112,"severity":24,"summary":113},"Code Execution","Error Handling","The script handles potential errors like missing input files and has structured error classification and output.",{"category":111,"check":115,"severity":42,"summary":116},"Logging","The skill is read-only and does not perform destructive actions or outbound calls that would require local audit logging.",{"category":118,"check":119,"severity":24,"summary":120},"Compliance","GDPR","The skill only analyzes provided error text and does not operate on personal data.",{"category":118,"check":122,"severity":24,"summary":123},"Target market","The skill is a general debugging tool with no regional or jurisdictional logic, making it globally applicable.",{"category":92,"check":125,"severity":24,"summary":126},"Runtime stability","The script uses standard Python 3 features and argparse, making it portable across POSIX-like and Windows environments.",{"category":45,"check":128,"severity":24,"summary":129},"README","The README file exists and provides a comprehensive overview of the repository's skills, installation, and usage.",{"category":33,"check":131,"severity":42,"summary":132},"Tool surface size","This is a single-function skill with no exposed tools or commands beyond its primary script.",{"category":40,"check":134,"severity":42,"summary":135},"Overlapping near-synonym tools","The skill is a single unit and does not expose multiple tools with overlapping functionality.",{"category":45,"check":137,"severity":24,"summary":138},"Phantom features","All features described in the README and SKILL.md are implemented in the provided scripts.",{"category":140,"check":141,"severity":24,"summary":142},"Install","Installation instruction","The README provides clear `npx` installation instructions and example invocations for calling the `safe-debug` skill.",{"category":144,"check":145,"severity":24,"summary":146},"Errors","Actionable error messages","The script provides structured error classification, suggested actions, and clear output files for diagnosis and patching.",{"category":104,"check":148,"severity":24,"summary":149},"Pinned dependencies","The script uses only Python's standard library and does not rely on external dependencies that would require pinning or lockfiles.",{"category":33,"check":151,"severity":42,"summary":152},"Dry-run preview","The skill is purely analytical and does not perform any state-changing operations or outbound data sending.",{"category":154,"check":155,"severity":42,"summary":156},"Protocol","Idempotent retry & timeouts","The skill operates on local input and has no remote calls or state-changing operations that would require idempotency or timeouts.",{"category":118,"check":158,"severity":24,"summary":159},"Telemetry opt-in","The skill does not emit any telemetry.",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","The skill's purpose is precisely defined, stating it's for deep learning research debugging, specifying when to use it (tracebacks, OOM) and when not to (refactoring, exploration).",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","The SKILL.md frontmatter is concise, clearly stating the skill's purpose and providing trigger phrases within a reasonable character limit.",{"category":45,"check":167,"severity":24,"summary":168},"Concise Body","The SKILL.md body is concise, outlining operating principles and notes, delegating deeper material to referenced files.",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","The SKILL.md references external files like `references/agent-operating-principles.md` and `references/debug-policy.md`, demonstrating progressive disclosure.",{"category":170,"check":174,"severity":42,"summary":175},"Forked exploration","This skill is focused on analysis and diagnosis, not deep exploration or code review, so `context: fork` is not applicable.",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","The README provides clear example prompts for using the `safe-debug` skill, demonstrating its intended invocation.",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","The script handles different error categories and suggests recovery actions, addressing potential failure modes.",{"category":111,"check":183,"severity":42,"summary":184},"Tool Fallback","The skill does not rely on external tools like MCP servers and uses only standard Python libraries.",{"category":186,"check":187,"severity":24,"summary":188},"Safety","Halt on unexpected state","The script's classification logic and error handling ensure it halts and reports if the input is unexpected or cannot be classified.",{"category":92,"check":190,"severity":24,"summary":191},"Cross-skill coupling","The `safe-debug` skill operates independently and does not rely on other skills being loaded concurrently.",1778692636337,"This skill acts as a trusted lane for debugging deep learning research failures. It analyzes provided error messages, tracebacks, or symptoms to identify root causes and suggest conservative, minimal fixes, requiring explicit user approval before any code modification.",[195,196,197,198,199],"Conservative error diagnosis for DL research failures","Classifies errors into categories (CUDA OOM, checkpoint mismatch, etc.)","Suggests minimal, safe fixes and recovery steps","Requires explicit user approval before patching code","Outputs detailed diagnosis and patch plan",[201,202,203,204],"Performing broad repository refactoring","Automatic exploratory patching","General repository familiarization without a failure symptom","Speculative adaptation of code","3.0.0","4.4.0","To provide a safe and conservative debugging experience for deep learning research, ensuring that diagnoses are thorough and any proposed code changes are minimal and explicitly approved.","The skill is exceptionally well-documented and robust, with clear purpose, usage, and safety features. It performs its specialized debugging task effectively and conservatively. The only minor point is the lack of explicit `context: fork` which is not applicable here.",99,"A high-quality, safe, and well-documented skill for diagnosing deep learning research errors.",[212,213,214,215,216],"debugging","deep-learning","research","error-analysis","troubleshooting","global","verified",[220,221,222,223,224],"Diagnosing CUDA Out Of Memory errors","Analyzing checkpoint loading failures","Troubleshooting shape mismatches in model tensors","Investigating NaN loss symptoms during training","Understanding terminal errors and tracebacks",{"codeQuality":226,"collectedAt":228,"documentation":229,"maintenance":232,"security":237,"testCoverage":239},{"hasLockfile":227},false,1778692621031,{"descriptionLength":230,"readmeSize":231},383,22701,{"closedIssues90d":8,"forks":233,"hasChangelog":234,"openIssues90d":8,"pushedAt":235,"stars":236},4,true,1778347974000,75,{"hasNpmPackage":227,"license":238,"smitheryVerified":227},"MIT",{"hasCi":234,"hasTests":234},{"updatedAt":241},1778692636476,{"basePath":243,"githubOwner":244,"githubRepo":245,"locale":18,"slug":13,"type":246},"skills/safe-debug","lllllllama","ai-paper-reproduction-skill","skill",null,{"evaluate":249,"extract":251},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":250,"targetMarket":217,"tier":218},[212,213,214,215,216],{"commitSha":252},"HEAD",{"repoId":254},"kd7629v5mqesxwwe9w7qtfgp7d86n6re",{"_creationTime":256,"_id":254,"identity":257,"providers":258,"workflow":491},1778692391648.3123,{"githubOwner":244,"githubRepo":245,"sourceUrl":14},{"classify":259,"discover":485,"github":488},{"commitSha":252,"extensions":260},[261,338,368,380,400,413,426,439,449,463,476],{"basePath":262,"description":263,"displayName":264,"installMethods":265,"rationale":266,"selectedPaths":267,"source":337,"sourceLanguage":18,"type":246},"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",{"basePath":339,"description":340,"displayName":341,"installMethods":342,"rationale":343,"selectedPaths":344,"source":337,"sourceLanguage":18,"type":246},"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",[345,346,348,350,352,354,356,358,360,362,364,366],{"path":269,"priority":270},{"path":347,"priority":286},"assets/COMMANDS.template.md",{"path":349,"priority":286},"assets/LOG.template.md",{"path":351,"priority":286},"assets/PATCHES.template.md",{"path":353,"priority":286},"assets/SUMMARY.template.md",{"path":355,"priority":286},"assets/status.template.json",{"path":357,"priority":273},"references/architecture.md",{"path":359,"priority":273},"references/language-policy.md",{"path":361,"priority":273},"references/output-spec.md",{"path":363,"priority":273},"references/patch-policy.md",{"path":365,"priority":273},"references/research-safety-principles.md",{"path":367,"priority":286},"scripts/orchestrate_repro.py",{"basePath":369,"description":370,"displayName":371,"installMethods":372,"rationale":373,"selectedPaths":374,"source":337,"sourceLanguage":18,"type":246},"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",[375,376,378],{"path":269,"priority":270},{"path":377,"priority":273},"references/analysis-policy.md",{"path":379,"priority":286},"scripts/analyze_project.py",{"basePath":381,"description":382,"displayName":383,"installMethods":384,"rationale":385,"selectedPaths":386,"source":337,"sourceLanguage":18,"type":246},"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",[387,388,390,392,394,396,398],{"path":269,"priority":270},{"path":389,"priority":273},"references/assets-policy.md",{"path":391,"priority":273},"references/env-policy.md",{"path":393,"priority":286},"scripts/bootstrap_env.py",{"path":395,"priority":286},"scripts/bootstrap_env.sh",{"path":397,"priority":286},"scripts/plan_setup.py",{"path":399,"priority":286},"scripts/prepare_assets.py",{"basePath":401,"description":402,"displayName":403,"installMethods":404,"rationale":405,"selectedPaths":406,"source":337,"sourceLanguage":18,"type":246},"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",[407,408,410,412],{"path":269,"priority":270},{"path":409,"priority":273},"references/explore-policy.md",{"path":411,"priority":286},"scripts/plan_code_changes.py",{"path":336,"priority":286},{"basePath":414,"description":415,"displayName":416,"installMethods":417,"rationale":418,"selectedPaths":419,"source":337,"sourceLanguage":18,"type":246},"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",[420,421,423,425],{"path":269,"priority":270},{"path":422,"priority":273},"references/execution-policy.md",{"path":424,"priority":286},"scripts/plan_variants.py",{"path":336,"priority":286},{"basePath":427,"description":428,"displayName":429,"installMethods":430,"rationale":431,"selectedPaths":432,"source":337,"sourceLanguage":18,"type":246},"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",[433,434,436,438],{"path":269,"priority":270},{"path":435,"priority":273},"references/reporting-policy.md",{"path":437,"priority":286},"scripts/run_command.py",{"path":336,"priority":286},{"basePath":440,"description":441,"displayName":442,"installMethods":443,"rationale":444,"selectedPaths":445,"source":337,"sourceLanguage":18,"type":246},"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",[446,447],{"path":269,"priority":270},{"path":448,"priority":273},"references/paper-assisted-reproduction.md",{"basePath":450,"description":451,"displayName":452,"installMethods":453,"rationale":454,"selectedPaths":455,"source":337,"sourceLanguage":18,"type":246},"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",[456,457,459,461],{"path":269,"priority":270},{"path":458,"priority":273},"references/repo-scan-rules.md",{"path":460,"priority":286},"scripts/extract_commands.py",{"path":462,"priority":286},"scripts/scan_repo.py",{"basePath":464,"description":465,"displayName":466,"installMethods":467,"rationale":468,"selectedPaths":469,"source":337,"sourceLanguage":18,"type":246},"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",[470,471,473,475],{"path":269,"priority":270},{"path":472,"priority":273},"references/training-policy.md",{"path":474,"priority":286},"scripts/run_training.py",{"path":336,"priority":286},{"basePath":243,"description":10,"displayName":13,"installMethods":477,"rationale":478,"selectedPaths":479,"source":337,"sourceLanguage":18,"type":246},{"claudeCode":12},"SKILL.md frontmatter at skills/safe-debug/SKILL.md",[480,481,483],{"path":269,"priority":270},{"path":482,"priority":273},"references/debug-policy.md",{"path":484,"priority":286},"scripts/safe_debug.py",{"sources":486},[487],"manual",{"closedIssues90d":8,"description":489,"forks":233,"license":238,"openIssues90d":8,"pushedAt":235,"readmeSize":231,"stars":236,"topics":490},"",[],{"classifiedAt":492,"discoverAt":493,"extractAt":494,"githubAt":494,"updatedAt":492},1778692395631,1778692391648,1778692393876,[212,213,215,214,216],{"evaluatedAt":241,"extractAt":497,"updatedAt":498},1778692396032,1778692750992,[],[501,528,559,579,608,637],{"_creationTime":502,"_id":503,"community":504,"display":505,"identity":511,"providers":515,"relations":521,"tags":523,"workflow":524},1778692607327.23,"k1797wq7825nd9yhz5q538asgn86nq05",{"reviewCount":8},{"description":506,"installMethods":507,"name":509,"sourceUrl":510},"Post-hoc diagnosis of a failed agent trajectory. Classifies the first unrecoverable step into one of nine failure categories (plan adherence, hallucinated information, invalid tool call, misread tool output, intent–plan mismatch, under-specified intent, unsupported intent, guardrail trigger, system failure) and produces an evidence-backed root-cause report.",{"claudeCode":508},"majiayu000/vibeguard","trajectory-review","https://github.com/majiayu000/vibeguard",{"basePath":512,"githubOwner":513,"githubRepo":514,"locale":18,"slug":509,"type":246},"skills/trajectory-review","majiayu000","vibeguard",{"evaluate":516,"extract":520},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":517,"targetMarket":217,"tier":218},[212,216,518,215,519],"agent-performance","trajectory-analysis",{"commitSha":252},{"repoId":522},"kd7b0vh258xpbyerk68bk3e1ks86mk58",[518,212,215,519,216],{"evaluatedAt":525,"extractAt":526,"updatedAt":527},1778692729089,1778692607327,1778693058643,{"_creationTime":529,"_id":530,"community":531,"display":532,"identity":538,"providers":543,"relations":553,"tags":555,"workflow":556},1778697652123.895,"k179x649dvyg7xswjx2h5a199n86m32x",{"reviewCount":8},{"description":533,"installMethods":534,"name":536,"sourceUrl":537},"Diagnose OpenClaw Android, iOS, or macOS node pairing, QR/setup code, route, auth, and connection failures.",{"claudeCode":535},"steipete/clawdis","Node Connect","https://github.com/steipete/clawdis",{"basePath":539,"githubOwner":540,"githubRepo":541,"locale":18,"slug":542,"type":246},"skills/node-connect","steipete","clawdis","node-connect",{"evaluate":544,"extract":552},{"promptVersionExtension":205,"promptVersionScoring":206,"score":545,"tags":546,"targetMarket":217,"tier":218},100,[212,547,548,549,550,216,551],"networking","android","ios","macos","openclaws",{"commitSha":252,"license":238},{"repoId":554},"kd738npxg9yh3xf3vddzy9fyfh86nhng",[548,212,549,550,547,551,216],{"evaluatedAt":557,"extractAt":558,"updatedAt":557},1778698735523,1778697652123,{"_creationTime":560,"_id":561,"community":562,"display":563,"identity":567,"providers":569,"relations":575,"tags":576,"workflow":577},1778697652123.8813,"k175pymk0vm7xrcjj2p0jf904186nae7",{"reviewCount":8},{"description":564,"installMethods":565,"name":566,"sourceUrl":537},"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":535},"openclaw-debugging",{"basePath":568,"githubOwner":540,"githubRepo":541,"locale":18,"slug":566,"type":246},".agents/skills/openclaw-debugging",{"evaluate":570,"extract":574},{"promptVersionExtension":205,"promptVersionScoring":206,"score":545,"tags":571,"targetMarket":217,"tier":218},[212,551,572,216,573],"cli","development",{"commitSha":252},{"repoId":554},[572,212,573,551,216],{"evaluatedAt":578,"extractAt":558,"updatedAt":578},1778697754713,{"_creationTime":580,"_id":581,"community":582,"display":583,"identity":589,"providers":594,"relations":602,"tags":604,"workflow":605},1778683190010.284,"k1757t8mrzzrf8yabxrtp82mg586m6nf",{"reviewCount":8},{"description":584,"installMethods":585,"name":587,"sourceUrl":588},"Systematic debugging methodology emphasizing root cause analysis over quick fixes",{"claudeCode":586},"bobmatnyc/claude-mpm-skills","Systematic Debugging","https://github.com/bobmatnyc/claude-mpm-skills",{"basePath":590,"githubOwner":591,"githubRepo":592,"locale":18,"slug":593,"type":246},"universal/debugging/systematic-debugging","bobmatnyc","claude-mpm-skills","systematic-debugging",{"evaluate":595,"extract":600},{"promptVersionExtension":205,"promptVersionScoring":206,"score":545,"tags":596,"targetMarket":217,"tier":218},[212,216,597,598,599],"root-cause-analysis","methodology","problem-solving",{"commitSha":252,"license":601},"Apache-2.0",{"repoId":603},"kd72g55e5qeqs90bk1bvkt8wbx86nkn3",[212,598,599,597,216],{"evaluatedAt":606,"extractAt":607,"updatedAt":606},1778686304588,1778683190010,{"_creationTime":609,"_id":610,"community":611,"display":612,"identity":617,"providers":621,"relations":629,"tags":632,"workflow":633},1778683762612.1245,"k1709q7z5grftph7kb93c569qh86n56a",{"reviewCount":8},{"description":613,"installMethods":614,"name":216,"sourceUrl":616},"Uses Chrome DevTools MCP and documentation to troubleshoot connection and target issues. Trigger this skill when list_pages, new_page, or navigate_page fail, or when the server initialization fails.",{"claudeCode":615},"ChromeDevTools/chrome-devtools-mcp","https://github.com/ChromeDevTools/chrome-devtools-mcp",{"basePath":618,"githubOwner":619,"githubRepo":620,"locale":18,"slug":216,"type":246},"skills/troubleshooting","ChromeDevTools","chrome-devtools-mcp",{"evaluate":622,"extract":628},{"promptVersionExtension":205,"promptVersionScoring":206,"score":545,"tags":623,"targetMarket":217,"tier":218},[624,625,216,212,626,627],"devtools","chrome","automation","mcp",{"commitSha":252},{"parentExtensionId":630,"repoId":631},"k17evynnzmmag96rw4rpybyydx86m0py","kd7an8ppnz1q2np9tc5yw4qenn86mg6h",[626,625,212,624,627,216],{"evaluatedAt":634,"extractAt":635,"updatedAt":636},1778683958622,1778683762612,1778684097619,{"_creationTime":638,"_id":639,"community":640,"display":641,"identity":647,"providers":651,"relations":658,"tags":661,"workflow":662},1778694480889.9556,"k17cw5h9amytcw2kg63ygtqqxn86nsp8",{"reviewCount":8},{"description":642,"installMethods":643,"name":645,"sourceUrl":646},"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":644},"NeoLabHQ/context-engineering-kit","root-cause-tracing","https://github.com/NeoLabHQ/context-engineering-kit",{"basePath":648,"githubOwner":649,"githubRepo":650,"locale":18,"slug":645,"type":246},"plugins/kaizen/skills/root-cause-tracing","NeoLabHQ","context-engineering-kit",{"evaluate":652,"extract":657},{"promptVersionExtension":205,"promptVersionScoring":206,"score":209,"tags":653,"targetMarket":217,"tier":218},[212,216,654,655,656],"code-analysis","developer-tools","call-stack",{"commitSha":252},{"parentExtensionId":659,"repoId":660},"k17884m6t3p8517a1d2zjp8zbd86n13x","kd7a3rj13ezgx1wgm0jfh08hsx86n0sz",[656,654,212,655,216],{"evaluatedAt":663,"extractAt":664,"updatedAt":663},1778695268236,1778694480890]