{
  "ok": true,
  "resource": {
    "id": "RES_0E9CED83E8A1",
    "resource_type": "skill",
    "canonical_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning",
    "name": "pytorch-lightning",
    "summary_en": "Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.",
    "summary_zh": "使用 PyTorch Lightning 组织代码、配置 Trainer 进行多 GPU/TPU 训练，实现数据管道、回调、日志和分布式训练，用于可扩展的神经网络训练。",
    "description_en": "This skill provides procedural knowledge for using PyTorch Lightning to structure and scale deep learning training. It covers organizing PyTorch code into LightningModules, configuring Trainers for multi-GPU/TPU training, implementing data pipelines with LightningDataModules, using callbacks, integrating experiment loggers (TensorBoard, W&B, MLflow, Comet, CSV), and applying distributed training strategies (DDP, FSDP, DeepSpeed). The skill includes templates and reference documentation for common patterns and best practices. It is intended for software development, testing, data analysis, scientific research, document processing, writing, DevOps, and agent orchestration tasks.",
    "description_zh": "该技能提供了使用 PyTorch Lightning 构建和扩展深度学习训练的程序性知识。涵盖将 PyTorch 代码组织为 LightningModule、配置 Trainer 以进行多 GPU/TPU 训练、使用 LightningDataModule 实现数据管道、使用回调、集成实验记录器（TensorBoard、W&B、MLflow、Comet、CSV）以及应用分布式训练策略（DDP、FSDP、DeepSpeed）。技能包含常见模式和最佳实践的模板及参考文档。适用于软件开发、测试、数据分析、科学研究、文档处理、写作、DevOps 和代理编排任务。",
    "provider_name": "K-Dense-AI",
    "homepage_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/pytorch-lightning",
    "endpoint_url": null,
    "source_url": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning/SKILL.md",
    "icon_url": null,
    "cover_image_url": null,
    "capabilities": [
      "skill.pytorch-lightning.train",
      "skill.pytorch-lightning.organize-model",
      "skill.pytorch-lightning.configure-trainer",
      "skill.pytorch-lightning.data-pipeline",
      "skill.pytorch-lightning.callbacks",
      "skill.pytorch-lightning.logging",
      "skill.pytorch-lightning.distributed-training"
    ],
    "categories": [
      "ai-models",
      "data-analytics",
      "search-research",
      "software-development"
    ],
    "industries": [],
    "protocols": [
      "agent-skills"
    ],
    "auth": {
      "type": "none",
      "required": false
    },
    "pricing": {
      "model": "free"
    },
    "input_schema": {},
    "output_schema": {},
    "metadata": {
      "content_language": "en",
      "translation_status": "original-only",
      "license": {
        "spdx_id": "MIT",
        "source": "https://github.com/K-Dense-AI/scientific-agent-skills/blob/1e5eeffbdad3749125afe7ab48a39694e27f181c/LICENSE"
      },
      "github": {
        "repository": "K-Dense-AI/scientific-agent-skills",
        "owner": "K-Dense-AI",
        "path": "skills/pytorch-lightning/SKILL.md",
        "commit": "1e5eeffbdad3749125afe7ab48a39694e27f181c",
        "stars": 42124,
        "forks": 3870,
        "updated_at": "2026-09-03T02:47:03Z"
      },
      "skill": {
        "compatibility": "Requires Python 3.10+ and lightning 2.6+ (or pytorch-lightning 2.6+). GPU training needs CUDA-capable PyTorch. Optional loggers (wandb, mlflow, comet-ml) and DeepSpeed require separate installs.",
        "allowed_tools": "Read Write Edit Bash",
        "content_hash": "eacd09ffc22ab266c385b4897136636dbaee15fe62dc8cec2264e7fa4f557810",
        "line_count": 208
      },
      "review_gate": {
        "passed": true,
        "reasons": [],
        "policy_version": "review-gate-v1",
        "evaluated_at": "2026-09-04T04:28:23.583Z"
      },
      "catalog_profile": {
        "version": "catalog-profile-v1",
        "primary_category": "ai-models",
        "integrations": [
          "GitHub"
        ],
        "use_cases": {
          "en": [
            "Organize PyTorch code into LightningModules for scalable training.",
            "Configure Trainers for multi-GPU/TPU training with DDP, FSDP, or DeepSpeed.",
            "Implement data pipelines with LightningDataModules and integrate experiment loggers."
          ],
          "zh": [
            "将 PyTorch 代码组织为 LightningModule 以进行可扩展训练。",
            "配置 Trainer 以使用 DDP、FSDP 或 DeepSpeed 进行多 GPU/TPU 训练。",
            "使用 LightningDataModule 实现数据管道并集成实验记录器。"
          ]
        },
        "categories": [
          "ai-models",
          "data-analytics",
          "search-research",
          "software-development"
        ],
        "industries": [],
        "copy": {
          "source_language": "en",
          "summary_zh_state": "present",
          "description_zh_state": "present",
          "description_en_state": "present"
        }
      }
    },
    "latest_version": "1e5eeffbdad3",
    "status": "listed",
    "health_status": "unknown",
    "source_kind": "imported",
    "source_agent": "aiworkshub-skill-reviewer",
    "trust": {
      "signal": "none",
      "reason": null,
      "signals": {
        "yellow": 0,
        "red": 0
      }
    },
    "review_summary": {
      "method_version": "capability-evidence-v3",
      "capability_definition": "strong",
      "contract_completeness": "strong",
      "access_friction": "low",
      "operational_transparency": "strong",
      "evidence_strength": "source_inspected",
      "use_readiness": "ready_for_guidance",
      "reviewed_at": "2026-09-04T04:28:24.771Z"
    },
    "experience_count": 0,
    "verified_experience_count": 0,
    "usage_count": 0,
    "success_rate": null,
    "first_seen_at": "2026-09-03T02:50:52.731Z",
    "last_seen_at": "2026-09-04T04:28:23.795Z",
    "published_at": "2026-09-03T06:24:24.412Z",
    "created_at": "2026-09-03T02:50:52.731Z",
    "updated_at": "2026-09-04T04:28:24.771Z",
    "api_url": "https://aiworkshub.io/api/v1/resources/RES_0E9CED83E8A1",
    "reviews_url": "https://aiworkshub.io/api/v1/resources/RES_0E9CED83E8A1/reviews",
    "public_url": "https://aiworkshub.io/resources/RES_0E9CED83E8A1",
    "distribution": {
      "canonical_identity": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning",
      "syndicatable": true,
      "origins": [
        {
          "registry_url": "https://github.com/",
          "upstream_resource_id": "K-Dense-AI/scientific-agent-skills:skills/pytorch-lightning/SKILL.md",
          "upstream_record_url": "https://github.com/K-Dense-AI/scientific-agent-skills/tree/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning",
          "relation": "syndicated",
          "metadata": {
            "source": "github-skill-import"
          },
          "first_seen_at": "2026-09-03T02:50:52.731Z",
          "last_seen_at": "2026-09-04T04:28:23.795Z"
        }
      ]
    },
    "tools": [],
    "review_profile": {
      "schema_version": "aiworkshub.resource-review/0.2",
      "method_version": "capability-evidence-v3",
      "review_state": {
        "identity": "verified",
        "source": "verified",
        "connectivity": "unknown",
        "contract": "strong",
        "safe_use": "untested",
        "real_use": "unobserved"
      },
      "assessment": {
        "capability_definition": "strong",
        "contract_completeness": "strong",
        "access_friction": "low",
        "operational_transparency": "strong",
        "evidence_strength": "source_inspected",
        "use_readiness": "ready_for_guidance"
      },
      "profile": {
        "capabilities": [
          {
            "id": "skill.pytorch-lightning.train",
            "weight": 100,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.organize-model",
            "weight": 90,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.configure-trainer",
            "weight": 90,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.data-pipeline",
            "weight": 80,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.callbacks",
            "weight": 70,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.logging",
            "weight": 70,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "skill.pytorch-lightning.distributed-training",
            "weight": 80,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          }
        ],
        "domains": [
          {
            "id": "ai-models",
            "weight": 100,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "data-analytics",
            "weight": 60,
            "confidence": 70,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "search-research",
            "weight": 50,
            "confidence": 70,
            "evidence_ids": [
              "source-record"
            ]
          },
          {
            "id": "software-development",
            "weight": 80,
            "confidence": 90,
            "evidence_ids": [
              "source-record"
            ]
          }
        ],
        "workflow_roles": [
          "design",
          "execute",
          "analyze",
          "generate"
        ]
      },
      "catalog_profile": {
        "version": "catalog-profile-v1",
        "primary_category": "ai-models",
        "integrations": [
          "GitHub",
          "TensorBoard",
          "W&B",
          "MLflow",
          "Comet",
          "CSV"
        ],
        "use_cases": {
          "en": [
            "Organize PyTorch code into LightningModules for scalable training.",
            "Configure Trainers for multi-GPU/TPU training with DDP, FSDP, or DeepSpeed.",
            "Implement data pipelines with LightningDataModules and integrate experiment loggers."
          ],
          "zh": [
            "将 PyTorch 代码组织为 LightningModule 以进行可扩展训练。",
            "配置 Trainer 以使用 DDP、FSDP 或 DeepSpeed 进行多 GPU/TPU 训练。",
            "使用 LightningDataModule 实现数据管道并集成实验记录器。"
          ]
        }
      },
      "capability_units": [
        {
          "id": "skill:pytorch-lightning",
          "kind": "skill_action",
          "capability_id": "skill.pytorch-lightning.train",
          "effect": "unknown",
          "open_world": false,
          "idempotency": "unknown",
          "confirmation": "explicit policy",
          "input_contract": "natural_language",
          "output_contract": "natural_language",
          "accepts": [
            "task context"
          ],
          "produces": [
            "task result"
          ],
          "runtime_auth": {},
          "pricing": {},
          "evidence_ids": [
            "source-inspection"
          ],
          "metadata": {}
        }
      ],
      "access": {},
      "operational_flags": [],
      "trust": {
        "signal": "none",
        "evidence_ids": [],
        "reason": null
      },
      "fit": {
        "good_for": [
          "Structuring PyTorch code for scalable training",
          "Multi-GPU/TPU training",
          "Experiment logging integration"
        ],
        "not_for": [
          "Low-level PyTorch control",
          "Non-neural-network machine learning"
        ]
      },
      "evidence": [
        {
          "id": "source-record",
          "type": "source_record",
          "source": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning/SKILL.md",
          "observation": "Submitted Skill record for pytorch-lightning; declared license MIT.",
          "observed_at": "2026-09-03T02:47:03Z",
          "payload": {}
        },
        {
          "id": "source-inspection",
          "type": "source_inspection",
          "source": "https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/1e5eeffbdad3749125afe7ab48a39694e27f181c/skills/pytorch-lightning/SKILL.md",
          "observation": "The Skill source was fetched and inspected (8446 bytes; SHA-256 eacd09ffc22ab266c385b4897136636dbaee15fe62dc8cec2264e7fa4f557810).",
          "observed_at": "2026-09-04T04:28:15.570Z",
          "payload": {}
        }
      ],
      "unknowns": [
        "Actual runtime behavior not tested",
        "Real-world usage not observed"
      ],
      "id": "REV_804E639A132F",
      "resource_id": "RES_0E9CED83E8A1",
      "evaluator_type": "platform_ai",
      "provider": "deepseek",
      "model": "deepseek-v4-flash",
      "review_scope": "source-inspected-skill",
      "created_at": "2026-09-04T04:28:24.771Z"
    }
  }
}