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unitorch-copilot-cli-core-copilot-pkg-infos
Use when an agent needs to invoke the `core/copilot/pkg_infos` unitorch copilot tool.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Use when an agent needs to invoke the `core/copilot/pkg_infos` unitorch copilot tool.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | unitorch-copilot-cli-core-copilot-pkg_infos |
| description | Use when an agent needs to invoke the `core/copilot/pkg_infos` unitorch copilot tool. |
List registered unitorch packages and copilot tools.
This is a subskill of unitorch-copilot-cli. Use the parent skill index to discover other registered copilot tools.
Use this skill when you need to call core/copilot/pkg_infos through unitorch copilot.
unitorch-copilot-cli core/copilot/pkg_infos
from unitorch.cli.copilots import get_copilot_tool
tool = get_copilot_tool("core/copilot/pkg_infos")
result = tool.invoke()
| Name | Type | Required | Default |
|---|---|---|---|
name | Optional[str] | no |
This copilot tool does not declare a remote FastAPI adapter.
Guidance for writing, reviewing, and updating unitorch INI configuration files for train, eval, infer, and FastAPI workflows. Use when creating or modifying examples/configs/*.ini, reasoning about Config interpolation and CLI overrides, composing preprocess_functions, choosing registered component names, or debugging unitorch CLI config behavior.
Use when an agent needs to discover and invoke registered UniTorch copilot tools through `unitorch-copilot-cli`.
Guidance for creating, reviewing, running, and debugging unitorch batch model inference workflows with unitorch-infer. Use when preparing inference INI configs, choosing registered models/processors/postprocess functions/writers, running inference from checkpoints, configuring vLLM inference, preserving raw input columns in outputs, or diagnosing empty, duplicated, or incorrect inference results.
Reference for using, reviewing, or modifying unitorch's @replace decorator in src/unitorch/utils/decorators.py. Use when overriding upstream classes, adding replacement classes under modules/replace, reasoning about process-global monkey patches, or debugging import-time replacement and subclass __bases__ rewriting.
Guidance for creating, reviewing, launching, calling, and debugging unitorch FastAPI services with unitorch-fastapi and CopilotClient. Use when preparing FastAPI INI configs, choosing registered core/fastapi services, configuring routers and pipeline sections, starting or stopping daemon/foreground servers, calling /start /status /generate endpoints, using autostart_services, or diagnosing health-check, port, route, service loading, and request-format issues.
Guidance for creating, reviewing, running, and debugging unitorch model training workflows with unitorch-train. Use when preparing training INI configs, choosing registered models/processors/losses/scores, launching single-GPU or distributed training, checking checkpoint loading, monitoring loss and validation metrics, or diagnosing unstable training.