본문으로 건너뛰기
cccskills
무료GitHub에 공개

doccano

Operate doccano for text annotation, dataset import/export, auto-labeling, deployment, and repo maintenance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구Docker
설치 방법 보기

포함된 파일(25)

  • SKILL.md2.8 KB
  • references/cli-reference.md2.9 KB
  • references/overview.md2.4 KB
  • references/repo-provenance.md1.5 KB
  • references/repo-routing-metadata.json303 B
  • references/task-types.md2.3 KB
  • references/troubleshooting.md4.3 KB
  • scripts/cli-smoke.sh710 B
  • sub-skills/auto-labeling/references/troubleshooting.md1.5 KB
  • sub-skills/auto-labeling/references/workflows.md2.1 KB
  • sub-skills/auto-labeling/scripts/list-templates.py777 B
  • sub-skills/auto-labeling/SKILL.md1.8 KB
  • sub-skills/data-transfer/references/formats.md2.8 KB
  • sub-skills/data-transfer/references/troubleshooting.md2.3 KB
  • sub-skills/data-transfer/scripts/list-formats.py1.3 KB
  • sub-skills/data-transfer/SKILL.md1.8 KB
  • sub-skills/project-annotation/references/troubleshooting.md1.9 KB
  • sub-skills/project-annotation/references/workflows.md3.0 KB
  • sub-skills/project-annotation/SKILL.md1.7 KB
  • sub-skills/setup-and-deploy/references/build-and-test.md1.0 KB
  • sub-skills/setup-and-deploy/references/deployment.md1.0 KB
  • sub-skills/setup-and-deploy/references/install-and-runtime.md1.7 KB
  • sub-skills/setup-and-deploy/references/troubleshooting.md1.6 KB
  • sub-skills/setup-and-deploy/scripts/build-package.sh1.1 KB
  • sub-skills/setup-and-deploy/SKILL.md1.9 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

doccano

doccano is a text annotation platform with a Django backend, a Nuxt frontend, and CLI/deployment entry points for local, Docker, and cloud use.

Use this skill when a task mentions doccano itself, project/label/member workflows, dataset import or export, auto-labeling, deployment, or repository maintenance for this checkout.

How to route

RouteRead when
sub-skills/setup-and-deploy/You need install, initialize, run, package, Docker, or cloud deployment guidance.
sub-skills/project-annotation/You need project creation, label setup, members, comments, annotation, cloning, or metrics.
sub-skills/data-transfer/You need dataset import/export formats, validation, encodings, or format-specific troubleshooting.
sub-skills/auto-labeling/You need template selection, request testing, response mapping, label mapping, or auto-labeling activation.

Start here

  • New users usually start with sub-skills/setup-and-deploy/SKILL.md.
  • If the request is about the running app, route to the workflow sub-skill that matches the task family first, then read the shared references listed below.
  • If the request is about editing the source checkout, package build, or tests, keep python-repository-maintenance in mind and start with sub-skills/setup-and-deploy/SKILL.md for the build/runtime entry points.

Safe minimal check

Use the installed package and CLI before deeper work:

pip install doccano
python -I -c "import backend; import backend.cli; print(backend.__file__)"
doccano --help

If the package was already installed, python -m pip check is a useful follow-up health check.

Shared references

  • Read references/overview.md for the repo map and major surfaces.
  • Read references/task-types.md when you need the supported project types or their annotation shapes.
  • Read references/cli-reference.md for the command list and environment variables.
  • Read references/troubleshooting.md for cross-cutting install, runtime, and validation failures.
  • Read references/repo-provenance.md before deciding whether the skill is stale.
  • Read references/repo-routing-metadata.json when you need the routing contract consumed by repo-skills-router.
  • Use scripts/cli-smoke.sh for a fast install-and-CLI sanity check.

Working rules

  • Keep runtime guidance self-contained inside this skill tree.
  • Do not point future agents back to the original checkout for commands that can be bundled here.
  • Prefer the nearest sub-skill for workflow details and keep this router short.
  • Use the repo-maintenance scenario only for source edits, tests, packaging, or contributor workflows.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

3ddfa

무료

Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

3ddfa-v2

무료

Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

ab3dmot

무료

Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

acme

무료

Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VectorSpaceLab/AREX-Skill3382026년 9월 3일 업데이트

VectorSpaceLab의 스킬 모두 보기

이 스킬의 문제 신고