소스 정보
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- crossxwill/IML4Finance
- 최근 소스 활동
- 2026년 5월 21일 01:46
- 감지된 SKILL.md 언어
- 영어
- 스타
- 5
- 포크
- 1
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/crossxwill/IML4Finance --skill quarto-qmd-cli-rendering명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Edit Quarto (.qmd) and Markdown (.md) files with proper nested code block handling to prevent parser errors and truncated output; standalone utility with no skill dependencies.
Consolidated AutoGluon skill covering end-to-end TabularPredictor workflow (constructor, fit, predict_proba, fit_summary, save/load, set_model_best), binary threshold calibration and setting, sklearn wrapper integration, and monotonic constraints. Use for any AutoGluon Tabular questions, training/ensembling configuration, inference/probabilities, threshold tuning, deployment persistence, or sklearn interoperability.
Create a concise plan. Use when a user explicitly asks for a plan related to a coding task.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | quarto-qmd-cli-rendering |
| description | Render or build or compile Quarto .qmd files from the command line. |
When asked to “render”, “build”, “preview”, or “compile” a Quarto .qmd, respond with quarto CLI commands that are copy-pastable and include brief, practical notes.
Include a short note that the terminal will show per-cell progress lines like:
Cell 1/3 '{cell-label}'.....Done
Cell 2/3 '{cell-label}'.....Done
Cell 3/3 '{cell-label}'.....Done
Output created: {file-name}
Some cells finish quickly while others can take a long time; the agent should be patient and wait for completion. For example, the following terminal indicates that cell 2 is still running:
Cell 1/3 '{cell-label}'.....Done
Cell 2/3 '{cell-label}'.....
quarto.quarto render <file.qmd>.quarto render or quarto render <dir> (named project directory).; if ($LASTEXITCODE -eq 0) { echo "Render finished" }&& echo "Render finished".qmdMinimal pattern:
quarto render <file.qmd>
Optional explicit success signal (choose ONE depending on shell):
quarto render <file.qmd> ; if ($LASTEXITCODE -eq 0) { echo "Render finished" }
quarto render <file.qmd> && echo "Render finished"
Use sequential rendering when the user requests:
Instructions:
quarto render <file.qmd> ; if ($LASTEXITCODE -eq 0) { echo "Render finished" }quarto render <file.qmd> && echo "Render finished".qmd, then re-run the same command until it succeeds..qmd only after the current one succeeds.Render finished.When Quarto reports a failing cell:
Cell 47/124: 'calibration-s2')..qmd plus one neighboring chunk that implements the same pattern.Prefer local chunk comparisons over broad repo exploration; most render failures are plain code or markdown defects inside the current .qmd.
Use this skill when:
.qmd, Quarto, “render/build/compile/preview”, CI, Makefiles, or scripting.Do not use this skill when:
Quarto looks for python3 on the PATH, but conda environments only provide python (not python3). Fix by setting the QUARTO_PYTHON environment variable to the full path of the Python executable before running quarto render.
First, find the Python path:
conda activate <env_name>; python -c "import sys; print(sys.executable)"
Then use it when rendering:
conda activate <env_name>; $env:QUARTO_PYTHON = "<full-python-path>"; quarto render <file.qmd>; if ($LASTEXITCODE -eq 0) { echo "Render finished" }
Example:
conda activate env_AutoGluon_202502; $env:QUARTO_PYTHON = "C:\Users\chiuw\miniforge3\envs\env_AutoGluon_202502\python.exe"; quarto render Labs/Lab_01.qmd; if ($LASTEXITCODE -eq 0) { echo "Render finished" }
This occurs when Quarto's internal cache is stale or was created by a different Quarto version. The error often manifests during Sass compilation for revealjs themes.
Fix: Clear all Quarto cache directories recursively before rendering:
conda activate <env_name>; Get-ChildItem -Recurse -Directory -Filter "_quarto*" | Remove-Item -Recurse -Force -ErrorAction SilentlyContinue; Get-ChildItem -Recurse -Directory -Filter ".quarto*" | Remove-Item -Recurse -Force -ErrorAction SilentlyContinue; Get-ChildItem -Recurse -Directory -Filter "_site*" | Remove-Item -Recurse -Force -ErrorAction SilentlyContinue; echo "All caches cleared"
Then retry the render with --no-cache:
conda activate <env_name>; $env:QUARTO_PYTHON = "<full-python-path>"; quarto render <file.qmd> --no-cache; if ($LASTEXITCODE -eq 0) { echo "Render finished" }
Harmless cleanup error. Use -ErrorAction SilentlyContinue on Remove-Item commands to suppress it. Does not affect render output.
This is common for notebook-backed .qmd files that train models or generate large reports. A terminal line such as:
Cell 29/124: 'lab04-fit-autogluon-s1'...............
does not imply a hang by itself.
Before treating it as stalled:
If those checks show activity, keep waiting. Long AutoGluon or SHAP cells can legitimately run for many minutes.
Do not restart broad debugging. Use the exact failing cell and traceback to inspect the local chunk first.
Common causes in .qmd code cells:
displayBefore rendering any .qmd in this project, always:
conda activate env_AutoGluon_202502$env:QUARTO_PYTHON to the conda env's Python executable--no-cache if cache issues persist; if ($LASTEXITCODE -eq 0) { echo "Render finished" }time_limit settings. Cells that train models (e.g., TabularPredictor.fit()) are the bottleneckAlways use mode='async' when running render commands and poll with get_terminal_output until the success signal appears.