Thinking_with_Visual_Primitives.pdf:

arXiv 2604.13016:

Convert academic PDF papers or arXiv/LaTeX sources into Chinese PDF outputs and sentence-interleaved English/Chinese bilingual PDF outputs while preserving LaTeX structure as much as practical.
Use this repository as the update source for the skill:
https://github.com/fanxing-6/pdf2zh-skill.git
DOC2Xmerge_中文.tex into a Chinese PDFmerge_中英双语.tex into a bilingual PDF whose prose alternates English sentence, green Chinese sentencevision_pack/, vision_pack_bilingual/, and quality_report_中文.* for model review and final correctionEach run creates a unique task folder under a persistent output root. By default this is PDF2ZH_SKILL_HOME/runs, or ~/pdf2zh-skill/runs when PDF2ZH_SKILL_HOME is not set. Set PDF2ZH_SKILL_OUTPUT_DIR to choose another durable location; PDF2ZH_SKILL_TMPDIR is accepted as a compatibility alias, but new configs should prefer PDF2ZH_SKILL_OUTPUT_DIR.
pdf2zh-skill/YYYYMMDD-HHMMSS-<source_slug>-<short_hash>/
The final deliverables are named from the original PDF stem or, for arXiv URLs, the paper title when available:
<name>_English.tex<name>_中文.tex<name>_中文.pdf<name>_中英双语.tex<name>_中英双语.pdfUser-facing handoff should point to these named files in the task root. Files named zh/merge_* are internal work artifacts; after any manual correction or recompile, copy the updated merge_* artifacts back to the named outputs and refresh run_summary.json.
Internal working files remain stable under zh/:
merge_English.texmerge_中文.texmerge_中文.pdfmerge_中英双语.texmerge_中英双语.pdfsegments_English.jsonlglossary_English.jsontranslations_中文.jsonltranslations_reviewed_中文.jsonlconsistency_report_中文.jsonquality_report_中文.jsonquality_report_中文.mdWhen a local --pdf or --source-pdf points at an upload cache or other temporary path, the pipeline copies it into source/ inside the task folder before conversion and visual review. Completed runs therefore do not depend on the original temp path still existing after a restart.
Create a .env from .env.example and fill in your credentials:
DOC2X_API_KEY=...
PDF2ZH_TRANSLATION_API_KEY=...
PDF2ZH_TRANSLATION_BASE_URL=...
PDF2ZH_TRANSLATION_MODEL=...
Check the effective configuration before a full run:
python scripts/pdf2zh_pipeline.py check-config
If translation config is missing, provide an OpenAI-compatible chat completions base_url, api_key, and model. If a regular PDF needs DOC2X conversion, also provide DOC2X_API_KEY.
Then run:
python scripts/pdf2zh_pipeline.py run --pdf paper.pdf --method doc2x --workers 50
For arXiv:
python scripts/pdf2zh_pipeline.py run --url https://arxiv.org/abs/0000.00000 --workers 50
The run output includes run_summary.json, Windows-visible paths when running under WSL, a visual review pack, and a quality review report.
After run finishes, inspect:
quality_report_中文.mdvision_pack/manifest.jsonvision_pack_bilingual/manifest.jsonzh/merge_中文.texzh/merge_中英双语.texThe framework handles deterministic cleanup and detection. Complex LaTeX template issues and final visual alignment are intentionally handled by the model by editing zh/merge_中文.tex or zh/merge_中英双语.tex and recompiling.
The first example above comes from the DOC2X route. The second comes from the source-TeX route, where the skill probes arXiv source first and skips DOC2X when the paper source is available.
Raw images are also included:
docs/images/thinking_with_visual_primitives_before.pngdocs/images/thinking_with_visual_primitives_after.pngdocs/images/arxiv_2604_13016_before.pngdocs/images/arxiv_2604_13016_after.pngSKILL.md: skill contract and operating notesscripts/pdf2zh_pipeline.py: CLI entrypointscripts/pdf2zh_skill/: implementation modulesPython
100.0%
Thinking_with_Visual_Primitives.pdf:

arXiv 2604.13016:

Convert academic PDF papers or arXiv/LaTeX sources into Chinese PDF outputs and sentence-interleaved English/Chinese bilingual PDF outputs while preserving LaTeX structure as much as practical.
Use this repository as the update source for the skill:
https://github.com/fanxing-6/pdf2zh-skill.git
DOC2Xmerge_中文.tex into a Chinese PDFmerge_中英双语.tex into a bilingual PDF whose prose alternates English sentence, green Chinese sentencevision_pack/, vision_pack_bilingual/, and quality_report_中文.* for model review and final correctionEach run creates a unique task folder under a persistent output root. By default this is PDF2ZH_SKILL_HOME/runs, or ~/pdf2zh-skill/runs when PDF2ZH_SKILL_HOME is not set. Set PDF2ZH_SKILL_OUTPUT_DIR to choose another durable location; PDF2ZH_SKILL_TMPDIR is accepted as a compatibility alias, but new configs should prefer PDF2ZH_SKILL_OUTPUT_DIR.
pdf2zh-skill/YYYYMMDD-HHMMSS-<source_slug>-<short_hash>/
The final deliverables are named from the original PDF stem or, for arXiv URLs, the paper title when available:
<name>_English.tex<name>_中文.tex<name>_中文.pdf<name>_中英双语.tex<name>_中英双语.pdfUser-facing handoff should point to these named files in the task root. Files named zh/merge_* are internal work artifacts; after any manual correction or recompile, copy the updated merge_* artifacts back to the named outputs and refresh run_summary.json.
Internal working files remain stable under zh/:
merge_English.texmerge_中文.texmerge_中文.pdfmerge_中英双语.texmerge_中英双语.pdfsegments_English.jsonlglossary_English.jsontranslations_中文.jsonltranslations_reviewed_中文.jsonlconsistency_report_中文.jsonquality_report_中文.jsonquality_report_中文.mdWhen a local --pdf or --source-pdf points at an upload cache or other temporary path, the pipeline copies it into source/ inside the task folder before conversion and visual review. Completed runs therefore do not depend on the original temp path still existing after a restart.
Create a .env from .env.example and fill in your credentials:
DOC2X_API_KEY=...
PDF2ZH_TRANSLATION_API_KEY=...
PDF2ZH_TRANSLATION_BASE_URL=...
PDF2ZH_TRANSLATION_MODEL=...
Check the effective configuration before a full run:
python scripts/pdf2zh_pipeline.py check-config
If translation config is missing, provide an OpenAI-compatible chat completions base_url, api_key, and model. If a regular PDF needs DOC2X conversion, also provide DOC2X_API_KEY.
Then run:
python scripts/pdf2zh_pipeline.py run --pdf paper.pdf --method doc2x --workers 50
For arXiv:
python scripts/pdf2zh_pipeline.py run --url https://arxiv.org/abs/0000.00000 --workers 50
The run output includes run_summary.json, Windows-visible paths when running under WSL, a visual review pack, and a quality review report.
After run finishes, inspect:
quality_report_中文.mdvision_pack/manifest.jsonvision_pack_bilingual/manifest.jsonzh/merge_中文.texzh/merge_中英双语.texThe framework handles deterministic cleanup and detection. Complex LaTeX template issues and final visual alignment are intentionally handled by the model by editing zh/merge_中文.tex or zh/merge_中英双语.tex and recompiling.
The first example above comes from the DOC2X route. The second comes from the source-TeX route, where the skill probes arXiv source first and skips DOC2X when the paper source is available.
Raw images are also included:
docs/images/thinking_with_visual_primitives_before.pngdocs/images/thinking_with_visual_primitives_after.pngdocs/images/arxiv_2604_13016_before.pngdocs/images/arxiv_2604_13016_after.pngSKILL.md: skill contract and operating notesscripts/pdf2zh_pipeline.py: CLI entrypointscripts/pdf2zh_skill/: implementation modulesPython
100.0%