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- Rosalynyang
- Feishu Doc Creator Skill
- Feishu Md Parser
feishu-md-parser_skill
- Python
5
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill rosalynyang/feishu-doc-creator-skill --skill feishu-md-parser- SKILL.md3.2 KB
Overview
This skill parses Markdown files into Feishu document block JSON, supporting a wide range of block types and producing ready-to-use output. It maps up to 25 block types (headings, lists, tables, code, callouts, images, etc.) and now includes local image upload support. The parser writes parsed blocks and metadata to output JSON files for downstream workflows.
How this skill works
The parser reads a Markdown file from a provided path, tokenizes common Markdown constructs, and converts each construct into the corresponding Feishu block structure. It normalizes text (removing zero-width characters and cleaning table cells), detects images (local paths vs. remote URLs), and records local image paths for upload. The final output is blocks.json and a metadata.json summary with counts for headings, tables, images, and other block types.
When to use it
- Converting project or product docs from Markdown into Feishu-compatible JSON for automated document creation.
- Preparing content for a Feishu document creation pipeline where images must be uploaded from local files.
- Batch-processing Markdown files to extract structured block data and usage metadata.
- Integrating with a workflow that consumes block JSON and handles uploading tokens and file attachments.
Best practices
- Keep local image paths absolute and ensure files exist; supported formats are .png, .jpg, .jpeg, .gif.
- Use standard Markdown syntax for headings, lists, tables, code blocks, and blockquotes for best mapping accuracy.
- Run the parser in a controlled environment so local image upload steps have access to the filesystem.
- Clean or simplify complex table markup before parsing to reduce post-processing.
- Validate the generated blocks.json against downstream Feishu block expectations before mass deployment.
Example use cases
- Automated conversion of a Markdown release note directory into a Feishu doc with uploaded local screenshots.
- CI pipeline step: parse documentation Markdown into blocks.json, then call a Feishu document creator skill to import it.
- Content migration: transform wiki Markdown pages to Feishu documents while preserving headings, code samples, and images.
- Preflight validation: generate metadata.json to count tables, code blocks, and images for QA before publishing.
FAQ
The parser records local_path and prepares image blocks; the actual upload and token setting are handled by the image uploader in the document creation step.
How are remote image URLs treated?
Remote URLs are preserved as links in image blocks and are not uploaded.
What output files are produced?
It produces output/blocks.json with block data and output/metadata.json with counts and summary information.