Feishu Knowledge Ingest

Use this skill to turn a Feishu folder or a single shared attachment into structured, reviewable knowledge outputs.

What this skill does

• - Accept a Feishu folder link/token or a single shared attachment.
• Classify files into direct-read, download-and-parse, manual-review, or permission-blocked.
• Parse .docx and .pdf in v0.1.
• Produce report-first outputs instead of writing MEMORY.md directly.
• Preserve failures and uncertainty instead of guessing content.

Supported v0.1 scope

Inputs

• - Feishu folder link or INLINECODE3
• Single shared attachment link or token

Parsing

• - INLINECODE4
• INLINECODE5

Outputs

• - INLINECODE6
• INLINECODE7
• INLINECODE8
• INLINECODE9

Required behavior

1. 1. Distinguish Feishu native docs from uploaded attachments.

- Native docs: doc, sheet, wiki, bitable - Uploaded attachments: .docx, .pdf, .pptx, other files

1. 2. Do not claim attachment content was learned unless text was actually extracted.
2. Default to report-first. Do not write MEMORY.md in v0.1.
3. Record every failed file with a concrete reason.
4. Prefer plain-text summaries over complex Feishu cards when reporting progress.

File routing rules

Direct-read

Treat these as direct-read only when the runtime has a reliable native-reader path:

• - INLINECODE18
• INLINECODE19
• INLINECODE20
• INLINECODE21

Download-and-parse

Treat these as download-and-parse:

• - INLINECODE22
• INLINECODE23

Manual-review

Route here when the file is out of scope or low-confidence in v0.1:

• - INLINECODE24
• images
• scans with no extractable text
• archives
• unusual file types

Permission-blocked

Route here when listing is possible but the file cannot be downloaded or read.

Standard workflow

1. 1. Resolve input type.

- Folder link/token -> enumerate files. - Single file link/token -> build a one-file manifest.

1. 2. Create a batch record.

- Generate batch_id. - Record started_at.

1. 3. Build a manifest.

- File name - File token/link - file type - route decision

1. 4. Attempt extraction.

- .docx -> use parsers/parse_docx.py - .pdf -> use parsers/parse_pdf.py

1. 5. Produce structured outputs.

- success -> append to kb-items.jsonl - failure -> append to failed-items.jsonl

1. 6. Summarize the batch.

- Write ingest-report.md - Write MEMORY.candidate.md

1. 7. Finish the batch.

- Record finished_at - Never auto-write INLINECODE36

Output contracts

kb-items.jsonl

Write one JSON object per successfully extracted knowledge item with at least:

• - INLINECODE37
• INLINECODE38
• INLINECODE39
• INLINECODE40
• INLINECODE41
• INLINECODE42
• INLINECODE43
• INLINECODE44
• INLINECODE45

failed-items.jsonl

Write one JSON object per failed or blocked file with at least:

• - INLINECODE46
• INLINECODE47
• INLINECODE48
• INLINECODE49
• INLINECODE50
• INLINECODE51
• INLINECODE52
• INLINECODE53

MEMORY.candidate.md

Include:

• - batch header (batch_id, started_at, finished_at, source_directory or source_file)
• grouped knowledge summaries
• source references
• confidence notes
• items needing review

ingest-report.md

Include:

1. 1. Batch summary
2. Input scope
3. File counts and routing counts
4. Successful extraction summary
5. Failures and risks
6. Recommended next actions

Safety rules

• - Never invent text that was not extracted.
• If parsing fails, say so plainly and log it.
• Treat filenames as hints only, never as proof of document contents.
• Keep sensitive data out of MEMORY.candidate.md unless the workflow explicitly allows it.

Included files

• - run.py: minimal batch runner for local testing
• INLINECODE61: docx text extraction helper
• INLINECODE62: pdf text extraction helper
• INLINECODE63: sample output shapes and field guidance
• INLINECODE64: setup and usage notes