Install
$ agentstack add skill-daymade-claude-code-skills-feishu-doc-scraper ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Feishu Doc Scraper
Extract a Feishu/Lark source into faithful local Markdown. Prefer the lark-cli API — it extracts the body programmatically (no model paraphrasing), follows a collection's reference graph, and reads permission boundaries from error codes instead of guessing. Treat the rendered browser page as a fallback, not the source of truth: in real collection-scraping work the API path consistently does the whole job while the browser path is never needed.
Scope (read this first)
This skill's contract is faithful per-source Markdown + a record of what was extracted. It does not decide how the resulting files are named, indexed, deduplicated against existing notes, or organized into a knowledge base — that belongs to the host PKM / the user's own conventions. Stopping at faithful extraction keeps this skill orthogonal and reusable. When the user wants the output filed into a vault, extract first, then hand the clean Markdown to their organizing workflow.
Choose the path
Is the source a Feishu/Lark URL (wiki / docx / sheets / minutes / base)?
├── YES → is lark-cli installed and authenticated to that tenant?
│ ├── YES → PATH A: lark-cli API extraction (primary — start here)
│ │ └── hit code 131006 / 99991679 (permission denied)?
│ │ └── PATH B: owner-exported .docx → faithful Markdown
│ └── NO → install/auth lark-cli first (it is worth it); only if
│ truly impossible → PATH D: browser DOM fallback
├── the URL is a Minutes / 妙记 link, or a doc references one → PATH C: Minutes transcript
└── you were handed an exported .docx (not a URL) → PATH B
A collection/hub is just a docx whose body references other docs — Path A handles it by recursively following the reference graph, not by visiting pages in a browser.
Path A — lark-cli API extraction (primary)
Full command catalog, recursion engine, cross-tenant and personal-space nuances: [references/lark-cli-api-extraction.md](references/lark-cli-api-extraction.md). The essentials for the common case:
1. Disable the proxy for Feishu domestic domains. Feishu's *.feishu.cn endpoints are direct-connect in mainland China; routing them through a local proxy leaks credentials through the proxy and gets DNS-hijacked. lark-cli itself warns about this. Always:
export LARK_CLI_NO_PROXY=1
This does not conflict with any "Claude/Anthropic domains must use the proxy" rule — Feishu is a different host and is direct.
2. Classify the URL, then resolve to a fetchable doc token.
…/wiki/— a wiki node token is not a doc token. Resolve it first:
``bash lark-cli wiki spaces get_node --params '{"token":""}' # → .data.node.obj_token and .data.node.obj_type (e.g. "docx") ``
…/docx/— already a doc token, fetch directly.…/sheets/— spreadsheet, use the sheets commands (see reference).…/minutes/— Minutes, go to Path C.
3. Fetch the body programmatically — never via the model. The body field moved across lark-cli versions, so probe both rather than hard-coding one (this keeps working whichever version is installed):
lark-cli docs +fetch --doc --format json > /tmp/fetch.json 2> /tmp/fetch.err
# ≤1.0.32: clean Markdown in .data.markdown.
# 1.0.55: body moved to .data.document.content as HTML (.data.markdown is null).
if jq -e -r '.data.markdown // empty' /tmp/fetch.json > source.md && [ -s source.md ]; then
: # got clean Markdown directly
else
jq -r '.data.document.content' /tmp/fetch.json | pandoc -f html -t gfm > source.md
fi
--format markdown is not a valid value (lark-cli warns and falls back to json). Keep stdout and stderr separate — a harmless [deprecated] line goes to stderr, and piping 2>/dev/null and jq together produced a false Exit code 5 in practice. The body must reach disk via jq/pandoc, never retyped or summarized by the model — paraphrasing silently corrupts source text, the single most important fidelity rule. (pandoc only re-renders HTML structure to Markdown; it does not rewrite prose, so fidelity holds.)
4. If it's a collection/hub, follow the reference graph (BFS). The hub body contains `, , ` tags and cross-tenant / Minutes / Tencent-Meeting URLs. Extract every reference, dispatch by type, fetch, and repeat on each newly fetched doc until no new references remain (leaf nodes). Use the bundled extractor so nothing is silently missed (a missed reference = a missing document, the #1 hub-scraping failure):
python3 scripts/feishu_extract_refs.py source.md # → JSON list of {type, token, title}
Recursion loop, dispatch table, and the cross-tenant/my.feishu.cn personal-space rules are in the reference.
5. Final residual-tag check (acceptance gate for collections). Every rich-media reference must have been resolved and rendered:
grep -rlE '` tokens from a docx — exhaustively verified. Register the image tokens and note "needs document owner to right-click → save"; the text is the value, images are a tracked gap.
- **HTTP 200 from anonymous curl ≠ accessible.** A Feishu login wall returns 200 with a body containing `accounts.feishu.cn` / `login` / `passport` / an empty ``. Check the body, never infer "public" from the status code.
- **A file "not found" by a search agent is not authoritative.** Verify against authoritative sources before concluding (this is general Inference Discipline; relevant when locating where ingested content already lives).
- **U+FFFD final check on every produced file:** `LC_ALL=C grep -rl $'\xef\xbf\xbd' .` must be empty. A replacement character means an encoding step corrupted the text.
## Acceptance contract
Stop only when all that apply are true:
- Every fetched body reached disk via `jq`/script, not retyped by the model.
- Collections: the residual rich-media-tag grep (Path A step 5) is empty — every `mention-doc`/`sheet`/cross-tenant reference was followed to a leaf.
- `LC_ALL=C grep -rl $'\xef\xbf\xbd' .` is empty.
- docx path: rendered to an image and visually compared to the source; heading hierarchy and highlights match (see docx reference's checklist).
- Browser fallback only: TOC coverage + scale check (see browser-failure-rules.md).
- Each output file's frontmatter records `source` (the original URL/token) and, if any post-processing was applied, a `post_process` provenance line.
- Permission gaps (131006 docs not exported yet, undownloadable images) are explicitly listed for the user — a transparent gap beats a silent omission.
## Do NOT attempt
Verified dead-ends — retrying them only wastes the session. Full table with failure modes and root causes: **[references/permission-and-failure-boundaries.md](references/permission-and-failure-boundaries.md)**. The top ones:
- Bypassing `131006` permission-denied by any means (lark-cli / curl / anonymous browser) — it is a server-side boundary.
- Downloading docx embedded images via `docs +media-download`, `api …/drive/v1/medias//download` (with or without `extra`), or `schema drive.medias.download` — none work; lark-cli even mis-reports the real HTTP 400 as "empty JSON".
- `WebFetch` against `open.feishu.cn/document/server-docs/...` for API specs — backend is flaky; use `open.feishu.cn/llms-docs/zh-CN/llms-.txt` instead (LLM-friendly, stable).
- AppleScript/JXA `executeJavaScript`, Chrome CDP on port 9222 — disabled/empty in this environment (browser path only).
- Using `minimax-docx` to convert docx→md — it is a docx *authoring* tool; use the doc-to-markdown skill instead.
## Bundled resources
- `scripts/feishu_extract_refs.py` — deterministic reference-token extractor; the recursion engine's core. Run it on every fetched body to enumerate ``/``/``/cross-tenant/Minutes/Tencent-Meeting references as JSON.
- `scripts/restore_docx_headings.py` — for Path B: reads true font sizes via python-docx, maps them to heading levels, restores `w:shd` highlights to Obsidian `==…==`, without retyping body text.
- `scripts/feishu_dom_capture.js` — Path D: injectable end-to-end browser DOM capture.
- `scripts/download_feishu_images.py` — Path D: SSR image extraction when browser automation is unavailable.
- `scripts/build_feishu_markdown.py` — Path D: render a capture manifest into Markdown.
- `scripts/check_heading_coverage.py` — coverage verification (both paths).
- `references/lark-cli-api-extraction.md` — Path A full reference (commands, recursion, sheets, cross-tenant).
- `references/feishu-minutes-transcript.md` — Path C native transcript API + scope auth.
- `references/permission-and-failure-boundaries.md` — error codes + the full Do-NOT-attempt table.
- `references/docx-export-to-markdown.md` — Path B faithful conversion procedure.
- `references/browser-dom-fallback.md` + `references/browser-failure-rules.md` — Path D.
- `references/capture-manifest.md` — manifest shape for `build_feishu_markdown.py`.
## Next step
After extraction completes, the clean Markdown typically feeds the user's own knowledge-base ingestion (filing, indexing, dedup) — which is deliberately out of this skill's scope. If the source went through Path B (a docx), the doc-to-markdown skill is already part of that flow. Offer the handoff; do not auto-organize:
Extraction complete: [N] sources → faithful Markdown ([M] permission/image gaps listed).
Options: A) Hand off to your PKM/organizing workflow — file & index these (Recommended if part of a vault) B) Run /daymade-docs:docs-cleaner — consolidate redundant content across the extracted files C) Stop here — the faithful Markdown is the deliverable
## Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- **Author:** [daymade](https://github.com/daymade)
- **Source:** [daymade/claude-code-skills](https://github.com/daymade/claude-code-skills)
- **License:** MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.