read_file's .ipynb extraction previously dropped cell outputs entirely,
so a notebook's training logs, tracebacks, and printed results were
invisible to the model. Ported LobeHub's token-efficient conversion:
- stream text and error tracebacks are kept (ANSI-stripped, \r
progress-bar rewrites collapsed to the final frame)
- execute_result/display_data prefer text/plain over the HTML twin
- base64 images become sized placeholders ([image/png output — 3 KB,
omitted]); widget state and script-bearing HTML are omitted
- legacy nbformat v3 pyout/pyerr flat-field shapes handled
- per-cell output block capped at 20k chars
The coverage warning listed bare page ranges, which tells the agent
WHERE the gaps are but not WHAT they contain — its only options were
guessing or OCRing everything. Each gap is now labeled with the last
text extracted before it (usually a section divider page), so the agent
can decide which gaps it actually needs and render/OCR only those.
Gap list capped at 20 entries with a summary line for pathological
alternating documents.
anydoc converts the PDF text layer only and emits no image placeholders
or page markers, so a mostly-scanned PDF extracts 'successfully' into
section headers with empty bodies — silent data loss the model cannot
detect. Count per-page text via poppler pdftotext and prepend an
EXTRACTION COVERAGE WARNING naming the empty pages and the recovery
path (pdftoppm + vision_analyze, or the ocr-and-documents skill).
Found on a 311-page HOA resale package where 198 scanned pages
(CC&Rs, Bylaws, Articles, insurance certs) vanished without a trace.
The anydoc path from #79781 passed every covered file straight to
to_markdown with no pre-check. anydoc loads the whole document through
its Rust core and the read_file char budget only applies after
conversion, so one large PDF or deck could pin a tool turn and spike
RAM.
_extract_anydoc now rejects inputs over MAX_ANYDOC_BYTES (50 MB) with
ExtractionError before calling the converter, which routes them to the
existing read_file fallthrough instead of converting. No timeout is
added: the conversion is a synchronous Rust call that cannot be
cancelled from Python, so a thread-based deadline would bound the wait
but leave the RAM burn running in the background.
The first _anydoc() load cached None on any failure (network blip,
missing wheel, pip race), so one bad first try disabled document
extraction for the rest of the process. Long-lived gateway and desktop
workers never recovered.
Failed loads now cool down for ANYDOC_RETRY_SECONDS and retry instead
of sticking, and a lock serializes first use so parallel readers cannot
double-install or race a failure into the cache. Successful loads are
still cached for the process lifetime.
read_file's auto-extraction covered only the stdlib trio (.ipynb/.docx/
.xlsx). firecrawl-anydoc (MIT, Rust core, imports as `anydoc`) converts
Word, PowerPoint, Excel — including legacy .doc/.ppt/.xls — OpenDocument,
RTF, EPUB, and PDF to clean Markdown through one shared document model.
Wiring follows the footprint ladder: no new tool, no hard dependency.
- tools/read_extract.py gains an ANYDOC_EXTENSIONS set that is active
only when the converter imports; the stdlib extractors remain
authoritative for their three formats so behavior is identical with
or without the package.
- tools/lazy_deps.py adds tool.doc_extract (firecrawl-anydoc==0.1.6),
installed on first read of such a file with prompt=False so read_file
can never block. Lazy-only for now: the package's first release was
2026-08-04, inside uv's 14-day exclude-newer quarantine, so the
mirrored pyproject extra lands after it clears.
- Any anydoc ConvertError maps to ExtractionError, falling back to the
existing path/binary handling instead of erroring the tool.
Tests: real-binding suite skips cleanly when the wheel is absent
(verified: 15 passed/3 skipped without it, 18 passed with it), plus an
absent-dep contract class that pins the fallback regardless of local
install state.
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