Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hkuds/openspace/docx-read-fallbacknpx skills add HKUDS/OpenSpace --skill docx-read-fallbackgit clone --depth 1 https://github.com/HKUDS/OpenSpaceWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.00581 |
| Opus 5 | $0.00013 | $0.00291 |
| Sonnet 5 | $0.00005 | $0.00116 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
docx-read-fallback scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
DOCX Read Fallback
When read_file or execute_code_sandbox fails to read .docx files, use run_shell with python-docx as a reliable workaround.
When to Use
read_filefails, times out, or returns errors on.docxfilesexecute_code_sandboxattempts to read the docx fail- You need to extract text content from a Word document
- Multiple standard approaches have been exhausted
How to Use
Basic Text Extraction
python -c "import docx; doc = docx.Document('path/to/file.docx'); print('\n'.join([p.text for p in doc.paragraphs]))"
Using run_shell Tool
run_shell command="python -c \"import docx; doc = docx.Document('path/to/file.docx'); print('\n'.join([p.text for p in doc.paragraphs]))\"" timeout=60
Extract Paragraphs with Indices
python -c "import docx; doc = docx.Document('file.docx'); [print(f'P{i}: {p.text}') for i, p in enumerate(doc.paragraphs) if p.text.strip()]"
Extract Tables
python -c "import docx; doc = docx.Document('file.docx'); [[print([[cell.text for cell in row.cells] for row in table.rows]) for table in doc.tables]]"
Extract Headings (by style)
python -c "import docx; doc = docx.Document('file.docx'); [print(p.text) for p in doc.paragraphs if p.style.name.startswith('Heading')]"
Prerequisites
Ensure python-docx is available:
python -c "import docx; print('docx available')"
If not installed:
pip install python-docx
Tips
- Use absolute paths to avoid working directory issues
- Set appropriate
timeout(30-60 seconds for large documents) - Escape quotes properly when embedding in shell commands
- For large documents, extract content in chunks or filter by paragraph index
- This approach bypasses file type detection issues in read_file
Example Workflow
- Try
read_fileon the .docx file - If it fails, verify python-docx availability
- Use
run_shellwith the python-docx extraction command - Parse the stdout to get document content
- Proceed with your analysis using the extracted text
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 77 lines · 25 tokens per session scan A 238a7ac92c89
docx-read-fallback is a skill published in the GitHub repository HKUDS/OpenSpace (7,486 stars, last pushed 21d ago), licensed MIT. It adds 25 tokens to every session and 581 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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