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.
git clone --depth 1 https://github.com/Shan-Zhu/shuck-fileWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/shan-zhu/shuck-file/shuck)<a href="https://agentmods.dev/commands/shan-zhu/shuck-file/shuck"><img src="https://agentmods.dev/badge/commands/shan-zhu/shuck-file/shuck/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/shan-zhu/shuck-file/shuck"><img src="https://agentmods.dev/badge/commands/shan-zhu/shuck-file/shuck.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00025 | $0.00442 |
| Opus 5 | $0.00013 | $0.00221 |
| Sonnet 5 | $0.00005 | $0.00088 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
shuck 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 11d 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
/shuck
Convert a document to Markdown and display the result.
Instructions
Step 1: Validate the file
Check that the file exists and has a supported extension (.docx, .pdf, .xlsx, .pptx, .csv).
Step 2: Install dependencies if needed
If the conversion fails due to a missing dependency, install it:
pip install <package>
Packages by format:
- .docx →
python-docx - .pdf →
pdfplumber - .xlsx →
openpyxl - .pptx →
python-pptx - .csv → no extra dependency
Step 3: Convert
Run shuck. It auto-detects file size and picks the best mode:
python "{{PLUGIN_DIR}}/shuck.py" "<path>"
- Small files: outputs full Markdown directly
- Large files: outputs a document map with sections and suggested next steps
Step 4: Follow up
If the result is a map (large file), follow the suggested next steps based on the user's needs:
# Extract specific sections
python "{{PLUGIN_DIR}}/shuck.py" "<path>" --sections s1,s3
# Search within document
python "{{PLUGIN_DIR}}/shuck.py" "<path>" --grep "keyword"
# Tables only
python "{{PLUGIN_DIR}}/shuck.py" "<path>" --tables-only
# Compress to fit budget
python "{{PLUGIN_DIR}}/shuck.py" "<path>" --budget 4000
# Force full output
python "{{PLUGIN_DIR}}/shuck.py" "<path>" --all
Step 5: Present the result
Display the Markdown content. If the user had a specific request (summarize, extract data, answer questions), do that with the converted content.
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.
- 11d ago First seen · 65 lines · 25 tokens per session scan A 6442bd65cc61
shuck is a command published in the GitHub repository Shan-Zhu/shuck-file (6 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 442 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 2026-08-31.
Other commands, from other repositories
doc
A document parser that converts text-based PDF, Word, and Excel files into Markdown or JSON. It can extract headings, tables, pages, and worksheets, but it does not read scanned images.
convert
Use when the user attaches a bank statement PDF or asks for CSV/XLSX/QBO/Xero export of a converted statement. Do not use for spending analysis, reconciliation, or benchmark scoring — those have their own skills.
generate-report
A command for generating SEO and GEO analysis reports in Markdown, HTML, PDF, JSON, or Excel. SEO concerns search-engine visibility; GEO concerns how readily content appears in generative-AI search results.
batch-fill
Fill a form once per row of a CSV with Emboss.
read-summary
A document-reading command that creates summaries from Word, PDF, EPUB, and Excel files.
faostat-analytical-brief
Produce a FAOSTAT-style multi-page analytical brief (PDF + xlsx appendix).