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 skills add kennethkhoocy/legal-scholarship-skills --skill latex-to-wordgit clone --depth 1 https://github.com/kennethkhoocy/legal-scholarship-skillsWrote 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/skills/kennethkhoocy/legal-scholarship-skills/latex-to-word)<a href="https://agentmods.dev/skills/kennethkhoocy/legal-scholarship-skills/latex-to-word"><img src="https://agentmods.dev/badge/skills/kennethkhoocy/legal-scholarship-skills/latex-to-word/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/skills/kennethkhoocy/legal-scholarship-skills/latex-to-word"><img src="https://agentmods.dev/badge/skills/kennethkhoocy/legal-scholarship-skills/latex-to-word.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 | $0.00228 | $0.01764 |
| Opus 5 | $0.00114 | $0.00882 |
| Sonnet 5 | $0.00046 | $0.00353 |
| Haiku 4.5 | $0.00023 | $0.00176 |
Grade A, and why
latex-to-word 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 12d 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.
This is a copy
100% identical to latex-to-word — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LaTeX ↔ Word
This skill moves academic manuscripts between LaTeX and Microsoft Word and
assembles .tex from heterogeneous sources. It consolidates four former skills
into three workflows: a footnote-preserving round-trip for co-author editing
cycles, a high-fidelity one-way .tex → .docx engine for delivering finished
papers to Word-only journals or coauthors, and a set of knowledge patterns
for building a single .tex from PDF/docx/LLM-generated content. Read the deep
doc for the workflow you need before running anything.
Routing
| User intent | Workflow | Entry point | Deep doc |
|---|---|---|---|
| Deliver a finished LaTeX paper as high-fidelity Word (regression tables, math, cross-references must survive) | B — one-way tex→docx | scripts/convert.py |
references/tex-to-docx-engine.md |
| Iterate on a manuscript with Word-based co-authors while editing in LaTeX (docx→tex→docx, footnotes preserved) | A — round-trip | gui.py, or scripts/docx_to_tex.py + scripts/tex_to_docx.py |
references/roundtrip.md |
Build a .tex from PDF / .docx / LLM-generated text |
C — assemble from mixed sources | knowledge patterns (no scripts) | references/mixed-sources.md |
Which workflow
- B is the default for "deliver my LaTeX paper as Word." The fidelity engine
builds native Word tables, OMML equations, real footnotes, embedded figures,
and resolves
\cref/\Cref/\eqreffrom the.aux. Use B whenever the paper has regression/booktabs tables, math, or cross-references that must survive — plain pandoc drops or mangles all of these. - A is for iterating with Word-based co-authors while you edit in LaTeX. Its
tex → docxstep is plain pandoc plus a style-templatedscripts/reference.docx(fast, formatting-only), so it does not build native tables or resolve crefs. Choose A when the exchange is prose and footnotes and speed matters; switch to B once the document depends on tables/math/cross-references. - C is knowledge-only — patterns for a pipeline that emits
.tex, applied when you author the pipeline. No script to invoke.
What ships with it
60 files 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.
- convert_bracket_footnotes.py 4.3 KB runs code
- gui.py 25 KB runs code
- README.md 11 KB
- references/mixed-sources.md 4.4 KB
- references/roundtrip.md 12 KB
- references/tex-to-docx-engine.md 20 KB
- scripts/assemble.py 334 B runs code
- scripts/build_all_estout.py 364 B runs code
- scripts/build_fulltabular.py 3.9 KB runs code
- scripts/cleanup_tex.py 1.8 KB runs code
- scripts/combine_sections.py 3.3 KB runs code
- scripts/convert.py 174 KB runs code
- scripts/crop_white.py 599 B runs code
- scripts/detect_rules.py 1.3 KB runs code
- scripts/docx_to_tex.py 1.8 KB runs code
- scripts/extract_tables.py 1.0 KB runs code
- scripts/fix_quotes.py 3.1 KB runs code
- scripts/full_tabular_to_docx.py 32 KB runs code
- scripts/gen_reference.py 4.9 KB runs code
- scripts/gen_test_docx.py 16 KB runs code
- scripts/inspect_lastrow.py 742 B runs code
- scripts/mhchem_unicode.py 5.8 KB runs code
- scripts/pdf_to_png.py 441 B runs code
- scripts/postprocess_docx.py 4.3 KB runs code
- scripts/reference.docx 11 KB
- scripts/render_all_pages.py 461 B runs code
- scripts/render_latex_env.py 8.0 KB runs code
- scripts/render_ref.py 1.1 KB runs code
- scripts/siunitx_expand.py 7.2 KB runs code
- scripts/tex_table_to_docx.py 14 KB runs code
- scripts/tex_to_docx.py 3.9 KB runs code
- scripts/toolcheck.py 3.4 KB runs code
- tests/qa_metrics.py 15 KB runs code
- tests/run_tests.py 11 KB runs code
- tests/t01_booktabs/t01_booktabs.tex 1.5 KB
- tests/t02_longtable/t02_longtable.tex 5.5 KB
- tests/t03_tabularx_multirow/t03_tabularx_multirow.tex 1.5 KB
- tests/t04_threeparttable/t04_threeparttable.tex 1.0 KB
- tests/t05_siunitx/t05_siunitx.tex 1.1 KB
- tests/t06_math/t06_math.tex 1.4 KB
- tests/t07_lists/t07_lists.tex 1.5 KB
- tests/t08_subfigures/t08_subfigures.tex 937 B
- tests/t09_natbib_cite/refs.bib 725 B
- tests/t09_natbib_cite/t09_natbib_cite.tex 1.1 KB
- tests/t10_biblatex/refs.bib 956 B
- tests/t10_biblatex/t10_biblatex.tex 832 B
- tests/t11_twocolumn/t11_twocolumn.tex 2.0 KB
- tests/t12_mixed/refs.bib 706 B
- tests/t12_mixed/t12_mixed.tex 7.2 KB
- tests/t13_wrapfig/s13_wrapfig.tex 2.5 KB
- tests/t14_multicol/s14_multicol.tex 2.1 KB
- tests/t15_listings/s15_listings.tex 2.2 KB
- tests/t16_hyperref/s16_hyperref.tex 2.2 KB
- tests/t17_frontmatter/s17_frontmatter.tex 2.4 KB
- tests/t18_resizebox_wide/s18_resizebox_wide.tex 1.7 KB
- tests/t19_complex_merge/s19_complex_merge.tex 1.7 KB
- tests/t20_enumitem/s20_enumitem.tex 1.8 KB
- tests/t21_acronyms/s21_acronyms.tex 1.6 KB
- tests/t22_tcolorbox/s22_tcolorbox.tex 1.6 KB
- tests/t23_tikz/paper.tex 3.4 KB
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.
- 12d ago First seen · 130 lines · 228 tokens per session scan A 5a4b86f2d510
latex-to-word is a skill published in the GitHub repository kennethkhoocy/legal-scholarship-skills (9 stars, last pushed 7d ago), licensed MIT. It adds 228 tokens to every session and 1,764 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to latex-to-word, differing in 0 lines, and is treated as a copy.
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