legal-scholarship-skills

Place pre-screened literature citations into a LaTeX or Word manuscript, or restyle the citations already in one. Three modes: (1) inline placement — inline \cite{}/\citet{}/\citep{} with a compiled references.bib, for author-date journals (APA, MLA, Harvard, Chicago author-date, IEEE, Vancouver); (2) footnote placement — full formatted \footnote{} or OOXML footnotes for legal and notes styles (Bluebook, OSCOLA, Chicago, APA, McGill) with Id./supra short forms; (3) restyle — convert existing footnote citations from one style to another. This skill is manual-invoke ONLY — trigger ONLY when the user explicitly runs /cite-placement or explicitly names the "cite-placement" skill. Do NOT auto-trigger on general citation, footnote, or reference requests.

Download the actual PDF binary from bot-gated sites (taxpolicycenter.org, urban.org, SSRN-hosted mirrors, think-tank/publisher sites) via the Wayback Machine id_ URL form. Use when: (1) curl/WebFetch of a .pdf URL returns HTML instead of a PDF even with a browser User-Agent, (2) pypdf fails with "invalid pdf header: b'<!DOC'" or "EOF marker not found" on a freshly downloaded file, (3) Firecrawl can parse the PDF to markdown but you need the original file on disk (e.g., filing a reference copy).

Convert between LaTeX and Microsoft Word for academic manuscripts in either direction, and assemble .tex from mixed sources. Fires on: converting .tex/LaTeX to Word/.docx ("tex to docx", "latex to word", "tex2docx", "convert to word", "pandoc convert"); converting .docx manuscripts to LaTeX for editing and back ("convert to latex", "manuscript", "footnotes", "reference doc", the docx-to-tex-to-docx round-trip / academic paper editing pipeline); high-fidelity delivery where plain pandoc loses tables, mangles cross-references, or fails on custom macros — booktabs/regression tables, OMML equations, cleveref, \estauto, \@@input, \thanks, TikZ, native Word tables, longtable, siunitx; and building .tex from mixed PDF/docx/LLM-generated sources. Replaces and reroutes the retired skills manuscript-editing-template-latex, latex-to-docx-fidelity, tex2docx, and latex-from-mixed-sources.

Master controller for the lit-review pipeline, driven by a document. Give it a .tex or .docx file describing an article — a full manuscript, an abstract, or a proposal — and it extracts a search plan, runs Undermind (an automated Playwright driver in Classic mode) and Google Scholar (SearchAPI.io), then merges, deduplicates, and screens the results. Only use this skill when explicitly requested — e.g., the user says "run lit-review-orchestrator", "lit-review-orchestrator", or "/lit-review-orchestrator". Do NOT auto-trigger on general literature review requests.

Convert Markdown (.md) files to a polished PDF with ALL images preserved and scaled to the page. Use whenever the user asks to "save this markdown as a PDF", "convert README.md to pdf", "export the .md as a pdf", "turn these notes/docs into a PDF", or wants a PDF deliverable of any GitHub-flavored Markdown document (README, design doc, report, notes) — especially when it contains images or diagrams (remote or local), tables, code blocks, or a linked table of contents. Pipeline: pandoc (GFM → standalone HTML with embedded resources) → headless Chrome print-to-pdf with a GitHub-like print stylesheet → pypdf verification that every referenced image is embedded. Do NOT use for .tex → PDF (use a LaTeX toolchain) or for .docx work (use word-docx / tex2docx).

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables/formulas from PDFs (including scanned and photographed documents), OCR, combining or merging multiple PDFs, splitting, rotating, watermarking, creating new PDFs, encrypting/decrypting, and extracting images. Routes between pypdf (fast born-digital text), pdfplumber (tables), opendataloader-pdf (born-digital complex layout with optional Docling hybrid), and LightOnOCR-2-1B (vision-LM OCR for scanned/photographed docs; dolphin v2 fallback). If the user mentions a .pdf file or asks to produce one, use this skill.

Unified skill for Microsoft Word .docx workflows: extracting comments or tracked changes, summarizing reviewer feedback, generating response-to-comments documents, building Word memos or reports, applying tracked edits, auditing OOXML internals, validating and repairing documents, accepting revisions, adding or resolving comments, converting legacy .doc files, unpacking or repacking .docx files, simplifying redline markup, rendering .docx to images, and building Word documents with tables of contents, multi-column layouts, or page-numbered headers and footers. Use whenever a task involves reading, reviewing, building, editing, or analyzing .docx files. Prefer this skill over ad-hoc python-docx or docx2python usage. Route PDFs, spreadsheets, presentations, Google Docs, and LaTeX-to-Word conversion pipelines to their dedicated skills.

Produce a detailed .md plan for an academic article that a separate drafter agent then writes section-by-section in LaTeX. This is the academic-writing analog of the superpowers brainstorming → writing-plans workflow: it first interviews the user one question at a time (thesis, contribution, article type, structure, scope), gets approval on a skeleton, then emits a task-decomposed plan that hands off to a fresh section-drafter subagent and downstream to lit-review-orchestrator, cite-placement, and, when it is installed, style-emulation. Use this whenever the user wants to plan, outline, structure, or scaffold a paper before drafting, or asks for 'a plan for a drafter', 'an article plan', 'a paper outline to draft from', 'plan this paper', or 'write up a plan for this article' — even if they don't say the skill name. Also use it in REVISION MODE when the user wants an existing draft restructured or substantively revised (reorganize sections, change or sharpen the argument, conform a manuscript to a genre struc