pdf-explorelisted

Use this skill when the user has attached or pointed to a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, pull tables out as CSV, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers �� including appendices). It parses the PDF once in Python: pdf_pages (pages as persistent text), pdf_outline (TOC), pdf_tables (deterministic table extraction with per-table page provenance), pdf_images (embedded figures at native resolution), and prepare/assemble helpers that fan whole-doc relevance scans / per-page maps / structured extraction out over Task subagents so the pages never fill your own context. Complementary to the built-in Read(pages=...), which attaches ≤20 PDF pages as ephemeral vision dropped after one turn — reach for this skill
emaballarin/ccplugins · ★ 3 · Data & Documents · score 77

Install: claude install-skill emaballarin/ccplugins

# PDF Explore — navigate a PDF too big to embed The built-in `Read(file_path=..., pages=[...])` attaches PDF pages as vision blocks — capped at ~20 pages/turn and **dropped from context after one turn**, so multi-section synthesis turns into re-reading the same pages over and over. And when the answer is "every page" (list all datasets / citations / figures mentioned anywhere), reading the whole document page-by-page is the expensive way to get it. This skill parses the PDF **once** into persistent per-page text, and — for whole-document work — runs **one cheap model call per page (or per batch) in parallel via Task subagents**, so the page text lives in files and subagent contexts, never in yours. You load only what matters, or sweep every page without putting the pages in your own context at all. `Read(pages=...)` and this skill are **complementary**: use `Read(pages=...)` for a one-off look at 1–4 pages you will quote in your very next reply; use this skill for persistent text, multi-section synthesis, whole-doc sweeps, and structured extraction. ## Loading the kernel The helpers live in `kernel.py` next to this file. It is **not** auto-injected — import it by path in a Bash `python` heredoc (zero import-time side effects, all heavy imports are lazy): ```bash python3 - <<'PY' import importlib.util K = "/ABSOLUTE/PATH/TO/pdf-explore/kernel.py" # this SKILL.md's directory + /kernel.py spec = importlib.util.spec_from_file_location("pdf_kernel", K) k = importlib.util.m