Split PDF
scunning1975/MixtapeTools
Download, split, and deeply read academic PDFs. An agent skill from scunning1975/MixtapeTools.
Get a PDF into the model without blowing the context window or losing structure.
Install PDF Ingestion
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Archive228/loopkit pdf-ingestion --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/pdf-ingestion .claude/skills/pdf-ingestion && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .claude/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Archive228/loopkit pdf-ingestion --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/pdf-ingestion .agents/skills/pdf-ingestion && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .agents/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Archive228/loopkit pdf-ingestion --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/pdf-ingestion .cursor/skills/pdf-ingestion && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .cursor/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Archive228/loopkit.git --path skills/pdf-ingestion--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Archive228/loopkit pdf-ingestion --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/pdf-ingestion .gemini/skills/pdf-ingestion && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .gemini/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Archive228/loopkit pdf-ingestionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/pdf-ingestion .github/skills/pdf-ingestion && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .github/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Archive228/loopkit --skill pdf-ingestion -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Archive228/loopkit pdf-ingestion --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Archive228/loopkit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/pdf-ingestion .opencode/skills/pdf-ingestion && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "pdf-ingestion" agent skill from https://github.com/Archive228/loopkit/tree/main/skills/pdf-ingestion into .opencode/skills/pdf-ingestion/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-ingestion", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
pdf-ingestion- GitHub stars
- 755
- Token cost
- ~969 tokens
- SKILL.md length
- 521 words
- Files
- 1
- Skills in repo
- 43
- Repo updated
- First seen
- Licence
- MIT
At a glance
Get a PDF into the model without blowing the context window or losing structure.
- Works in 3 steps: Native PDF input — pass the file… → Text extraction then send — pdftotext /… → Extract → chunk → summarize → send — for…
- Tasks that involve PDF
- SKILL.md covers Deciding which path, Native PDF — the good defaults, Extract-then-send — the traps and Extract → chunk → summarize…, plus 2 more sections
- Calls pdftotext
What it does
PDF Ingestion is an agent skill from Archive228/loopkit. Get a PDF into the model without blowing the context window or losing structure. Native PDF beats OCR-then-text for most cases; extract-then-summarize beats native for very long docs.
Its SKILL.md is about 970 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Documents & Office, covering PDF and Context engineering. The repository describes itself as: 33 battle-tested skills + minimal .claude harness for any coding agent (Claude Code, Cursor, Codex, Gemini CLI). The licence is MIT.
When your agent uses it
- Tasks that involve PDF
- Tasks that involve Context engineering
Example prompts
- “/pdf-ingestion”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Native PDF input — pass the file directly. Model sees pages as images + extracted text. Best for docs under ~100 pages with meaningful…
- Text extraction then send — pdftotext / pypdf / equivalent, then send the text. Loses layout but cheap. Fine for prose-heavy docs where…
- Extract → chunk → summarize → send — for docs >100 pages or when you'll query the same doc many times. Preprocess once, cache the summary.
What it can do on your machine
Read from SKILL.md and the folder at commit 5ae033e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pdftotext
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
PDF Ingestion loads about 969 tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 521 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Archive228/loopkit at commit 5ae033e, republished under its MIT licence (© Archive228). 521 words, ~969 tokens.
Download SKILL.mdSave it as
.claude/skills/pdf-ingestion/SKILL.md (or your agent's skills folder).- name
- pdf-ingestion
- description
- Get a PDF into the model without blowing the context window or losing structure. Native PDF beats OCR-then-text for most cases; extract-then-summarize beats native for very long docs.
- when_to_use
- user drops a PDF, "read this report", extracting tables/figures from a doc, long-form doc summarization, spec document that lives as PDF
PDF Ingestion
Three ways to feed a PDF to the model, in increasing order of preprocessing:
Native PDF input — pass the file directly. Model sees pages as images + extracted text. Best for docs under ~100 pages with meaningful layout (tables, figures, forms). Preserves structure.
Text extraction then send —
pdftotext/pypdf/ equivalent, then send the text. Loses layout but cheap. Fine for prose-heavy docs where tables don't matter.Extract → chunk → summarize → send — for docs >100 pages or when you'll query the same doc many times. Preprocess once, cache the summary.
Deciding which path
| Doc shape | Path |
|---|---|
| <20 pages, layout matters (report, form, invoice) | Native |
| <20 pages, pure prose (article, memo) | Text extraction |
| 20-100 pages, mixed | Native, but chunk if context tight |
| >100 pages | Extract → chunk → summarize |
| Scanned PDF (no text layer) | OCR first (Tesseract or vision model), then treat as extracted text |
| Tables are the point | Native — text extractors mangle tables |
| Figures/diagrams are the point | Native + explicit "describe the figure on page N" prompt |
Native PDF — the good defaults
- Cache the PDF at a prompt-caching breakpoint (see
prompt-caching). Native PDFs are large — every uncached turn costs full input price on the whole doc. - Ask about specific pages ("summarize section 3.2 on page 14") rather than the whole doc. The model handles targeted queries better than "summarize this 80-page report".
- Follow up with page-cited claims — "on which page does the doc say X?" — as a sanity check the model isn't hallucinating.
Extract-then-send — the traps
pdftotextreading order. Multi-column PDFs come out as interleaved lines. Usepdftotext -layoutfor column preservation, orpdftotext -rawfor straight reading order — pick per doc, don't guess.- Tables become word soup. If tables are load-bearing, native or per-table image extraction. Not text.
- Headers/footers repeat on every page. Strip them before sending, or the model will treat them as content.
- Footnotes drift to random positions in the extracted stream. Filter or accept the noise.
Show full SKILL.md (202 more words)Show less
Extract → chunk → summarize (long docs)
- Chunk by section, not by token count. A section-aware split respects the doc's logic; a naive 4K-token split cuts sentences and tables.
- Summarize per section into a "map" — 1-2 paragraphs each. Keep the map short enough to fit in context whole (~2-4K tokens for a 200-page doc).
- Store the full section text alongside the map (paths in a manifest). Fetch on demand when a question needs detail beyond the summary.
- Cache the map at a prompt-caching breakpoint so multi-turn Q&A over the doc doesn't reprocess.
Red flags
- Sending a 200-page PDF native to answer one question. Extract the relevant page range first.
- Trusting the text extractor on a form or invoice. Layout carries meaning. Use native.
- OCR'ing a PDF that already has a text layer. Check
pdftotext -q file.pdf -first — if text comes out, no OCR needed. - No page citations in output. Model can hallucinate confidently across long PDFs. Force page numbers into the response format.
- Re-uploading the same PDF every turn without caching. Cost climbs linearly; a 5-minute cache fixes it.
Loopkit-adjacent
If the PDF is a spec, extract it into PROMPT.md via spec-first — the agent should re-read prose, not re-scan the PDF, on every turn.
© Archive228, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/pdf-ingestion of Archive228/loopkit.
Open the folder on GitHubat commit 5ae033e
Compare with similar skills
PDF Ingestion next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| PDF Ingestion this skillArchive228/loopkit | 755 | — | ~969 | Automated safety check: Pass | MIT | |
| Split PDFscunning1975/MixtapeTools | 474 | 2 repos | ~2.9k | Automated safety check: Pass | None | |
| MarkitdownImCa0/just-laws | 781 | 14 repos | ~3.2k | Automated safety check: Notes | MIT | |
| Gzh Designisjiamu/gzh-design-skill | 4k | — | ~2.2k | Automated safety check: Pass | AGPL-3.0 | |
| GenOffice Document CLIgenspark-ai/genoffice | 9.2k | — | ~19k | Automated safety check: Pass | Apache-2.0 | |
| Harness Book Best Practicewquguru/harness-books | 3.2k | — | ~4.1k | Automated safety check: Pass | None |
Similar skills
Markitdown
ImCa0/just-laws
Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.
Gzh Design
isjiamu/gzh-design-skill
微信公众号文章排版引擎，将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取，自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入（非 Markdown…
GenOffice Document CLI
genspark-ai/genoffice
Creates, converts, reads and edits real pptx, xlsx, docx and PDF files locally through the genoffice command line.
Harness Book Best Practice
wquguru/harness-books
Best practices for working on the Harness books repo. An agent skill from wquguru/harness-books.
Bookforge Korean Ebook PDF Maker
gongnyang/bookforge
Produces book-style Korean ebook PDFs from a topic or finished manuscript, with six design styles, real book parts and quality-check gates before output.
More from Archive228/loopkit
All 43 skills in this repoHitl Escalate
Archive228/loopkit
Escalate blocked runs to a human via configured channel or fallback to BLOCKED.md and exit the loop.
Structured Output
Archive228/loopkit
Get JSON out of the model reliably. An agent skill from Archive228/loopkit.
Using Loopkit
Archive228/loopkit
A skill your agent uses when starting any conversation in a loopkit-enabled project - establishes how to find and use loopkit's 49 skills, requiring skill invocation before ANY response including…
Active Memory Reminder
Archive228/loopkit
Before compaction Loopkit extracts decisions into claude-decisions.json (machine-readable).
Eval Harness
Archive228/loopkit
Build a repeatable eval loop that grades agent output with an LLM judge, so prompt/skill changes get scored against a baseline instead of eyeballed.
Feature List JSON
Archive228/loopkit
Enumerate every end-to-end feature as strict JSON entries with passes:false, editable-passes-only discipline, and priority order.
Related
Categories
Questions about PDF Ingestion
What does PDF Ingestion do?
Get a PDF into the model without blowing the context window or losing structure. PDF Ingestion is an agent skill from Archive228/loopkit. Get a PDF into the model without blowing the context window or losing structure.
When should I use PDF Ingestion?
PDF Ingestion fits situations like: tasks that involve PDF; tasks that involve Context engineering.
How do I install PDF Ingestion in Claude Code?
Run `npx skills add Archive228/loopkit --skill pdf-ingestion -a claude-code`. Or copy the skill folder (skills/pdf-ingestion in Archive228/loopkit) into .claude/skills/pdf-ingestion in your project. Claude Code loads it when a task matches its description.
How do I install PDF Ingestion in Codex?
Run `npx skills add Archive228/loopkit --skill pdf-ingestion -a codex`. Or copy the skill folder (skills/pdf-ingestion in Archive228/loopkit) into .agents/skills/pdf-ingestion in your project. Codex loads it when a task matches its description.
Can I use PDF Ingestion in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Archive228/loopkit --skill pdf-ingestion -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pdf-ingestion, .gemini/skills/pdf-ingestion, .github/skills/pdf-ingestion and .opencode/skills/pdf-ingestion in your project.
What does PDF Ingestion need to run?
Going by SKILL.md and its folder, PDF Ingestion needs the command-line tools its instructions call (pdftotext).
Does PDF Ingestion access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is PDF Ingestion safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does PDF Ingestion use?
PDF Ingestion is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does PDF Ingestion use?
About 969 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to PDF Ingestion?
Skills that share tags, products or a category with PDF Ingestion: Split PDF (scunning1975/MixtapeTools, 474 stars), Markitdown (ImCa0/just-laws, 781 stars), Gzh Design (isjiamu/gzh-design-skill, 4k stars) and GenOffice Document CLI (genspark-ai/genoffice, 9.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains PDF Ingestion?
Archive228 (a GitHub user) maintains it in Archive228/loopkit, which has 755 GitHub stars. The repository holds 43 skills in this directory. The repository was last updated on July 14, 2026.
Source: Archive228/loopkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.