Markitdown
ImCa0/just-laws
Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.
Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
$ npx skills add seb1n/awesome-ai-agent-skills --skill pdf-processing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills pdf-processing --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/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/documents-and-files/pdf-processing .claude/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .claude/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processingType 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 seb1n/awesome-ai-agent-skills --skill pdf-processing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills pdf-processing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/documents-and-files/pdf-processing .agents/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .agents/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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 seb1n/awesome-ai-agent-skills --skill pdf-processing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills pdf-processing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/documents-and-files/pdf-processing .cursor/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .cursor/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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/seb1n/awesome-ai-agent-skills.git --path documents-and-files/pdf-processing--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 seb1n/awesome-ai-agent-skills --skill pdf-processing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills pdf-processing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/documents-and-files/pdf-processing .gemini/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .gemini/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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 seb1n/awesome-ai-agent-skills pdf-processingInstalls 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 seb1n/awesome-ai-agent-skills --skill pdf-processing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/documents-and-files/pdf-processing .github/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .github/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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 seb1n/awesome-ai-agent-skills --skill pdf-processing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills pdf-processing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/documents-and-files/pdf-processing .opencode/skills/pdf-processing && 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-processing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/documents-and-files/pdf-processing into .opencode/skills/pdf-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pdf-processing", 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.
pdf-processingInspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
PDF Processing is an agent skill from seb1n/awesome-ai-agent-skills. Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity. Use when working with one or more .pdf files; converting documents to or from PDF; extracting text, tables, images, metadata, forms, or page ranges; applying true redactions or signatures; diagnosing malformed, encrypted, scanned, or inaccessible PDFs; or validating that a PDF transformation preserved the intended content and layout.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `assets/processing-record-template.md` and `references/tool-routing.md`).
It sits in Documents & Office, covering PDF. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
PDF Processing loads about 2.5k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 133 tokens; SKILL.md has 1,214 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.
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); the scripts in this folder are not scanned.
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 1,214 words, ~2,492 tokens.
.claude/skills/pdf-processing/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.Preserve the original, choose tools from what is actually available, and verify both document structure and rendered appearance.
Collect or state:
Clarify ambiguous page references: human page labels may differ from zero- or one-based physical page numbers.
Return:
Do not claim exactness when the check was heuristic or a page could not be rendered.
python3 scripts/inspect_pdf.py /path/to/input.pdf --pretty
python3 scripts/inspect_pdf.py /path/to/input.pdf --output /path/to/report.json --prettyThis default scan reads bytes without invoking a PDF parser. With --output, it refuses input aliases and non-regular destinations, then atomically creates or replaces the report via a sibling temporary file. Use --deep only after the file is trusted enough to parse, or after the untrusted-input sandbox profile in step 2 is verified. Declare the decision explicitly:
python3 scripts/inspect_pdf.py /path/to/input.pdf --deep --trust-level trusted --pretty
python3 scripts/inspect_pdf.py /path/to/untrusted.pdf --deep --sandbox-profile-confirmed --prettyTreat JavaScript, launch actions, automatic actions, embedded files, and rich media as inert hazards; do not activate them.
Inventory installed tools and libraries before choosing a method. Read tool-routing.md for capability-based routing and fallback behavior. Prefer a tool that preserves the required features; a text extractor is not a page editor, and rasterization is not a faithful editable conversion.
For an untrusted PDF, parse or render only in a disposable, low-privilege sandbox with no secrets or network access; a read-only source mount; isolated temporary/output storage; CPU, memory, process, file-size, page, and time limits; and no host viewer, shell, URL-handler, or clipboard integration. Configure the parser/renderer to disable JavaScript, OpenAction/additional/launch actions, form submission, external URI fetching, attachment extraction/opening, rich media, and automatic font/resource downloads. Verify these controls for the exact tool/version. If the available parser or renderer cannot satisfy the profile, stop after raw-byte inspection and report the capability gap.
If no suitable dependency exists, explain the missing capability and propose an installation or alternate workflow. Do not install software or upload the PDF without permission.
Open or render a trusted original with a trusted local viewer before any layout-sensitive change. For an untrusted original, use only the verified sandbox profile from step 2; if it is unavailable, stop without parsing/rendering. Inspect representative pages and every page that will change. Record page count, dimensions/orientation, searchable text availability, form fields, annotations, bookmarks, attachments, encryption, and obvious font or image issues.
For scanned pages, determine whether OCR is needed. Preserve the original image layer unless the user explicitly requests destructive cleanup.
Work on a temporary output, then move or copy it to the final requested path only after verification.
Follow verification-checklist.md. At minimum:
Render every changed page and a representative sample of unchanged pages under the applicable trust/sandbox profile. Inspect at readable resolution for clipping, missing glyphs, shifted tables, broken images, blank pages, wrong rotation, and redaction leakage. For short or high-stakes documents, inspect every page. Open the final file in the user's intended viewer only when its trust classification and active-content controls permit it.
Use processing-record-template.md for complex or regulated work. Report output paths, hashes, verification performed, failures, and untested behavior. Retain temporary artifacts only as long as needed and delete them only when authorized.
If processing fails, preserve the source and failed output separately, capture the exact command/tool/version and error, and retry from the unchanged original. If the output was distributed before a defect was found, identify affected versions and recipients but do not recall or replace files without authorization. For suspected redaction leakage or signature/key exposure, stop distribution and escalate immediately.
Request: “Extract this 38-page scanned contract into searchable text with page citations.”
Hash and render the original, OCR with the stated language, preserve the PDF image layer, spot-check names/numbers on every page, flag low-confidence passages, and deliver text with physical page references and an OCR limitation note.
Request: “Combine these five PDFs in agenda order and add bookmarks.”
Confirm order and page mapping, merge to a new file, preserve orientation and page sizes, add bookmarks, re-open with a second reader, render boundary pages, and report final page count and hash.
Request: “Remove account numbers before this PDF is shared publicly.”
Define the identifier pattern and all affected pages, apply true redaction to a copy, remove scoped metadata/comments/attachments, search and inspect with an independent parser, render every redacted page, and state that visual boxes alone were not used.
© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files (scripts, references, assets) in documents-and-files/pdf-processing of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
PDF Processing 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 Processing this skillseb1n/awesome-ai-agent-skills | 206 | — | ~2.5k | Automated safety check: Pass | MIT | |
| MarkitdownImCa0/just-laws | 781 | 14 repos | ~3.2k | Automated safety check: Notes | MIT | |
| Gzh Designisjiamu/gzh-design-skill | 3.9k | 1 repos | ~2.2k | Automated safety check: Pass | AGPL-3.0 | |
| GenOffice Document CLIgenspark-ai/genoffice | 8.8k | — | ~19k | Automated safety check: Pass | Apache-2.0 | |
| Harness Book Best Practicewquguru/harness-books | 3.2k | — | ~4.1k | Automated safety check: Pass | None | |
| Bookforge Korean Ebook PDF Makergongnyang/bookforge | 314 | 1 repos | ~1.7k | Automated safety check: Pass | MIT |
ImCa0/just-laws
Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.
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…
genspark-ai/genoffice
Creates, converts, reads and edits real pptx, xlsx, docx and PDF files locally through the genoffice command line.
wquguru/harness-books
Best practices for working on the Harness books repo. An agent skill from wquguru/harness-books.
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.
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.
seb1n/awesome-ai-agent-skills
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings.
seb1n/awesome-ai-agent-skills
Build a preliminary, evidence-based EU AI Act readiness assessment across AI-system inventory, territorial scope, operator roles, prohibited-practice screening, risk classification, transparency…
seb1n/awesome-ai-agent-skills
Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows.
seb1n/awesome-ai-agent-skills
Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests.
seb1n/awesome-ai-agent-skills
Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk.
seb1n/awesome-ai-agent-skills
Inspect, profile, clean, reconcile, analyze, visualize, and verify spreadsheet data while preserving formulas, formatting, types, and source files.
Categories
Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity. PDF Processing is an agent skill from seb1n/awesome-ai-agent-skills. Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
PDF Processing fits situations like: working with one; more .pdf files; converting documents to; extracting text.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill pdf-processing -a claude-code`. Or copy the skill folder (documents-and-files/pdf-processing in seb1n/awesome-ai-agent-skills) into .claude/skills/pdf-processing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill pdf-processing -a codex`. Or copy the skill folder (documents-and-files/pdf-processing in seb1n/awesome-ai-agent-skills) into .agents/skills/pdf-processing in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill pdf-processing -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-processing, .gemini/skills/pdf-processing, .github/skills/pdf-processing and .opencode/skills/pdf-processing in your project.
Going by SKILL.md and its folder, PDF Processing needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
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.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
PDF Processing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with PDF Processing: Markitdown (ImCa0/just-laws, 781 stars), Gzh Design (isjiamu/gzh-design-skill, 3.9k stars), GenOffice Document CLI (genspark-ai/genoffice, 8.8k stars) and Harness Book Best Practice (wquguru/harness-books, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.