القائمة
Comprehensive PDF manipulation - merge, split, rotate, extract pages, add watermarks, compress, and encrypt PDFs programmatically.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.
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Use br (beads_rust) as the local issue tracker for AI coding agents. Trigger when the user mentions issues, tickets, backlog, triage, dependencies, blocking, ready work, or any task involving tracking work items in a git repo. Also trigger when the user wants to plan work, pick next tasks, manage a dependency graph of issues, or coordinate across multiple agents. Use this skill for commands like br create, br ready, br close, br dep, br sync, and any br CLI interaction. Even if the user just says "what should I work on next" or "create a ticket for this", use this skill to ensure correct br usage patterns.
Design and implement practical AI agents using a production-oriented framework. Use this skill whenever the user wants to build an AI agent, decide whether a workflow should become an agent, choose between single-agent and multi-agent designs, define tools/instructions/guardrails, add human-in-the-loop controls, or scaffold an agentic workflow for real systems. Trigger for requests about agents, copilots, tool-using assistants, orchestration, handoffs, manager-worker patterns, agent guardrails, or productionizing multi-step LLM workflows even when the user does not explicitly ask for an “agent architecture.”
Generate or discover a CLI + AgentSkill for any REST API. Use when: user says 'create a CLI for X', 'wrap this API', 'search if a CLI exists', 'install an existing CLI', 'make a skill for X', 'publish my CLI', 'publish to npm', 'push to github'. Handles registry search, install, discovery, scaffolding, resource implementation, building, linking, skill generation, npm publishing, and GitHub publishing.
| name | pdf-toolkit |
| description | Comprehensive PDF manipulation - merge, split, rotate, extract pages, add watermarks, compress, and encrypt PDFs programmatically. |
Comprehensive PDF manipulation toolkit for merging, splitting, rotating, and more.
from pdf_toolkit import PDFToolkit
toolkit = PDFToolkit()
# Merge PDFs
toolkit.merge(['doc1.pdf', 'doc2.pdf'], 'merged.pdf')
# Extract pages
toolkit.load('document.pdf').extract_pages([1, 3, 5], 'extracted.pdf')
# Add watermark
toolkit.load('document.pdf').watermark('CONFIDENTIAL', output='watermarked.pdf')
# Merge
python pdf_toolkit.py merge file1.pdf file2.pdf --output merged.pdf
# Split
python pdf_toolkit.py split document.pdf --pages 10 --output chunks/
# Rotate
python pdf_toolkit.py rotate document.pdf --angle 90 --pages 1-5 --output rotated.pdf
# Watermark
python pdf_toolkit.py watermark document.pdf --text "DRAFT" --output watermarked.pdf