Claude With Skills is a progressive course that teaches developers to create reusable, portable Agent Skills for Claude Code, from basic SKILL.md files to advanced automation and plugin packaging. It is intended for developers who want repeatable instructions and workflows instead of repeatedly pasting the same guidance. The catalogue contains the course's skills, agents, and instruction.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add davila7/claude-with-skills --skill pdf-toolkitgit clone --depth 1 https://github.com/davila7/claude-with-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/davila7/claude-with-skills/pdf-toolkit)<a href="https://agentmods.dev/skills/davila7/claude-with-skills/pdf-toolkit"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/pdf-toolkit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/davila7/claude-with-skills/pdf-toolkit"><img src="https://agentmods.dev/badge/skills/davila7/claude-with-skills/pdf-toolkit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.00462 |
| Opus 5 | $0.00023 | $0.00231 |
| Sonnet 5 | $0.00009 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
pdf-toolkit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Process PDF files using the bundled scripts.
Capabilities
- Text extraction: read text content from any PDF page or page range → see extraction guide for multi-column layouts, page ranges, table extraction, and OCR limitations
- Form filling: fill PDF form fields programmatically and flatten the result → see forms guide for listing fields, setting values, checkboxes, radio buttons, and flattening
- Merging and splitting: combine multiple PDFs, reorder pages, add bookmarks, or split into individual pages → see merging guide for all merge and split operations
Quick reference
| Task | Command |
|---|---|
| Extract all text | python3 ${CLAUDE_SKILL_DIR}/scripts/extract.py <input.pdf> |
| Extract page range | python3 ${CLAUDE_SKILL_DIR}/scripts/extract.py <input.pdf> --pages 2-5 |
| Fill form | python3 ${CLAUDE_SKILL_DIR}/scripts/fill_form.py <input.pdf> <output.pdf> field=value ... |
| Merge PDFs | python3 ${CLAUDE_SKILL_DIR}/scripts/merge.py <out.pdf> <in1.pdf> <in2.pdf> ... |
Instructions
- Identify which operation the user needs: extraction, form filling, or merging/splitting.
- Read the relevant reference file for detailed instructions and edge case handling.
- Run the appropriate script from
${CLAUDE_SKILL_DIR}/scripts/. - If a required library (
pypdf,pdfplumber) is not installed, offer to install it withpip install <library>before retrying. - Report the output file path or print the extracted text to the user.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 32 lines · 47 tokens per session scan A 636d6c49f259
pdf-toolkit is a skill published in the GitHub repository davila7/claude-with-skills (12 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 462 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
pdf-extract-create-workflow
Complete PDF lifecycle: download, extract, and generate structured documents with reportlab.
document-direct-python
Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports.
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.