Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
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 daymade/claude-code-skills --skill photo-to-scanned-pdfgit clone --depth 1 https://github.com/daymade/claude-code-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/daymade/claude-code-skills/photo-to-scanned-pdf)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/photo-to-scanned-pdf"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/photo-to-scanned-pdf/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/daymade/claude-code-skills/photo-to-scanned-pdf"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/photo-to-scanned-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 54 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
- medium MCP Rug Pull · line 98 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
- medium MCP Rug Pull · line 114 uvx/uv tool run commands without ==version create a rug-pull risk.Fix: Pin the version: uvx package-name==1.2.3
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 | $0.00249 | $0.02331 |
| Opus 5 | $0.00125 | $0.01166 |
| Sonnet 5 | $0.00050 | $0.00466 |
| Haiku 4.5 | $0.00025 | $0.00233 |
Grade A, and why
photo-to-scanned-pdf 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Photo → Scanned PDF
Two related pipelines, same destination look, different starting point: phone photos of paper documents, or a digital document that needs a synthetic signature before it looks signed. The pipelines that work, and the failure modes that ship wrong PDFs if skipped.
Which one do you need?
| The input is... | Use |
|---|---|
| Phone photos of an already-signed/stamped paper document | This file, main pipeline below |
| A digital document (docx/PDF) with no signature yet, and you need to make it look hand-signed | references/digital-signature-synthesis.md |
photos ──► rectify (photo_to_scan.py --raw)
──► ORDER BY CONTENT, detect colored paper ← agent eyes, not filenames
──► enhance: noteshrink (white batch with -g │ colored pages separately,
after white-balance pre-pass)
──► assemble_pdf.py → A4 PDF
──► make_contact_sheet.py → READ IT, verify EVERY page ← mandatory
Division of labor: scripts carry execution; you (the agent) carry the two judgment steps — content-based page ordering, and whole-document verification. Neither can be automated away: filenames lie about order, and per-page spot checks miss wrong-slot bugs. The digital-signature branch shares this same philosophy with its own two judgment calls — see the reference file.
Step 0 — Dependencies
which pdftoppm || brew install poppler # contact sheet + any PDF rendering
uvx noteshrink --help | head -3 # first run builds it (~30 s)
Scripts are uv run single-file scripts (PEP 723); OpenCV/PIL/img2pdf resolve
automatically on first run.
Step 1 — Rectify
uv run <skill>/scripts/photo_to_scan.py --raw --out-dir work --prefix page \
photo1.jpg photo2.jpg ...
Expected: one page_NN.jpg per photo, each tagged [quad]. A
[FULLFRAME-fallback] tag means the paper outline wasn't found (busy background,
page cut off) — view that photo and decide: retake, or accept the uncropped frame.
What ships with it
5 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.
- 12d ago First seen · 185 lines · 249 tokens per session scan A 5f5b2161e715
photo-to-scanned-pdf is a skill published in the GitHub repository daymade/claude-code-skills (1,388 stars, last pushed today), licensed MIT. It adds 249 tokens to every session and 2,331 once invoked, about $0.0012 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.
Other skills, from other repositories
pydicom
Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
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.