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 JeanDiable/obsidian-claude --skill paper-imagesgit clone --depth 1 https://github.com/JeanDiable/obsidian-claudeWrote 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/jeandiable/obsidian-claude/paper-images)<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/paper-images"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/paper-images/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/jeandiable/obsidian-claude/paper-images"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/paper-images.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 | $0.00026 | $0.01278 |
| Opus 5.5 | $0.00010 | $0.00511 |
| Sonnet 5.5 | $0.00005 | $0.00256 |
| Haiku 4.5 | $0.00003 | $0.00128 |
Grade A, and why
paper-images scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- If arXiv ID, use curl to download PDF to temp directory How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Paper Image Extractor.
Goal
Extract all images from a paper, save to 50_Clippings/Papers/[domain]/[paper_title]/images/ directory, and return image path list for note references.
Key improvement: Prioritize extracting real paper figures (architecture diagrams, experiment result figures, etc.) from arXiv source packages, rather than logos and non-core images from PDFs.
Workflow
Step 1: Identify Paper Source
-
Identify paper source
- Supported formats: arXiv ID (e.g., 2510.24701), full ID (arXiv:2510.24701), local PDF path
-
Download PDF (if needed)
- If arXiv ID, use curl to download PDF to temp directory
Step 2: Extract Images (Three-tier Priority)
Priority 1: Extract from arXiv Source Package (Highest Priority)
The script automatically attempts these steps:
-
Download arXiv source package
- URL:
https://arxiv.org/e-print/[PAPER_ID] - Extract to temp directory
- URL:
-
Find image directories in source
- Check directories:
pics/,figures/,fig/,images/,img/ - If found, copy all image files to output directory
- Check directories:
-
Extract PDF images from source
- Find PDF files in source package (e.g.,
dr_pipelinev2.pdf) - Convert PDF pages to PNG images
- Find PDF files in source package (e.g.,
-
Generate image index
- Group by source (arxiv-source, pdf-figure, pdf-extraction)
Priority 2: Extract Directly from PDF (Fallback)
If source package unavailable or insufficient images found, fall back to PDF extraction:
python "$SKILL_DIR/scripts/extract_images.py" \
"[PAPER_ID or PDF_PATH]" \
"$OBSIDIAN_VAULT_PATH/50_Clippings/Papers/[DOMAIN]/[PAPER_TITLE]/images" \
"$OBSIDIAN_VAULT_PATH/50_Clippings/Papers/[DOMAIN]/[PAPER_TITLE]/images/index.md"
Parameter notes:
- 1st parameter: paper ID (arXiv ID) or local PDF path
- 2nd parameter: output directory
- 3rd parameter: index file path
Step 3: Return Image Paths
Return image path list relative to the note file, formatted for easy note reference.
What ships with it
1 file 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.
- 2mo ago First seen · 157 lines · 26 tokens per session scan A 39a9fc6daae8
paper-images is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 8mo ago), licensed MIT. It adds 26 tokens to every session and 1,278 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
paper-images compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| paper-imagesJeanDiable/obsidian-claude | Skill | 2 | 8mo ago | MIT | A | 26 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |