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 EKKOLearnAI/hermes-studio --skill pdfgit clone --depth 1 https://github.com/EKKOLearnAI/hermes-studioWrote 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/ekkolearnai/hermes-studio/pdf)<a href="https://agentmods.dev/skills/ekkolearnai/hermes-studio/pdf"><img src="https://agentmods.dev/badge/skills/ekkolearnai/hermes-studio/pdf.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.00675 |
| Opus 5 | $0.00017 | $0.00338 |
| Sonnet 5 | $0.00007 | $0.00135 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
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 8d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
What ships with it
16 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.
- LICENSE 1.0 KB
- references/forms.md 3.9 KB
- scripts/_raster.py 2.6 KB runs code
- scripts/pdf_create.py 4.5 KB runs code
- scripts/pdf_fill_form.py 3.8 KB runs code
- scripts/pdf_form_layout.py 7.0 KB runs code
- scripts/pdf_make_form.py 5.8 KB runs code
- scripts/pdf_merge.py 1.6 KB runs code
- scripts/pdf_meta.py 4.4 KB runs code
- scripts/pdf_page_image.py 3.5 KB runs code
- scripts/pdf_read.py 5.7 KB runs code
- scripts/pdf_secure.py 4.3 KB runs code
- scripts/pdf_split.py 3.0 KB runs code
- scripts/pdf_stamp.py 5.6 KB runs code
- scripts/pdf_watermark.py 1.8 KB runs code
- tests/test_pdf_skill.py 17 KB runs code
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.
- 8d ago First seen · 64 lines · 34 tokens per session scan A 7e04a39774b3
pdf is a skill published in the GitHub repository EKKOLearnAI/hermes-studio (10,904 stars, last pushed today), with no licence file. It adds 34 tokens to every session and 675 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.
Other skills, from other repositories
PDF files: create, read, merge, fill, OCR, edit text.
pdf-toolkit
Structured .pdf operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract…
extracting-lab-tables
Detects and extracts tabular laboratory panels from PDFs, scans, and images into structured rows ready for OpenMed and FHIR. Use when the user has a CBC, CMP, lipid panel, or other lab report as a scanned image / PDF / spreadsheet and needs the test name, value, unit, reference range, and abnormal flag as clean rows.…
nano-pdf
Edit PDFs with natural-language instructions using the nano-pdf CLI.
liteparse
Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.
meta-pdf-intelligence
Use this meta-skill instead of answering directly when the user needs PDF analysis, pasted PDF excerpt analysis, digesting, comparison, or question answering that benefits from multi-skill orchestration across PDF extraction, summarization, cross-document synthesis, traceable evidence indexing, and memory capture.