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 agentmods add skills/zhuzhaoyun/molio/doclingnpx skills add zhuzhaoyun/Molio --skill doclinggit clone --depth 1 https://github.com/zhuzhaoyun/MolioWrote 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/zhuzhaoyun/molio/docling)<a href="https://agentmods.dev/skills/zhuzhaoyun/molio/docling"><img src="https://agentmods.dev/badge/skills/zhuzhaoyun/molio/docling.svg" alt="Measured on agentmods" 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 | $0.00119 | $0.02926 |
| Opus 5 | $0.00060 | $0.01463 |
| Sonnet 5 | $0.00024 | $0.00585 |
| Haiku 4.5 | $0.00012 | $0.00293 |
Grade A, and why
docling 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 5d 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
2 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.
- 5d ago First seen · 288 lines · 119 tokens per session scan A 6a591cbe99b8
docling is a skill published in the GitHub repository zhuzhaoyun/Molio (242 stars, last pushed today), with no licence file. It adds 119 tokens to every session and 2,926 once invoked, about $0.0006 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
doc-processor
当用户要生成 Word/Excel/PowerPoint、做文档格式转换（Markdown ↔ HTML ↔ DOCX ↔ PDF）、PDF 文本提取、读写 Excel、合并文档或批量转换时使用。.
report-exporter
Use when exporting weekly or monthly business reports to CSV, PDF, or spreadsheet formats; when the user needs scheduled report packaging, multi-sheet exports, filtered dataset dumps, or download-ready report bundles for stakeholders and analytics review.
data_processing
Extract data from PDFs and query CSV files.
learn
Ingests an external data source into the Second Brain. Fetches content from Confluence, Google Docs, GitHub repositories, remote URLs, or any local file format supported by docling (DOCX, PPTX, XLSX, PDF, HTML, EPUB, images, Markdown, CSV, and more), converts non-markdown formats to markdown via docling, runs the…
local-doc-ops
Use when extracting, inspecting, splitting, or converting local PDFs, documents, and image-based files before they enter a knowledge pipeline.
markdown-converter
Markdown conversion: PDF, Office, HTML, data, OCR, audio, ZIP, YouTube.