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 seaworld008/Commonly-used-high-value-skills --skill markdown-toolsgit clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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/seaworld008/commonly-used-high-value-skills/markdown-tools)<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/markdown-tools"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/markdown-tools/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/seaworld008/commonly-used-high-value-skills/markdown-tools"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/markdown-tools.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00031 | $0.01349 |
| Opus 5 | $0.00015 | $0.00674 |
| Sonnet 5 | $0.00006 | $0.00270 |
| Haiku 4.5 | $0.00003 | $0.00135 |
Grade A, and why
markdown-tools 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.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Markdown Tools
Convert documents to high-quality markdown with intelligent multi-tool orchestration.
When to Use
Use this skill when the user wants to:
- convert PDF, DOCX, PPTX, or XLSX into Markdown
- extract images alongside Markdown output
- compare multiple converters for quality
- validate a conversion before downstream LLM use
Usage
Recommended flow:
choose quick or heavy mode
-> convert with best-fit tool(s)
-> validate output quality
-> extract images if needed
-> merge or refine outputs
Dual Mode Architecture
| Mode | Speed | Quality | Use Case |
|---|---|---|---|
| Quick (default) | Fast | Good | Drafts, simple documents |
| Heavy | Slower | Best | Final documents, complex layouts |
Quick Start
Installation
# Required: PDF/DOCX/PPTX support
uv tool install "markitdown[pdf]"
pip install pymupdf4llm
brew install pandoc
Basic Conversion
# Quick Mode (default) - fast, single best tool
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.pdf -o output.md
# Heavy Mode - multi-tool parallel execution with merge
uv run --with pymupdf4llm --with markitdown scripts/convert.py document.pdf -o output.md --heavy
# Check available tools
uv run scripts/convert.py --list-tools
Tool Selection Matrix
| Format | Quick Mode Tool | Heavy Mode Tools |
|---|---|---|
| pymupdf4llm | pymupdf4llm + markitdown | |
| DOCX | pandoc | pandoc + markitdown |
| PPTX | markitdown | markitdown + pandoc |
| XLSX | markitdown | markitdown |
Tool Characteristics
- pymupdf4llm: LLM-optimized PDF conversion with native table detection and image extraction
- markitdown: Microsoft's universal converter, good for Office formats
- pandoc: Excellent structure preservation for DOCX/PPTX
Heavy Mode Workflow
Heavy Mode runs multiple tools in parallel and selects the best segments:
- Parallel Execution: Run all applicable tools simultaneously
- Segment Analysis: Parse each output into segments (tables, headings, images, paragraphs)
- Quality Scoring: Score each segment based on completeness and structure
- Intelligent Merge: Select best version of each segment across tools
What ships with it
8 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.
- references/conversion-examples.md 6.5 KB
- references/heavy-mode-guide.md 3.8 KB
- references/tool-comparison.md 3.7 KB
- scripts/convert_path.py 1.4 KB runs code
- scripts/convert.py 13 KB runs code
- scripts/extract_pdf_images.py 7.6 KB runs code
- scripts/merge_outputs.py 13 KB runs code
- scripts/validate_output.py 16 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.
- 5d ago Changed · -38 tokens per session 3812f49fd9a9
- 9d ago First seen · 192 lines · 69 tokens per session scan A ca6833b35b4f
markdown-tools is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 5d ago), licensed MIT. It adds 31 tokens to every session and 1,349 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 2026-09-03.
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