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 Microck/ordinary-claude-skills --skill markitdowngit clone --depth 1 https://github.com/Microck/ordinary-claude-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/microck/ordinary-claude-skills/markitdown)<a href="https://agentmods.dev/skills/microck/ordinary-claude-skills/markitdown"><img src="https://agentmods.dev/badge/skills/microck/ordinary-claude-skills/markitdown/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/microck/ordinary-claude-skills/markitdown"><img src="https://agentmods.dev/badge/skills/microck/ordinary-claude-skills/markitdown.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 | $0.00101 | $0.01559 |
| Opus 5 | $0.00051 | $0.00779 |
| Sonnet 5 | $0.00020 | $0.00312 |
| Haiku 4.5 | $0.00010 | $0.00156 |
Grade A, and why
markitdown 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
6 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.
- 8d ago First seen · 242 lines · 101 tokens per session scan A 370e2f53e2a3
markitdown is a skill published in the GitHub repository Microck/ordinary-claude-skills (394 stars, last pushed 4d ago), with no licence file. It adds 101 tokens to every session and 1,559 once invoked, about $0.0005 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.
Other skills, from other repositories
markitdown
Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.
llm-document-extraction
Extract structured data from construction documents using LLMs. Process RFIs, submittals, contracts, specifications. Convert unstructured PDFs to structured JSON/Excel.
antinet-doc-parse
A document-processing skill for building RAG systems, which let an AI search a knowledge base before answering. It handles complex PDF, Word, and Excel files and produces structured Markdown and metadata.
doc-parse
A document parser that converts PDFs, PowerPoint files, spreadsheets, and Word files into structured Markdown with metadata and a confidence score.
openapi-utilities
Openapi utility services - real-time currency exchange rates, HTML-to-PDF conversion (renders JavaScript), .it domain registration/management, and managed RAG (retrieval-augmented generation over your documents). Use for these one-off utility tasks.
ChatDOC Studio--KnowledgeMate
Create and operate ChatDOC Studio knowledge bases through pdrouter using a Bearer API key and JavaScript helpers. Use when Codex needs to upload one or more PDF/DOC/DOCX files, skip failed files without aborting the whole job, create a knowledge base from successful uploads, or call the ChatDOC Studio knowledge-base…