managedcode-markitdown

managedcode-markitdown is a skill for Claude Code, Codex from managedcode/dotnet-skills. It costs 113 tokens per session (430 once invoked), scanned A, original, MIT.

A .NET document-conversion tool that turns office and rich-text files into Markdown, a plain-text format with headings, links, and other structure.

In plain words
What is it for?
Use it in document-ingestion pipelines before search indexing, content chunking, or AI summarisation.
Why use it?
It provides a predictable document format for later indexing, splitting into chunks, summarising, or preparing content for AI workflows.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/managedcode/dotnet-skills/managedcode-markitdown
Any agent
npx skills add managedcode/dotnet-skills --skill managedcode-markitdown
Clone the repo
git clone --depth 1 https://github.com/managedcode/dotnet-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for managedcode-markitdown

README.md
[![agentmods](https://agentmods.dev/badge/skills/managedcode/dotnet-skills/managedcode-markitdown.svg)](https://agentmods.dev/skills/managedcode/dotnet-skills/managedcode-markitdown)
Your own site
<a href="https://agentmods.dev/skills/managedcode/dotnet-skills/managedcode-markitdown"><img src="https://agentmods.dev/badge/skills/managedcode/dotnet-skills/managedcode-markitdown.svg" alt="Measured on agentmods" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 430 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00113 $0.00430
Opus 5 $0.00056 $0.00215
Sonnet 5 $0.00023 $0.00086
Haiku 4.5 $0.00011 $0.00043

Measured yesterday against content hash 93bd3f2a6b0d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

managedcode-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 yesterday.

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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

catalog/Libraries/ManagedCode-MarkItDown/skills/managedcode-markitdown/SKILL.md · 45 lines

What it actually says

ManagedCode.MarkItDown

Trigger On

  • integrating ManagedCode.MarkItDown into document ingestion flows
  • converting office or rich-text content into Markdown for downstream processing
  • reviewing indexing, chunking, or AI-preparation pipelines that depend on Markdown output
  • documenting file-conversion steps for a .NET application

Workflow

  1. Identify the document sources the app actually handles.
  2. Decide where Markdown conversion belongs in the pipeline:
    • before indexing
    • before chunking
    • before AI summarization or enrichment
  3. Keep conversion isolated behind one ingestion or processing service instead of scattering format handling everywhere.
  4. Validate real converted output for structure, links, headings, and attachment handling.
  5. Document which downstream stage depends on the produced Markdown.
flowchart LR
  A["Input document"] --> B["ManagedCode.MarkItDown conversion"]
  B --> C["Markdown output"]
  C --> D["Indexing, chunking, or AI workflow"]

Deliver

  • guidance on where ManagedCode.MarkItDown fits in a real processing pipeline
  • conversion-boundary recommendations for application design
  • output-validation expectations for document ingestion

Validate

  • the converted Markdown is good enough for the actual downstream consumer
  • conversion is isolated in one clear pipeline step
  • tests or review samples cover the real input formats the application claims to support
Files

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.

Changes

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.

  1. yesterday First seen · 45 lines · 113 tokens per session scan A 93bd3f2a6b0d

Subscribe to this mod's changes

managedcode-markitdown is a skill published in the GitHub repository managedcode/dotnet-skills (477 stars, last pushed 4d ago), licensed MIT. It adds 113 tokens to every session and 430 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 2026-09-03.

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