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/seed-forge/harness-ai-kit/markitdownnpx skills add seed-forge/harness-ai-kit --skill markitdowngit clone --depth 1 https://github.com/seed-forge/harness-ai-kitWrote 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/seed-forge/harness-ai-kit/markitdown)<a href="https://agentmods.dev/skills/seed-forge/harness-ai-kit/markitdown"><img src="https://agentmods.dev/badge/skills/seed-forge/harness-ai-kit/markitdown.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 | $0.00073 | $0.00643 |
| Opus 5 | $0.00036 | $0.00321 |
| Sonnet 5 | $0.00015 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00064 |
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 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.
What it actually says
MarkItDown
这是当前项目的本地化 markitdown 技能入口。
它基于上游全局 Skill，但这里补上了本环境下已经验证过的稳定用法，避免每次重复处理安装和命令路径问题。
Use This Skill For
- 把
docx、pdf、pptx、xlsx转成 markdown - 批量把资料转换成更适合 LLM 处理的文本格式
- 在 Obsidian 项目里落地文档转写结果
Environment Notes
- 当前环境已验证
python -m markitdown可用 - 建议优先调用本地包装命令：
.\.agents\tools\markitdown.cmd
- 如果直接输入
markitdown失败，通常是因为 Python 的Scripts目录不在PATH
Stable Invocation
.\.agents\tools\markitdown.cmd input.docx -o output.md
或：
python -m markitdown input.docx -o output.md
Verified Dependency Strategy
本环境里不建议直接依赖：
pip install "markitdown[all]"
因为实测可能把主包错误回退到旧版本。
更稳的方式是：
python -m pip install --upgrade markitdown==0.1.5
python -m pip install azure-ai-documentintelligence azure-identity openpyxl pandas pydub python-pptx speechrecognition youtube-transcript-api openai pathvalidate puremagic mammoth olefile xlrd pdfminer-six pdfplumber
Workflow
- 确认源文件存在，并避免覆盖现有
.md - 优先输出到新文件名，例如
*.markitdown.md - 转换后抽查文件头部，确认不是空文件
- 如需给 Obsidian 使用，再做一轮 markdown 清洗
推荐输出格式
执行完毕后按以下结构输出：
状态：✅ 成功 / ⚠️ 部分成功 / ❌ 失败
| <输入→输出文件/格式/路径> | <值/状态> | 说明 |
|---|
下一步：<可执行动作>
Practical Notes
- DOCX 已在当前环境验证通过
- PDF、PPTX、XLSX、音频、YouTube 转写依赖已补齐
- Azure Document Intelligence 和 OpenAI 增强能力仍需各自凭证
What ships with it
3 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 · 77 lines · 73 tokens per session scan A e3cfecb3bbcb
markitdown is a skill published in the GitHub repository seed-forge/harness-ai-kit (21 stars, last pushed 4d ago), licensed Apache-2.0. It adds 73 tokens to every session and 643 once invoked, about $0.0004 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.
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