noatmark-dsh-plugin
Đã xác minhnoatmark-dsh-plugin · v0.1.0 · MIT
NoAtMark text hygiene as a DeepSeek Harness (dsh) plugin — sanitize untrusted text, scan invisible characters, clean LLM formatting, and escape CSV formula injection.
Cài đặt
dsh plugin add noatmark-dsh-plugin Xác nhận layer đã áp bằng dsh --profile default --dump-config — xem hướng dẫn cài plugin.
Mã nguồn
Phát hành lên npm mà không có repository công khai. Hãy kiểm tra nội dung package trước khi cài.
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Readme
noatmark-dsh-plugin
NoAtMark text hygiene as a DeepSeek Harness (dsh) plugin.
Everything-is-a-plugin: this plugin gives your dsh agent four text-hygiene tools, backed by the same deterministic engines behind noatmark.com.
Tools
| Tool | What it does |
|---|---|
sanitize_text |
Strip invisible/zero-width characters and flag prompt-injection + hidden-text signals. |
scan_text |
Report invisible characters (with code points + positions), injection patterns, and hidden text. |
clean_format |
Clean LLM formatting artifacts (blank lines, stray fences, trailing spaces) — meaning untouched. |
sanitize_csv |
Escape CSV formula injection (OWASP): = + - @ prefixes get a leading quote. |
All processing is deterministic and local — no data leaves your machine.
Install
Add this plugin to your dsh Web UI. If you're running from a source checkout, use a cordis.yml patch:
- insert:
- id: noatmark
name: noatmark-dsh-plugin
or point at the source directly (absolute path):
- insert:
- id: noatmark
name: '/path/to/noatmark-dsh-plugin/src/index.ts'
Start dsh with the patch:
npx @deepseek-ai/dsh web --patch ./cordis.yml
Usage
In a dsh session, ask the agent to use a tool, e.g.:
Sanitize this pasted text before you summarize it.
Scan this file for invisible characters.
Clean the formatting of this AI output.
Escape this CSV before saving it.
Development
pnpm install
pnpm build # tsc -> dist/
Resources
- Web tools: https://noatmark.com/
- NoAtMark SDK (npm/PyPI):
noatmark-text-hygiene - DeepSeek Harness: https://github.com/deepseek-ai/deepseek-harness
- Official docs: https://deepseek-harness.github.io/deepseek-harness/
MIT