DeepSeek Harness plugin

dsh-vision-no-vision

Gives a text-only LLM vision capability

Jump to install

Source facts

Repository
wdwind/dsh-vision-no-vision
Latest update
Aug 15, 2026
Category
Vision & Multimodal
GitHub stars
1
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/wdwind/dsh-vision-no-vision
Plugin: dsh-vision-no-vision
Author: wdwind

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer2 files
README.mdSource Β· read only

dsh-vision-no-vision

A DeepSeek Harness (dsh) plugin that gives a text-only LLM vision capability!!!

Install

pnpm dsh plugin --profile web add dsh-vision-no-vision

Note

Seriously, it is not a serious plugin 😝. The tool generates an ascii-art from the input image and feed it into the text-only LLM to guess the content.