deepseekplugins

DeepSeek Harness plugin

dsh-plugin-rag

Local knowledge base RAG for DeepSeek Harness -- index project files and search for relevant context

Docs & Rendering
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Source facts

Repository
YYTbit/dsh-plugin-rag
Latest update
Aug 14, 2026
Category
Docs & Rendering
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/YYTbit/dsh-plugin-rag
Plugin: dsh-plugin-rag
Author: YYTbit

Check the source files

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

File explorer3 files
README.mdSource · read only

dsh-plugin-rag

Local knowledge base RAG for DeepSeek Harness.

What it does

Indexes project files (markdown, code, configs) and provides keyword search to find relevant context. No external APIs or embedding models needed -- pure local TF-IDF search.

Install

dsh plugin --profile your-profile add dsh-plugin-rag

CLI

# Search for relevant files
rag "authentication" ./src

# Show index stats
rag --index ./src ./docs

What gets indexed

  • Markdown (.md, .txt)
  • Code (.ts, .js, .py, .rs, .go, .java, .c, .cpp)
  • Config (.json, .yaml, .toml, .env)
  • Docs (.html, .xml, .sql, .graphql)

Skips: node_modules, .git, dist, build, __pycache__

Configuration

- id: rag
  name: dsh-plugin-rag
  config:
    indexPaths: ['.']
    maxResults: 3
    maxBytes: 4096
    enableInjection: true

How it works

1. Scans directories for text files 2. Builds a keyword index (TF-IDF scoring) 3. Injects index stats into system prompt 4. Agent uses CLI to search when needed

No embedding models, no external APIs, no heavy dependencies.

License

MIT -- YYTbit

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