dsh-context-aware-search
Run the following command in DeepSeek Harness:
dsh plugin install helibeiqi/dsh-context-aware-search
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install helibeiqi/dsh-context-aware-search in DeepSeek Harness to install the plugin; the source code is hosted at https://github.com/helibeiqi/dsh-context-aware-search
About this plugin
Generic web-search plugins hit a wall the moment your query is context-dependent. Search "error handling" and you get a Wikipedia overview; but if you are writing Rust, what you actually need is doc.rust-lang.org and thiserror patterns. dsh-context-aware-search closes that gap: it reads the most recent session messages, detects the languages, frameworks, and libraries you are working with, rewrites your raw query into a precise, context-rich search term, and reranks results by TF-IDF similarity so the most relevant source lands on top.
Beyond query rewriting and reranking, every result carries a high / medium / low credibility badge derived from domain rules (.edu, .gov, official docs are high; known media and registries are medium; personal blogs are low). A built-in web_summarize tool takes a single URL or the top-N search hits, fetches the page text, and returns a structured Markdown brief with key points, critical data, and source links, all in one call.
Zero configuration out of the box (DuckDuckGo requires no API key), up to three backends with automatic fallback, and no dependency on embedding models or LLM calls, just TypeScript and the platform fetch API. It is built for developers and researchers who use DeepSeek Harness to look up references while coding: you no longer need to craft the perfect keyword string; the plugin carries "what I am working on" into every search for you.
Screenshots
Use Cases
- Debugging a Rust error while coding, searching for docs and best practices
- Investigating Python asyncio issues, needing precise exception-handling references
- Generating a quick Markdown brief on a tech topic for code review
Best For
- Developers coding with DeepSeek Harness
- Researchers needing precise technical documentation retrieval
- Engineers who want efficient search without manual keyword tuning
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