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dsh-academic-research

Model Inference Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install userInner/dsh-academic-research

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install userInner/dsh-academic-research in your DeepSeek Harness terminal, or clone https://github.com/userInner/dsh-academic-research locally and use dsh plugin install ./path; after restarting the profile the plugin row is mounted automatically.

About this plugin

The most tedious part of academic work is often not writing but verifying: tracking down sources across paywalled databases, double-checking citation formats, and drafting reviewer responses without a clear evidence trail. dsh-academic-research folds all of that into a single DeepSeek Harness plugin that runs on public Crossref and OpenAlex metadata, requiring no account, no licensed database connection, and no extra credentials.

Three read-only tools do the heavy lifting. research_search retrieves matching records from Crossref and OpenAlex by keyword; research_fetch pulls one allowlisted public HTTPS record or paper page; research_source_status reports the scope and limitations of the current public coverage. Results are stratified into metadata, abstract, and full-text-link evidence levels, and the plugin explicitly warns that a link is never treated as proof the full paper was read. This keeps every literature review, writing draft, citation check, and reviewer-response suggestion anchored to verifiable public data.

Baked-in research-integrity rules prohibit fabricated sources, data, quotations, experiments, and peer-review claims, so the output stays honest by construction. The plugin is ideal for graduate students, independent researchers, and bilingual writing teams who already run DeepSeek Harness or OnPeople. It mounts declaratively via the profile-bundle contract, adds no custom UI, and composes cleanly with whatever tool presentation, permissions, and model settings the host already provides.

Use Cases

  • Build an evidence matrix for a bilingual literature review
  • Verify citation formats, DOIs, and source coverage
  • Draft reviewer responses backed by verifiable evidence

Best For

  • Graduate students and independent researchers
  • Research teams working in bilingual Chinese-English writing
  • Academic users of DeepSeek Harness or OnPeople