DEDUPED Hot AI repos, turned into use cases Get 5 a day

How to map where AI models agree and disagree on a research question with DSH Council

Run a panel on a contested question and read the consensus, disagreements, and rankings.

  • Research
  • Intermediate
  • 45 minutes
  • From the README
  • Any agent

Who it is forA researcher or analyst who needs a structured overview of a question where sources conflict.

The problemOne model summary hides where the models, and the evidence behind them, actually disagree.

The outcomeA decision summary with consensus, disagreements, and average rankings, plus the original answers kept in DSH child sessions.

What you need first

  • DeepSeek Harness (dsh) installed by following its official installation guide
  • Node.js ^22.19.0 or >=24.0.0
  • pnpm 11.7.0, as listed in the README requirements
  • At least two configured, authenticated models in DSH

Steps

  1. Install DSH by following the official guide at https://www.deepseek.com/harness/
  2. Run npx --yes @deepseek-ai/dsh@latest plugin --profile web add @a1exsun/[email protected]
  3. Run npx --yes @deepseek-ai/dsh@latest web and restart DSH Web if it is already running
  4. In a DSH Web conversation, enter /council, then select answerers, reviewers, and an arbiter
  5. Open the child sessions to read the original answers and reviews behind the final summary

Prompt for your agent

Using the a1exsun/dsh-council repo in DSH Web, run /council on this research question: <question with the scope and the sources you already hold>. Return the consensus, the disagreements, and the average rankings. Verify each cited claim against the source material before using it.

Caveat. The plugin does not gather sources for you, so check every factual claim against primary material before relying on it.

Share: X LinkedIn Hacker News Email Copy link

Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page