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

How to classify a new agent paper against the taxonomy with Harness RSI

Place a new paper in the existing update-target taxonomy using the taxonomy data file.

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

Who it is forA research engineer who receives a new self-improving agent paper and must decide which branch it belongs in for a review or design doc.

The problemNew papers arrive faster than a team can read the whole taxonomy, and inconsistent labels make comparisons hard.

The outcomeA category label, the nearest listed entry, and a one-sentence reason, all drawn from the repo's taxonomy data.

What you need first

  • A web browser to open the README, the project page, and the linked PDFs
  • A goal to pick an update target, classify a paper, or cite the survey

Steps

  1. Open the taxonomy data link in the Taxonomy section to read the categories as structured data.
  2. Read the Taxonomy section text to recall the difference between interpreted updates and executable updates.
  3. Read the new paper's abstract and note what it changes: instructions, memory, coordination specs, or implementations.
  4. Pick the category whose entries share that update target, and note the nearest listed method.
  5. Record the reason in one sentence and flag any paper that changes model weights, since the framework holds the model fixed.

Prompt for your agent

Read data/taxonomy.json in the zgcagi/Harness-RSI repo at https://github.com/zgcagi/Harness-RSI and classify the paper described by <paper title and abstract> into one existing category. Output the category name, the nearest listed entry, and a one-sentence reason. Verify that the category name appears in the file before you answer.

Caveat. The taxonomy reference numbers follow the manuscript, so check the manuscript before citing a number from the data file.

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 The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong.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