{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "danielxu0208-rsi-eval--run-bundled-rsi-method-on-experiment",
 "repo": "Danielxu0208/rsi_eval",
 "repo_url": "https://github.com/Danielxu0208/rsi_eval",
 "repo_slug": "danielxu0208-rsi-eval",
 "title": "Run a bundled RSI method on a prepared experiment",
 "page_title": "How to run a bundled RSI method on a prepared experiment with Rsi Eval",
 "summary": "Prepare, check, run, and independently test a Meta-Harness, RRSI, AHE, or HarnessX workflow.",
 "who": "A researcher who wants a ready-made self-improvement workflow instead of writing one from scratch.",
 "problem": "Each method has its own dependencies, pinned upstream code, and seed handling, which are tedious to set up by hand.",
 "outcome": "An experiment directory with a frozen configuration, a method run, and an independent test of the selected artifact.",
 "steps": [
  "`rsi-eval method list`",
  "`rsi-eval method prepare --method meta-harness --profile profile.json --experiment runs/meta-example` (inferred, check the README)",
  "`rsi-eval method check --experiment runs/meta-example`",
  "`rsi-eval method run --experiment runs/meta-example`",
  "`rsi-eval method test --experiment runs/meta-example --output runs/meta-test`"
 ],
 "agent_prompt": "In the rsi_eval repo, prepare a <method> experiment at runs/<experiment-name> using profile.json, then run method check, run, and test in that order. Report the artifact selected by the method and the test output. Verify that the experiment directory contains the frozen configuration and seed.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "300 minutes",
 "basis": "readme",
 "caveat": "The README says prepare downloads packages and sources without calling a model, but the run step does call models and consumes quota.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.12 or newer and git",
  "Docker Engine with Compose and Buildx, or Docker Desktop, for benchmark runs",
  "Codex CLI on PATH and access to a model for candidate runs",
  "Harbor 0.18.0 installed through the harbor extra for benchmark runs"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "credentials",
   "notice": "The method runs use the Codex profile and login directory, so keep those credentials out of the repository and candidate artifacts."
  }
 ],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/danielxu0208-rsi-eval/run-bundled-rsi-method-on-experiment/",
 "md": "https://dedupedai.com/use-cases/danielxu0208-rsi-eval/run-bundled-rsi-method-on-experiment/index.md",
 "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 hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/danielxu0208-rsi-eval--run-bundled-rsi-method-on-experiment.json",
 "api_version": "v1"
}