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Synthetic Self Improve Rl

Agent skill
1 skill
READMEOverview ↓

Teacher/student self-improvement loop. Claude post-trains a smaller student model on a real dataset via prime-rl, analyzes failed training traces, generates a 500-1000 row dataset targeting the model's weaknesses, wraps it as a verifiers environment, and re-trains in a loop until a wall-clock budget expires. Default student is Qwen/Qwen3-0.6B; override with --model. Use when the user types /synthetic-self-improve-rl .

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryGeneralStars0

About this skill

Teacher/student self-improvement loop. Claude post-trains a smaller student model on a real dataset via prime-rl, analyzes failed training traces, generates a 500-1000 row dataset targeting the model's weaknesses, wraps it as a verifiers environment, and re-trains in a loop until a wall-clock budget expires. Default student is Qwen/Qwen3-0.6B; override with --model. Use when the user types /synthetic-self-improve-rl .

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.

Installation guide →

Review, license & listing details
Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Partial

Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: 686738057131f96e29d28689d79d4566c8e5f9aed7eb5d7c377a32a0398a4798

About scan coverage and limitations
Original listing metadata

Original name

synthetic-self-improve-rl

Original description

Teacher/student self-improvement loop. Claude post-trains a smaller student model on a real dataset via prime-rl, analyzes failed training traces, generates a 500-1000 row dataset targeting the model's weaknesses, wraps it as a verifiers environment, and re-trains in a loop until a wall-clock budget expires. Default student is Qwen/Qwen3-0.6B; override with --model. Use when the user types /synthetic-self-improve-rl <dataset>.

About this listing

Category
General
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
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Synthetic Self Improve Rl | Agent Skills Atlas