ralph

A command set for repeatedly running a task until a chosen condition is met, such as passing tests, building successfully, or having no lint errors.

In plain words
What is it for?
Use it for tasks that need repeated attempts until tests pass, the project builds, linting is clean, or a custom command succeeds.
Why use it?
It removes the need to restart and check the same task by hand. You can also stop the loop, inspect its status, change its settings, or stop it while rolling back changes.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/roboco-io/ralph-mem/ralph
Clone the repo
git clone --depth 1 https://github.com/roboco-io/ralph-mem
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 191 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.00191
Opus 5 $0.00010 $0.00096
Sonnet 5 $0.00004 $0.00038
Haiku 4.5 $0.00002 $0.00019

Measured 2d ago against content hash 588df3f8ae67, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ralph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

commands/ralph.md · 27 lines

What it actually says

Ralph Loop

성공 기준을 달성할 때까지 작업을 자동으로 반복 실행합니다.

사용법

  • start "task" - Loop 시작
  • start "task" --criteria lint_clean - 커스텀 성공 기준으로 시작
  • stop - Loop 중단
  • stop --rollback - 변경사항 롤백하며 중단
  • status - 현재 상태 확인
  • config - 설정 확인/변경

성공 기준

  • test_pass - 테스트 통과 (기본값)
  • build_success - 빌드 성공
  • lint_clean - Lint 오류 없음
  • type_check - 타입 체크 통과
  • custom - 사용자 정의 명령

$ARGUMENTS

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 27 lines · 21 tokens per session scan A 588df3f8ae67

Subscribe to this mod's changes

ralph is a command published in the GitHub repository roboco-io/ralph-mem (2 stars, last pushed 7mo ago), licensed MIT. It adds 21 tokens to every session and 191 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.