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.
npx agentmods add skills/samqin123/claude_skill_pool/ralphnpx skills add samqin123/Claude_skill_pool --skill ralphgit clone --depth 1 https://github.com/samqin123/Claude_skill_poolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/samqin123/claude_skill_pool/ralph)<a href="https://agentmods.dev/skills/samqin123/claude_skill_pool/ralph"><img src="https://agentmods.dev/badge/skills/samqin123/claude_skill_pool/ralph.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.00791 |
| Opus 5 | $0.00030 | $0.00396 |
| Sonnet 5 | $0.00012 | $0.00158 |
| Haiku 4.5 | $0.00006 | $0.00079 |
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 5d 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.
What it actually says
Ralph - Autonomous Agent Loop
Overview
将 PRD 转为结构化 prd.json,然后循环生成全新 Agent 实例逐个完成 User Story,每轮实例只有 Git 历史 + prd-progress.txt + prd.json 作为上下文记忆。
Workflow
Phase 1: PRD Conversion (if markdown provided)
- 读取 PRD — 解析用户提供的 Markdown PRD 文件。
- 归档上一次运行 — 若
prd.json已存在且branchName不同,归档到.claude/archive/YYYY-MM-DD-[feature]/。 - 生成 prd.json — 按以下格式:
{
"project": "[Project Name]",
"branchName": "ralph/[feature-kebab-case]",
"description": "[Description]",
"userStories": [
{
"id": "US-001",
"title": "[Story title]",
"description": "As a [user], I want [feature] so that [benefit]",
"acceptanceCriteria": ["Criterion 1", "Typecheck passes"],
"priority": 1,
"passes": false,
"notes": ""
}
]
}
Story 规则:
- 每个 Story 必须单轮可完成(2-3 句话能描述的变更)。
- 按依赖排序:schema → backend → UI → dashboard。
- 每个 Story 必须包含 "Typecheck passes"。
- UI Story 额外包含 "Verify in browser"。
Phase 2: Ralph Execution
- 预检 — 确认
ampCLI、jq已安装,Git 工作目录干净,prd.json有效。 - 创建/切换分支 — 从
prd.json读取branchName。 - 执行循环 —
bash .claude/scripts/ralph.sh [max_iterations](默认 10 轮):- 生成全新 Agent 实例 +
.claude/scripts/prompt.md - Agent 选取最高优先级未完成 Story
- 实现 → 质量检查(typecheck/lint/test)→ 通过则提交
- 更新
prd.json(passes: true)+ 追加prd-progress.txt - 循环直到全部通过或达到最大轮数
- 生成全新 Agent 实例 +
Memory Between Iterations
唯一的跨轮记忆:
- Git 历史(之前的提交)
prd-progress.txt(学习日志)prd.json(完成状态)
每轮都是全新实例,无隐式状态泄漏。
Key Files
| 文件 | 用途 |
|---|---|
.claude/scripts/ralph.sh |
Bash 循环脚本 |
.claude/scripts/prompt.md |
每轮 Agent 的指令 |
prd.json |
User Story 及完成状态 |
prd-progress.txt |
追加式学习日志 |
.claude/archive/ |
历史运行归档 |
Guardrails
- Story 必须小到单轮可完成,否则强制拆分。
- 不提交未通过质量检查的代码。
- Git 工作目录必须干净才能启动。
- 支持断点续传(重新运行即从未完成处继续)。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 81 lines · 61 tokens per session scan A dd7a3ea8d891
ralph is a skill published in the GitHub repository samqin123/Claude_skill_pool (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 791 once invoked, about $0.0003 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.
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