dojo-hack

dojo-hack is a skill for Claude Code, Codex from ttguy0707/codojo. It costs 348 tokens per session (2,179 once invoked), scanned A, original, MIT.

A project-improvement guide for the fourth Codojo learning stage. After the teaching plan is complete, it suggests specific changes and carries them out according to a shared plan.

In plain words
What is it for?
Use it to add features, reorganise code, improve performance, expand tests, or strengthen project tools such as CI/CD, logging, monitoring, and documentation.
Why use it?
It turns a broad wish to improve a project into a set of concrete tasks. It also lets the user pause and continue the work from the saved plan.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to add features, reorganise code, improve performance, expand tests, or strengthen project tools such as CI/CD, logging, monitoring, and documentation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ttguy0707/codojo/dojo-hack
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.

Any agent
npx skills add ttguy0707/codojo --skill dojo-hack
Clone the repo
git clone --depth 1 https://github.com/ttguy0707/codojo

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for dojo-hack

README.md
[![agentmods](https://agentmods.dev/badge/skills/ttguy0707/codojo/dojo-hack/github.svg)](https://agentmods.dev/skills/ttguy0707/codojo/dojo-hack)
Your own site
<a href="https://agentmods.dev/skills/ttguy0707/codojo/dojo-hack"><img src="https://agentmods.dev/badge/skills/ttguy0707/codojo/dojo-hack/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dojo-hack

Your own site · 80×15
<a href="https://agentmods.dev/skills/ttguy0707/codojo/dojo-hack"><img src="https://agentmods.dev/badge/skills/ttguy0707/codojo/dojo-hack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 348 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,179 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00348 $0.02179
Opus 5.5 $0.00139 $0.00872
Sonnet 5.5 $0.00070 $0.00436
Haiku 4.5 $0.00035 $0.00218

Measured 1mo ago against content hash 99370e23641f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dojo-hack 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 1mo 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.

skills/dojo-hack/SKILL.md · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dojo-hack — S4 魔改阶段

一句话定位:推荐魔改方向,制定计划,动手改造项目,直到用户满意。

何时使用

  • ✅ S3 教学 100% 完成,用户选择进入 S4
  • ✅ 用户说"我想魔改"、"给项目加功能"、"改造一下"
  • ❌ S3 未完成 → 提示先完成 S3,转 dojo-teach
  • ❌ 用户只是想学习不想改代码 → 不强制进入

前置条件

  • <repo-root>/.codojo/schedule.md 存在且显示 100% 完成

若前置条件不满足,提示用户先完成 S3 教学。

工作流

Step 1:项目深度分析与推荐

全面分析项目代码,从以下维度推荐魔改方向:

  • 功能扩展:基于项目已有能力,可以新增哪些实用功能
  • 代码重构:哪些地方可以优化结构、提升可读性
  • 性能优化:有没有明显的性能瓶颈可以改进
  • 测试完善:缺少哪些测试覆盖
  • 工程化改进:CI/CD、日志、监控、文档等

输出推荐列表:

## 🎯 魔改方向推荐

根据项目分析,为你推荐以下魔改方向(可多选,也可以自己提需求):

### 功能扩展类
1. **<功能名>**:<一句话描述 + 预估工作量>
2. **<功能名>**:<一句话描述 + 预估工作量>

### 代码优化类
3. **<优化点>**:<一句话描述 + 预估工作量>
4. **<优化点>**:<一句话描述 + 预估工作量>

### 工程化改进类
5. **<改进点>**:<一句话描述 + 预估工作量>

---
请回复你想做的编号(如「1 3 5」),或者直接告诉我你想做什么改动。
回复「不了」可以跳过 S4,结束整个学习流程。

推荐原则:

  • 推荐 5-8 个方向,不要太多造成选择困难
  • 每个方向要有具体可落地的改动点,不要空泛
  • 按难度从低到高排列
  • 预估工作量帮助用户做选择

Step 2:制定 plan.md

根据用户选择(可多选 + 自定义),生成 <repo-root>/.codojo/plan.md:

# 魔改计划

> 根据你的选择生成,AI 将按此计划协助你改造项目。

## 概要

- **选定方向**:<列出>
- **预计总工作量**:约 X 小时
- **当前状态**:进行中

## 任务清单

### 任务 1:<任务名>
- **目标**:<达成什么效果>
- **涉及文件**:<文件路径列表>
- **实施步骤**:
  1. <具体步骤>
  2. <具体步骤>
  3. <具体步骤>
- **验证方式**:<如何确认改动生效>
- **状态**:⚪ 未开始

### 任务 2:<任务名>
...

## 变更日志

<!-- 每次有新需求或计划变更时追加记录 -->

生成后向用户确认:

plan.md 已生成,共 N 个任务。先从「任务 1:<名称>」开始?

Step 3:执行改造

按 plan.md 任务顺序,逐个协助用户完成改造。

代码改动确认协议:

每个任务开始前,AI 必须先向用户展示改动方案并等待确认:

## 🔧 任务 N:<任务名>

**改动方案**:
1. 修改 `<文件路径>` — <改动说明>
2. 新增 `<文件路径>` — <说明>
3. ...

**影响范围**:<哪些现有功能可能受影响>
**验证方式**:<如何确认改动生效>

确认开始?回复「开始」执行,或提出修改意见。

用户回复"开始"、"可以"、"执行"后,才能动手修改代码。

执行流程:

  1. 讲解思路:这个改动要做什么、为什么这样做、会影响哪些文件
  2. 协作实施:AI 生成代码改动,解释每处修改的含义,引导用户理解
  3. 验证结果:指导用户验证改动效果(编译、运行、测试等)
  4. 更新 plan.md:将任务状态更新为 ✅,记录完成时间

每完成一个任务:

---
✅ 任务 1「<名称>」已完成!

📋 **魔改进度**: 1/N 任务完成
⏭️ 下一个:任务 2「<名称>」

继续?或者有新想法随时告诉我。
---

Step 4:持续迭代

S4 阶段不设终点,持续接受用户新需求:

  • 用户新增需求 → 追加到 plan.md 任务清单,在变更日志中记录
  • 用户修改需求 → 更新 plan.md 对应任务,在变更日志中记录
  • 用户取消某个任务 → 标记为 ❌ 已取消,在变更日志中记录
  • 用户说"满意了"/"结束" → 输出完成总结

Read the full file on GitHub · 221 lines

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. 1mo ago First seen · 221 lines · 348 tokens per session scan A 99370e23641f

Subscribe to this mod's changes

dojo-hack is a skill published in the GitHub repository ttguy0707/codojo (71 stars, last pushed 3mo ago), licensed MIT. It adds 348 tokens to every session and 2,179 once invoked, about $0.0014 per session on Opus 5.5. 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 2026-08-30.

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