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/ttguy0707/codojo/dojo-assessnpx skills add ttguy0707/codojo --skill dojo-assessgit clone --depth 1 https://github.com/ttguy0707/codojoWrote 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/ttguy0707/codojo/dojo-assess)<a href="https://agentmods.dev/skills/ttguy0707/codojo/dojo-assess"><img src="https://agentmods.dev/badge/skills/ttguy0707/codojo/dojo-assess.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 | $0.00327 | $0.01853 |
| Opus 5 | $0.00163 | $0.00927 |
| Sonnet 5 | $0.00065 | $0.00371 |
| Haiku 4.5 | $0.00033 | $0.00185 |
Grade A, and why
dojo-assess 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dojo-assess — S1 能力评估
一句话定位:分析项目技术栈,通过交互式问答评估用户当前水平,产出
open-questions.md。
何时使用
- ✅ 用户第一次进入项目学习流程
- ✅ 用户说"帮我学习这个项目"、"评估我的水平"、"我是新手"
- ✅
.codojo/目录不存在或open-questions.md不存在 - ❌
open-questions.md已存在且已填答案 → 转dojo-plan - ❌ 用户已有学习计划想直接开始学 → 转
dojo-teach
前置条件
- 无(S1 是起点)
工作流
Step 1:项目全面扫描
扫描 <repo-root>/ 的完整目录结构、代码文件、配置文件,识别:
- 编程语言:Java / Python / Go / JS / TS 等
- 框架:Spring Boot / Django / React / Vue 等
- 构建工具:Maven / Gradle / npm / pip 等
- 中间件:Redis / MySQL / Kafka / MQ 等
- 架构模式:MVC / 微服务 / 分层架构等
- 其他:设计模式、领域概念、第三方 API 等
将分析结果(语言、框架、构建工具等)写入 open-questions.md 的"项目技术栈概览"章节。分析过程本身不单独输出给用户。
Step 2:生成 open-questions.md
根据 Step 1 的分析结果,生成 <repo-root>/.codojo/open-questions.md。
格式要求:
# 能力评估问卷
> 本问卷由 AI 根据项目技术栈自动生成,用于评估你的当前水平,以便制定个性化学习计划。
## 项目技术栈概览
- 语言:xxx
- 框架:xxx
- 构建工具:xxx
- ...
## 评估问题
### Q1: <问题>
- [ ] 完全不了解
- [ ] 听说过但没用过
- [ ] 用过但不熟练
- [ ] 熟练掌握
**你的回答**:<待填>
### Q2: <问题>
...
## 自由补充
<用户自行补充的说明,如学习目标、时间安排、特殊背景等>
问题设计原则:
- 覆盖项目涉及的每个主要技术点
- 从基础到进阶分层(如:Java 基础语法 → Spring IoC → Spring Boot 自动配置)
- 问题数量 8-15 个(不宜过多造成负担)
- 措辞友好,不让用户有压力
Step 3:交互式问答
将 open-questions.md 中的问题逐个向用户提问:
- 展示问题 + 选项
- 等待用户回答
- 立即写入文件
- 进入下一个问题
问题数量限制:最多 15 题,避免评估阶段过长。
注意:
- 每次只问一个问题,不要一次性抛出所有问题
- 用户回答后可以简短回应("好的"、"了解"),不要展开讲解(教学在 S3)
- 如果用户回答模糊,可追问一次澄清
- 用户回答明确后,必须立刻更新
open-questions.md中对应题目的**你的回答** - 如果会话中断,恢复时读取
open-questions.md,从第一个**你的回答**:<待填>的问题继续
Step 4:自由补充
所有问题问完后,给用户一次机会:
所有问题已回答完毕!在生成学习计划之前,你还有什么想补充的吗?
比如:
- 你的学习目标是什么?(看懂代码 / 能改 Bug / 能加功能)
- 每天大概能投入多少时间学习?
- 有没有特别想重点学的部分?
- 其他任何你觉得我应该知道的信息
没有补充的话,回复「无」即可。
Step 5:补充自由说明并完成
将 Step 4 收集的自由补充写入 open-questions.md,并在文件末尾追加完成标记(其他 skill 通过此标记判断 S1 是否完成):
## 评估完成
- 完成时间:YYYY-MM-DD HH:mm
<!-- ASSESS_DONE -->
输出完成自检:
## 📋 S1 能力评估 完成
**产出物** ✅
- `.codojo/open-questions.md`(已填写完毕)
**评估概要**
- 已掌握:<列出>
- 需学习:<列出>
- 用户补充:<摘要>
**下一步** → S2 计划生成
是否进入 S2 生成个性化学习计划?
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 · 178 lines · 327 tokens per session scan A bb832d1e0f4f
dojo-assess is a skill published in the GitHub repository ttguy0707/codojo (57 stars, last pushed 2mo ago), licensed MIT. It adds 327 tokens to every session and 1,853 once invoked, about $0.0016 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 2026-08-30.
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