dojo-assess

dojo-assess is a skill for Claude Code, Codex from ttguy0707/codojo. It costs 327 tokens per session (1,853 once invoked), scanned A, original, MIT.

The assessment step for Codojo, a guided system for learning a software project. It scans the project, identifies its technologies, and asks questions to estimate the learner's current knowledge.

In plain words
What is it for?
Use it at the beginning of a project-learning journey to create or continue `.codojo/open-questions.md`.
Why use it?
It gives the later study plan a clear starting point instead of teaching topics the learner already knows or skipping important gaps.

Skill for Claude CodeCodex

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 skills/ttguy0707/codojo/dojo-assess
Any agent
npx skills add ttguy0707/codojo --skill dojo-assess
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-assess

README.md
[![agentmods](https://agentmods.dev/badge/skills/ttguy0707/codojo/dojo-assess.svg)](https://agentmods.dev/skills/ttguy0707/codojo/dojo-assess)
Your own site
<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>
Per session 327 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,853 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 $0.00327 $0.01853
Opus 5 $0.00163 $0.00927
Sonnet 5 $0.00065 $0.00371
Haiku 4.5 $0.00033 $0.00185

Measured 5d ago against content hash bb832d1e0f4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

skills/dojo-assess/SKILL.md · 178 lines

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:

  1. 展示问题 + 选项
  2. 等待用户回答
  3. 立即写入文件
  4. 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?

Read the full file on GitHub · 178 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. 5d ago First seen · 178 lines · 327 tokens per session scan A bb832d1e0f4f

Subscribe to this mod's changes

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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