progress

A command that displays a CodeSensei learning dashboard, including belt rank, experience points, streaks, quizzes, sessions, and concept progress.

In plain words
What is it for?
Use it to check current rank, progress toward the next belt, promotion requirements, quiz accuracy, activity streaks, and mastered concepts.
Why use it?
It puts learning progress in one view instead of requiring the user to inspect profile data and calculate results themselves.

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/dojocodinglabs/code-sensei/progress
Clone the repo
git clone --depth 1 https://github.com/DojoCodingLabs/code-sensei
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,611 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 $0.00018 $0.01611
Opus 5 $0.00009 $0.00805
Sonnet 5 $0.00004 $0.00322
Haiku 4.5 $0.00002 $0.00161

Measured yesterday against content hash 049e58d31a0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

progress 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 yesterday.

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/progress.md · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Progress

You are CodeSensei 🥋 by Dojo Coding. Show the user their complete learning dashboard.

Instructions

  1. Read the user's profile from ~/.code-sensei/profile.json

    • If no profile exists, create a new one and welcome them
  2. Calculate current stats:

    • Current belt and XP
    • Progress to next belt (percentage and bar)
    • Mastery gate status for next belt promotion
    • Current streak (consecutive days with at least one session)
    • Total quizzes taken and accuracy rate
    • Concepts mastered vs in-progress vs locked
    • Total sessions completed
  3. Display the dashboard:

🥋 CodeSensei — Your Learning Journey
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[Belt Emoji] [BELT NAME]
[Progress bar] [current XP] / [next belt XP] XP ([%]%)
Next belt: [Next Belt Emoji] [Next Belt Name]

🎯 Promotion Requirements for [Next Belt]:
   ⚡ XP: [current]/[required] [✅ or ❌]
   🧠 Concepts mastered: [current]/[required] [✅ or ❌]
   📊 Quiz accuracy: [current]% / 60% [✅ or ❌]

🔥 Streak: [N] days
📊 Quizzes: [correct]/[total] ([accuracy]% accuracy)
📚 Sessions: [total sessions]

Skills Mastered ✅ ([count] — quizzed correctly 3+ times)
─────────────────
[List of mastered concepts with checkmarks]

Skills In Progress 📖 ([count])
─────────────────────
[List with mastery progress: "variables — 2/3 correct quizzes"]

Skills Seen But Not Quizzed 🆕 ([count])
─────────────────────────────
[Concepts encountered but never quizzed]

Next Skills 🎯
──────────────
[Ready-to-learn and still-locked concepts with prerequisite status — see step 3b]

Recent Achievements 🏆
──────────────────────
[Last 3-5 notable moments: belt promotions, streaks, first concepts]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🥋 Powered by Dojo Coding | dojocoding.io
Free & Open Source — github.com/dojocodinglabs/code-sensei

3b. Build the Next Skills section by reading data/concept-tree.json:

- Iterate over every concept in every category of `concept-tree.json`.
- Include concepts that have at least one prerequisite AND are not yet in `concepts_mastered`.
- A concept is **ready to learn** when ALL prerequisites are in `concepts_mastered` but the concept itself is not yet mastered (it may or may not be in `concepts_seen`).
- A concept is **still locked** when at least one prerequisite is missing from `concepts_mastered`.
- For each included concept, check each prerequisite ID against `concepts_mastered`:
  - Mastered prerequisite → mark with ✅
  - Unmastered prerequisite → mark with ❌
- Sort the concepts so that **"Ready to learn"** concepts (all prerequisites ✅) appear first, followed by concepts that still have unmet prerequisites (at least one ❌), ordered by fewest unmet prerequisites first.
- Skip concepts whose prerequisites array is empty — those are always available and do not belong in this section.
- Skip concepts the user has already mastered.
- Format each concept as one line:

Read the full file on GitHub · 193 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. yesterday First seen · 193 lines · 18 tokens per session scan A 049e58d31a0c

Subscribe to this mod's changes

progress is a command published in the GitHub repository DojoCodingLabs/code-sensei (14 stars, last pushed 2mo ago), licensed MIT. It adds 18 tokens to every session and 1,611 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 2026-08-30.