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 commands/sean-xhz/ai-learning-platform/learn-progressgit clone --depth 1 https://github.com/Sean-xhz/ai-learning-platformWrote 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/commands/sean-xhz/ai-learning-platform/learn-progress)<a href="https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-progress"><img src="https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-progress.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 | $0.00039 | $0.00730 |
| Opus 5 | $0.00019 | $0.00365 |
| Sonnet 5 | $0.00008 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
learn-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 3d 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
/learn-progress
请给我看一下学习进度总览。
$ARGUMENTS
学习计划进度（锚定每日状态行 - **状态**： 统计——注释行、笔记标题均不会误计）：
- 总天数：
grep -Fc -- '- **状态**：' learning-plan.md 2>/dev/null - 已完成：
grep -Fc -- '- **状态**：✅ 已完成' learning-plan.md 2>/dev/null - 进行中：
grep -Fc -- '- **状态**：🔄 进行中' learning-plan.md 2>/dev/null - 未完成：
grep -Fc -- '- **状态**：⬜ 未开始' learning-plan.md 2>/dev/null
学习增益统计（数据源 = progress-dashboard.md「每日进度」表，由 progress-tracker Hook 自动维护；learning-plan.md 不再维护独立增益表）：
- 平均 Pre-test：
grep -A 100 '每日进度' progress-dashboard.md 2>/dev/null | awk -F'|' '/Day [0-9]/{split($4,a,"/"); gsub(/[^0-9]/,"",a[1]); if(a[1]!=""){s+=a[1]; n++}} END{if(n>0)printf "%.1f",s/n; else print "N/A"}' - 平均 Post-test：
grep -A 100 '每日进度' progress-dashboard.md 2>/dev/null | awk -F'|' '/Day [0-9]/{split($5,a,"/"); gsub(/[^0-9]/,"",a[1]); if(a[1]!=""){s+=a[1]; n++}} END{if(n>0)printf "%.1f",s/n; else print "N/A"}'
复习队列状态（P1-7，若 review-queue.md 存在则读取）：
- 待复习 / 已掌握 / carryover 各多少项
- 哪些盲区「忘记次数」≥2（顽固弱项，取队列
忘记次数列） - 哪些盲区在多天反复出现（最常出现的盲区）
请汇总以上数据，给出：
- 当前进度和健康度判断（完成率 vs 预期时间）
- 学习增益趋势（增量是在上升还是下降？）
- 五维度雷达图（文字版）：概念理解 / 场景应用 / 边界认知 / 跨域联想 / 术语理解
- 六角色表现评估：哪些角色发挥了最大价值？哪些角色被低估了？
- 学习模式建议：当前模式是否仍然合适？是否需要切换？
- 盲区与记忆巩固：最常出现的盲区、顽固弱项（
忘记次数≥2）、已掌握多少；是否需要在下一个缓冲日做一次深度复习
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.
- 3d ago First seen · 34 lines · 39 tokens per session scan A 95f4cb582d8a
learn-progress is a command published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 730 once invoked, about $0.0002 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.
Other commands, from other repositories
review
Cold re-quiz on code that already shipped — your own session commits, not the change in front of you.
learn-story-flow
Learn story-flow concepts with interactive guidance for junior developers.
no-vibe
Enter no-vibe mode in OpenCode (tutor mode, no direct project file writes).
teach-me-testing
Teach testing progressively through structured sessions. Use when user says ""lets learn testing"" or ""I want to study test practices"".
setup-bigquery.es
Command "setup-bigquery.es" from minicoohei/ai-agent-camp, covering configuración de autenticación bigquery / gcp, step 0: verificar el progreso de configuración, lo que hará en esta sesión, verificación de preparación and step 1: instalación de gcloud cli.
setup-content
Lesson command — 教材コンテンツの初回セットアップ.