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/guoqiaozhou/study-with-claude-code/statsnpx skills add guoqiaoZhou/study-with-claude-code --skill statsgit clone --depth 1 https://github.com/guoqiaoZhou/study-with-claude-codeWrote 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/guoqiaozhou/study-with-claude-code/stats)<a href="https://agentmods.dev/skills/guoqiaozhou/study-with-claude-code/stats"><img src="https://agentmods.dev/badge/skills/guoqiaozhou/study-with-claude-code/stats.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 | $0.00048 | $0.00688 |
| Opus 5 | $0.00024 | $0.00344 |
| Sonnet 5 | $0.00010 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
swcc-stats 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.
What it actually says
swcc · stats — 复习进度展示
只读地展示一个专题的复习进度。
开始前先读数据契约:
${CLAUDE_PLUGIN_ROOT}/skills/_shared/data-contract.md。本技能只读不写。
参数:$ARGUMENTS —— 可选 topic（默认 config 的 activeTopic）。
核心原则
- 只读，不改任何文件。
- 不编数字。 趋势/统计数据不足时如实留空或省略，绝不臆造。
- 最该复习的排在最前。 薄弱点按
nextReview升序，让用户一眼看到今天该补什么。
流程
1. 加载数据
- topic 缺省 → 读
$HOME/.study-with-cc/config.json的activeTopic（config 不存在或缺 activeTopic 时，按数据契约第九节「兜底」扫topics/自愈，不要直接报错）。 - 该专题不存在 → 提示先
/swcc-plan <topic>，停止。 - 读
progress.json（必要时读review-sessions/做趋势聚合）。
2. 计算
- 按
nodes的status统计:mastered / in_progress / not_started 各占多少、百分比。 weakPoints按nextReview升序排列（最该复习的在前）。- 从
stats取 streak、totalReviewCount、totalReviewTime。
3. 渲染
📊 <topic> 复习进度
━━━━━━━━━━━━━━━━━━━━
🟢 已掌握：<a> / <total> (<x%>)
🟡 学习中：<b> / <total> (<y%>)
🔴 未开始：<c> / <total> (<z%>)
🔴 薄弱点（<n>）
1. <concept>（节点：<node> 上次：<lastReviewed> 下次：<nextReview>）
2. …
🔥 连续复习：<streak> 天
🔢 总复习次数：<totalReviewCount>
⏱️ 总复习时长：<totalReviewTime> 分钟
掌握度变化趋势（可选）:若 review-sessions/ 有多份记录，可按日期聚合各节点掌握度，画一个简单的 ASCII 趋势条;数据不足时省略此段，不要编造数字。
质量基准
- 比例数字和 progress.json 对得上;薄弱点按 nextReview 正确排序。
- 数据不足的段落如实省略，不臆造趋势。
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 · 63 lines · 48 tokens per session scan A 834b285524e8
swcc-stats is a skill published in the GitHub repository guoqiaoZhou/study-with-claude-code (2 stars, last pushed 2mo ago), licensed MIT. It adds 48 tokens to every session and 688 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.
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