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 skills add yyz666ai/Learning-Agent --skill spaced-reviewgit clone --depth 1 https://github.com/yyz666ai/Learning-AgentWrote 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/yyz666ai/learning-agent/spaced-review)<a href="https://agentmods.dev/skills/yyz666ai/learning-agent/spaced-review"><img src="https://agentmods.dev/badge/skills/yyz666ai/learning-agent/spaced-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yyz666ai/learning-agent/spaced-review"><img src="https://agentmods.dev/badge/skills/yyz666ai/learning-agent/spaced-review.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00037 | $0.00453 |
| Opus 5 | $0.00018 | $0.00227 |
| Sonnet 5 | $0.00007 | $0.00091 |
| Haiku 4.5 | $0.00004 | $0.00045 |
Grade A, and why
spaced-review 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 9d 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
间隔复习
用少量、可检索的任务验证长期保留情况；准备任务和学习者完成任务是两个不同状态。
执行流程
- 只读取
user-data/reviews/review-schedule.json、到期项目引用的掌握度节点和必要概念定义；不得扫描全部历史。 - 使用
tools.review_schedule.due_items选择最多五项，按优先级和到期时间排序。没有到期项时简短报告，不修改掌握状态。 - 混合安排三类任务：无提示回忆、用自己的话解释、短代码或真实代码迁移。隐藏旧答案和旧参考实现。
- 每次只呈现一个题目并等待回答。提示必须走 L0-L5，记录最高提示等级；复习失败或 L4 帮助会缩短下次间隔。
- 后台或定时运行只能准备今日任务，不能把未作答内容标记为完成，也不能制造学习证据。
- 用户作答后路由到
assignment-review核验证据，再用tools.review_schedule.next_interval_days计算间隔。 - 只有证据核验成功后，才依据
references/state-contract.md更新复习计划和掌握证据。
手动与定时调用
- 手动调用：立即选择到期内容并开始第一题。
- 定时调用：使用
references/scheduled-run.md中的耐久提示词准备任务；具体运行频率由用户在 Codex 中确认和创建。
边界
- 只能写入
user-data/，目标代码保持只读。 - 不根据“已提醒”或“已打开任务”推进复习阶段。
- 状态损坏、时区不明确或日期无法解析时停止写入并报告具体问题。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 30 lines · 37 tokens per session scan A 2438b3c6cd65
spaced-review is a skill published in the GitHub repository yyz666ai/Learning-Agent (1 stars, last pushed 9d ago), licensed MIT. It adds 37 tokens to every session and 453 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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