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 SuperJJ007/eatbook --skill branchgit clone --depth 1 https://github.com/SuperJJ007/eatbookWrote 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/superjj007/eatbook/branch)<a href="https://agentmods.dev/skills/superjj007/eatbook/branch"><img src="https://agentmods.dev/badge/skills/superjj007/eatbook/branch/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/superjj007/eatbook/branch"><img src="https://agentmods.dev/badge/skills/superjj007/eatbook/branch.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 | $0.00106 | $0.00932 |
| Opus 5 | $0.00053 | $0.00466 |
| Sonnet 5 | $0.00021 | $0.00186 |
| Haiku 4.5 | $0.00011 | $0.00093 |
Grade A, and why
branch scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
allowed-tools: Read, Write, WebSearch, WebFetch, Bash(curl *), AskUserQuestion What it actually says
/eatbook:branch — 分支深研
方法论：snowballing 滚雪球（详见 references/lit-search.md）。 目标产物：有理由、有顺序、可执行的三层文献清单——不是论文堆砌。
步骤 1：选分支
- 参数给了分支名则直接用；否则读
overview.md列出候选分支，问用户 - 和用户确认深研目标：通识了解 / 跟进前沿 / 找研究切入点（影响清单层次配比）
- 建
branches/<分支slug>/
步骤 2：定种子（seed papers）
两路并行，得到 2-4 篇种子：
- 教材引文：grep 该分支相关章节笔记和
source/full.md的引文——教科书反复引用的论文天然是经典候选 - 近年综述：WebSearch 找 3-5 年内权威 review（Annual Review 系列 / Nature Reviews 优先），综述的参考文献就是现成的领域地图
步骤 3：三层滚雪球
按 lit-search.md 的流程：
- Backward（经典奠基）：沿种子的参考文献向上游走，找被反复引用的奠基工作
- Forward（里程碑）：用 Semantic Scholar API 查"谁引用了经典"，按引用数+影响力筛出范式转移点
- 前沿（领军学者代表作）：从里程碑作者中找近 3 年仍活跃的高影响力学者，取其代表作
每层 3-6 篇为宜；宁缺毋滥，每篇必须能写出"为什么读"。
步骤 4：产出 reading-list.md
# {分支名} 文献指南
## 深研目标
（用户确认的目标 + 本清单如何服务它）
## 第一层：经典奠基（读懂领域从哪来）
### {作者年份}《标题》
- 为什么读：……
- 读什么：（重点章节/核心结论，不必通读的说明白）
- 图谱连接：关联实体 {entity-id}，读完可新增 {关系}
- 引用规模：约 N 次（Semantic Scholar，查询日期）
## 第二层：里程碑（领域怎么变成今天这样）
（同上结构，按时间排）
## 第三层：前沿（领域正往哪去）
### {学者} —— {机构}
- 地位依据：……（高被引/获奖/里程碑作者）
- 代表作：《…》（年份）+ 为什么是它
## 建议阅读顺序
（考虑依赖关系的串行顺序 + 理由）
步骤 5：交付与回流
- 汇报三层清单概要 + 阅读顺序
- 提醒闭环：想精读的论文 →
/eatbook:ingest <PDF> <领域>（论文可跳过翻译）→/eatbook:read - 更新
00-domain.md：记录该分支已建立文献清单
防幻觉提醒
文献信息（标题/作者/年份/结论）全部以检索结果为准，禁止凭模型记忆给出； 引用数注明查询日期；查不到的信息写"未确认"，不要编。
What ships with it
1 file 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 · 72 lines · 106 tokens per session scan A be8b48855c09
branch is a skill published in the GitHub repository SuperJJ007/eatbook (4 stars, last pushed 3mo ago), licensed MIT. It adds 106 tokens to every session and 932 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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