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/pieable/dragon-ball-agent/eli5npx skills add pieable/dragon-ball-agent --skill eli5git clone --depth 1 https://github.com/pieable/dragon-ball-agentWhat 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 | $0.00102 | $0.01035 |
| Opus 5 | $0.00051 | $0.00517 |
| Sonnet 5 | $0.00020 | $0.00207 |
| Haiku 4.5 | $0.00010 | $0.00103 |
Grade A, and why
eli5 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 2d 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
面向受众的解释
把复杂内容解释到目标受众能够理解和行动，同时保留会改变判断的事实、边界和不确定性。解释不是降低对方的智力，而是减少他们为了理解当前问题必须承担的领域背景和实现细节。
确定受众和用途
用户明确指定年龄、知识水平、职业或关系时按其要求调整。未指定时，默认面向聪明但不负责日常实现的成年项目负责人：他们需要迅速理解目的、现状、影响、下一步和需要作出的决定，不需要先学习完整技术体系。
解释前先弄清：
- 要解释的核心问题和它为什么重要；
- 当前已确认的事实、假设和未知；
- 哪些机制或取舍会改变行动；
- 受众读完后需要理解、决定或完成什么。
先让人掌握全局
第一层先用日常语言给出足以行动的整体图景，通常涵盖目的、当前状态、下一步、影响和需要的决定，但不机械设置固定标题，也不为简单问题补齐无用项目。
第二层只在有助于理解、核实或行动时展开术语、实现机制、因果链、替代方案和边界条件。用户要求深入时再增加技术细节；不要把大量细节放在结论之前。
类比只在确实能连接受众已有经验时使用。类比必须说明到哪里仍然成立，不能用生动但错误的故事替代真实机制。
视觉优先，文字负责决定
当流程、层级、计划、因果关系或当前位置用图比段落更容易理解时，先给一张整体图，再补少量文字。图先回答“整个任务是什么、现在在哪里、接下来往哪走”，文字只补图中不能安全简化的变化、理由、差距和决定。
普通的结构、流程和计划优先使用 Mermaid。只有交互、筛选、动态关系或多视图切换确实能帮助理解时，才制作自包含 HTML；不要为了显得高级而把一张静态关系图扩成网页。可视化不明显优于短段落时，直接用文字。
一张图只承载一个主要心智模型。阶段报告通常围绕整个任务、已经完成的阶段、当前阶段、后续阶段和受阻位置组织，不把模块清单、测试数量、工具调用和长日志塞进图里。
图后通常只保留三个短点：发生了什么以及为什么；当前成立的结果和第一项未成立的结果；下一步会得到什么新证据或需要用户决定什么。简单情况少于三个，不为套格式补齐。
视觉图是帮助理解的模型，不是完成证据。事实、推断和未知需要区分；重要结论仍附最短可核验依据或文件、页面和运行结果链接。
在多 agent 任务中，subagent 返回证据和限制，由主 agent 形成面向用户的全局图和说明。不要把下属原始报告直接拼接成用户报告，也不要求每条普通进度都生成 Mermaid 或 HTML。
调整语言
- 面向儿童或明确要求经典 ELI5 时，使用短句、具体事物和一个核心类比。
- 面向非技术成年人时，解释必要术语，重点说明现实影响和决定。
- 面向管理者时，优先说明结果、风险、时间、成本和依赖。
- 面向工程师或专业人员时，使用标准术语，集中说明机制、取舍、失败条件和边界，避免居高临下地过度简化。
- 面向家人或朋友时，保持耐心、自然和尊重，不刻意模仿幼儿语气。
准确性边界
不得为了“容易懂”删除会改变决定的前提、限制、风险或不确定性。事实与推断分开表达；不能确定时直接说明，并指出怎样核实。简化可以减少背景负担，不能把多个不同状态合并成错误结论，也不能用肯定语气掩盖证据不足。
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.
- 2d ago First seen · 54 lines · 102 tokens per session scan A 324416158a96
eli5 is a skill published in the GitHub repository pieable/dragon-ball-agent (10 stars, last pushed 3d ago), licensed MIT. It adds 102 tokens to every session and 1,035 once invoked, about $0.0005 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 skills, from other repositories
trulens-notebook-execution
Execute and display Jupyter notebooks for TruLens demos and quickstarts.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
暖纸背景 + Playfair, 左侧学习目标常驻, 含 MCQ 自测页.
master-yinguang
Use when user asks about 印光大师, 净土, 念佛, 持名念佛, 十念法, 摄耳谛听, 老实念佛, 信愿行, 带业往生, 仗佛慈力, 自力他力, 竖出横超, 往生, 极乐, 阿弥陀佛, 净土三经, 敦伦尽分, 闲邪存诚, 因果报应, 文钞, 一函遍复, or wants teaching in 印光大师 Yinguang's voice. Triggers include "印光"、"文钞"、"老实念佛"、"信愿行"、"带业往生"、"仗佛慈力"、"横超竖出"、"都摄六根"、"净念相继"、"敦伦尽分"、"闲邪存诚"、"因果"、"十念法"、"摄耳谛听"、"一函遍复"、"净土三经"、"往生" — invoke…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
obsidian-to-clew-import
Convert an Obsidian vault or wiki-linked markdown graph into a validated structured-learning graph package for Clew. Use when the user wants to inspect a vault, preview whether it imports cleanly, preserve explicit relation markers, choose only the few import settings that matter, and produce a fail-closed package…