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 WOWCharlotte/nanobot-learn --skill nanobot-learngit clone --depth 1 https://github.com/WOWCharlotte/nanobot-learnWrote 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/wowcharlotte/nanobot-learn/nanobot-learn)<a href="https://agentmods.dev/skills/wowcharlotte/nanobot-learn/nanobot-learn"><img src="https://agentmods.dev/badge/skills/wowcharlotte/nanobot-learn/nanobot-learn/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/wowcharlotte/nanobot-learn/nanobot-learn"><img src="https://agentmods.dev/badge/skills/wowcharlotte/nanobot-learn/nanobot-learn.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 | $0.00014 | $0.00420 |
| Opus 5.5 | $0.00006 | $0.00168 |
| Sonnet 5.5 | $0.00003 | $0.00084 |
| Haiku 4.5 | $0.00001 | $0.00042 |
Grade A, and why
nanobot-learn 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 1mo 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
nanobot-learn
Use the nanobot learn command to help users learn about nanobot's architecture or prepare for technical interviews.
Two Modes
- Teacher Mode - Answer questions about nanobot's technical principles based on documentation
- Quiz Mode - Ask questions, evaluate user answers, and provide feedback
Commands
Teacher Mode (Default)
nanobot learn
nanobot learn --mode teacher
nanobot learn --mode teacher --day Day2
Quiz Mode
nanobot learn --mode quiz
nanobot learn --mode quiz --day Day3
Single Question Mode
nanobot learn --message "How does Agent Loop work?"
Interactive Commands
When in interactive mode, users can use:
/mode teacher- Switch to teacher mode/mode quiz- Switch to quiz mode/stats- View learning progress/exit- Exit learn mode
When to Use
Use this skill when:
- User asks about nanobot's architecture, design, or implementation
- User wants to learn about nanobot's code structure
- User is preparing for a nanobot-related technical interview
- User wants to test their knowledge of nanobot
Response Guidelines
- In teacher mode: Answer based on the Day1-7 documentation
- In quiz mode: Ask clear questions, provide constructive feedback
- Keep responses concise and encouraging
- Use Chinese (中文) for communication
Day Topics
| Day | Topic |
|---|---|
| Day1 | 项目结构与核心概念 |
| Day2 | Agent Loop 与 Context |
| Day3 | Memory 与 Session |
| Day4 | Tool 与 Agent 扩展 |
| Day5 | Provider 系统 |
| Day6 | Channel 系统 |
| Day7 | CLI/Cron/Heartbeat |
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.
- 1mo ago First seen · 75 lines · 14 tokens per session scan A 24e10ba60d7f
nanobot-learn is a skill published in the GitHub repository WOWCharlotte/nanobot-learn (102 stars, last pushed 7mo ago), licensed MIT. It adds 14 tokens to every session and 420 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
lean-formalize
Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…
exam-forecast
Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.
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
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.