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 VectorPeak/vectorpeak-agent-skills --skill ai-learning-mentor-vpgit clone --depth 1 https://github.com/VectorPeak/vectorpeak-agent-skillsWrote 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/vectorpeak/vectorpeak-agent-skills/ai-learning-mentor-vp)<a href="https://agentmods.dev/skills/vectorpeak/vectorpeak-agent-skills/ai-learning-mentor-vp"><img src="https://agentmods.dev/badge/skills/vectorpeak/vectorpeak-agent-skills/ai-learning-mentor-vp/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/vectorpeak/vectorpeak-agent-skills/ai-learning-mentor-vp"><img src="https://agentmods.dev/badge/skills/vectorpeak/vectorpeak-agent-skills/ai-learning-mentor-vp.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 | $0.00185 | $0.03089 |
| Opus 5.5 | $0.00074 | $0.01236 |
| Sonnet 5.5 | $0.00037 | $0.00618 |
| Haiku 4.5 | $0.00018 | $0.00309 |
Grade A, and why
ai-learning-mentor-vp 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Learning Mentor VP
Purpose
Use this skill as a personal learning mentor for computer science, AI, LLM, and Agent topics. Route the user's request into one of seven learning modes, ground explanations in user-provided context when present, check local LLM_wiki knowledge when useful, expose weak points, and optionally prepare compact DailyNotes or Wiki candidates.
Default language: Chinese, unless the user asks otherwise.
First Move
- Detect the mode from trigger words.
- Identify the topic, provided materials, known context, and desired output.
- Treat user-provided context as the first grounding layer.
- For memory, analogy, graph, practice, or compression tasks, check known concepts from local
LLM_wikiwhen available. - Do not write to DailyNotes, wiki, mastery, or question bank unless the user explicitly asks to record/save/write/update.
Mode Router
| Mode | Triggers | Use for |
|---|---|---|
| 00 Memory Aid | 00, jy, 辅助记忆, 记忆, 助记, 怎么记, 记不住 |
Build hooks, chunks, mnemonics, contrast pairs, and review prompts |
| 01 Concept Explanation | 01, gn, 概念, 概念讲解, 讲清楚, what/why/how |
Explain a concept top-down |
| 02 Feynman Feedback | 02, fm, 费曼, 费曼学习, 我来讲, 你来追问 |
Let the learner explain, then question and grade |
| 03 Analogy Diff Learning | 03, lb, 类比, 类比学习, diff, 迁移理解 |
Map a new idea to known CS/AI concepts |
| 04 Deliberate Practice | 04, ky, lx, 题目, 出题, 刻意练习, 练习 |
Generate targeted drills and adapt difficulty |
| 05 Knowledge Graph | 05, zs, tp, 知识图谱, 图谱, landscape, 关联概念 |
Build concept landscape and structural links |
| 06 Knowledge Compression | 06, 总结, 提炼, 压缩, 卡片, 记忆卡, 复习卡 |
Extract framework and review cards |
If no trigger is explicit, infer the mode from intent. If multiple modes fit, combine in this order: 01 concept -> 00 memory aid -> 03 analogy -> 05 graph -> 04 practice -> 06 compression.
Known-Concept Check
When the user asks for memory aid, analogy, graph, deliberate practice, compression, or “连接到 LLM_wiki”:
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.
- 2mo ago First seen · 378 lines · 185 tokens per session scan A c56b93bae201
ai-learning-mentor-vp is a skill published in the GitHub repository VectorPeak/vectorpeak-agent-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 185 tokens to every session and 3,089 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
founder-coach
Personal leadership development for founders and first-time CEOs. Covers founder archetype identification, delegation frameworks, energy management, CEO calendar audits, leadership style evolution, blind spot identification, imposter syndrome, founder mental health, and succession planning. Use when a founder feels…
subscription-setup
A setup workflow for creating recurring medical-learning subscriptions after a doctor’s profile has been registered.
study-plan
Build a weekly and daily study schedule from the goal and the available time, with method notes and adjustment rules, delivered as an Excel workbook.
explorer-pipeline
Use when asked to make an interactive 3D explorer of a topic from start to finish, go from a topic to a clickable 3D learning page, or run the whole 3D explorer process. Produces a staged run of explorer-interface-brief, model-prompt-pack and explorer-viewer-builder in order for one topic, with the hand-offs between…
model-prompt-pack
Use when asked to write prompts for image-to-3D or text-to-3D tools, generate 3D models of a topic's parts, plan the assets for a 3D explorer, or build a labelled parts list with sources. Produces prompts for image-to-3D tools, one per object, plus a parts list for labelling in which every label names a trusted…
financial-statement-explainer
Explain a financial statement (P&L, balance sheet, or cash flow) in plain English. Use when asked to explain a P&L / income statement, a balance sheet, a cash flow statement, or to make financials understandable to a non-finance reader. Produces a plain-language walkthrough — what each section means, the line items…