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 jamestorrevillas/dev-skills --skill ai-assisted-learninggit clone --depth 1 https://github.com/jamestorrevillas/dev-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/jamestorrevillas/dev-skills/ai-assisted-learning)<a href="https://agentmods.dev/skills/jamestorrevillas/dev-skills/ai-assisted-learning"><img src="https://agentmods.dev/badge/skills/jamestorrevillas/dev-skills/ai-assisted-learning/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/jamestorrevillas/dev-skills/ai-assisted-learning"><img src="https://agentmods.dev/badge/skills/jamestorrevillas/dev-skills/ai-assisted-learning.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 | $0.00084 | $0.01793 |
| Opus 5 | $0.00042 | $0.00897 |
| Sonnet 5 | $0.00017 | $0.00359 |
| Haiku 4.5 | $0.00008 | $0.00179 |
Grade A, and why
ai-assisted-learning 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.
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-Assisted Learning
Core Philosophy
AI raises the floor of developer competence — but the ceiling of senior expertise is defined by judgment, not syntax.
The biggest risk of AI-assisted learning is "Comprehension Debt" — shipping code you don't understand. The goal is to use AI as a force multiplier for your own thinking, not a replacement for it.
The rule: Use AI to understand faster, not to skip understanding.
The Socratic Method (Best for Deep Learning)
Instead of asking for answers, ask for dialogue:
Setup
I want to learn [topic] through dialogue. Do NOT give me solutions directly.
Instead:
- Ask me questions to guide my thinking
- Point out what I'm missing without filling it in
- Challenge my assumptions
- Only confirm when my reasoning is correct
My current understanding: [what you know]
My question: [what you want to understand]
Why It Works
Forces you to articulate your thinking → surfaces hidden gaps → builds durable mental models instead of just copying answers.
Socratic Learning Phases
| Phase | What to Do | AI's Role |
|---|---|---|
| 1. Debate | Ask "why does this work?" | Interrogate, challenge assumptions |
| 2. Crystallize | Convert discussion into a spec | Confirm your architecture is sound |
| 3. Anchor | Write tests before implementation | Define failure criteria |
| 4. Implement | Build step by step | Guide, not do |
| 5. Validate | Review your work | Find gaps, suggest improvements |
Learning New Technologies
The AI Learning Loop
1. OVERVIEW: "Give me a 5-minute overview of [tech].
What problem does it solve? When should I use it vs alternatives?"
2. MENTAL MODEL: "Explain the core concepts I need to understand
before writing any code."
3. GUIDED BUILD: "Walk me through building [small practical example].
Explain each decision as we go."
4. CHALLENGE ME: "Quiz me on what I just learned.
Ask about edge cases and gotchas."
5. APPLY: Build something real with the new tech.
6. REVIEW: "Review my implementation. What would a senior [X]
developer change and why?"
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 · 236 lines · 0 tokens per session scan A 90b3c87b3fb3
ai-assisted-learning is a skill published in the GitHub repository jamestorrevillas/dev-skills (3 stars, last pushed 5mo ago), licensed MIT. It adds 84 tokens to every session and 1,793 once invoked, about $0.0004 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
coaching-techniques
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counseling-psychology
Therapeutic frameworks, assessment, ethical practice, and client documentation for counselors and psychologists.
cognitive-load
Don't overwhelm — chunk, scaffold, summarize first.
learning-psychology
Help humans learn through partnership, not instruction.
onboard
Walk a new teammate through the team's curated agent toolchain.
learn
Learn and understand a concept in depth. Args.