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 congmnguyen/claude-code-wsl2-setup --skill deep-teachgit clone --depth 1 https://github.com/congmnguyen/claude-code-wsl2-setupWrote 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/congmnguyen/claude-code-wsl2-setup/deep-teach)<a href="https://agentmods.dev/skills/congmnguyen/claude-code-wsl2-setup/deep-teach"><img src="https://agentmods.dev/badge/skills/congmnguyen/claude-code-wsl2-setup/deep-teach.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00110 | $0.00913 |
| Opus 5 | $0.00055 | $0.00456 |
| Sonnet 5 | $0.00022 | $0.00183 |
| Haiku 4.5 | $0.00011 | $0.00091 |
Grade A, and why
deep-teach 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 8d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Teach
Use this skill to run an interactive teaching session. The goal is not to deliver a polished lecture; the goal is to help the user build durable understanding and prove it through recall.
Teaching Contract
Teach one layer at a time:
- Start with the problem, motivation, and big picture before low-level mechanics.
- Keep each explanation short enough that the user can respond to it.
- Ask the user to restate or apply the idea before moving on.
- Do not treat "I understand" as verification. Verify by asking them to explain, predict, debug, compare, or solve a small example.
- If the user is learning a codebase or artifact, inspect the real files first and anchor explanations to concrete paths, lines, data, or outputs.
Session Workflow
-
Assess first. Ask the user what they already understand, what feels unclear, and what level they want: ELI5, ELI14, intern, practitioner, or expert.
-
Build a running checklist. Maintain a visible markdown checklist with three groups:
- Problem: what exists, why it matters, and what variants or failure modes exist.
- Solution: how it works, why this design was chosen, and which edge cases matter.
- Context: what it impacts downstream and how it connects to neighboring concepts.
-
Teach the next smallest layer. Explain the current layer, then stop. Prefer concrete examples, analogies only when they clarify, and diagrams or code snippets when the topic is structural.
-
Quiz with active recall. Ask one question at a time. Mix formats:
- Open-ended restatement: "Explain this back in your own words."
- Prediction: "What happens if this input changes?"
- Debugging: "Where would this break?"
- Multiple choice with varied correct-option positions.
-
Update the checklist. Tick an item only after the user demonstrates understanding. If their answer is partial, mark what is solid and reteach the missing piece.
-
Iterate until the requested scope is verified. Keep moving from high-level motivation to low-level mechanics to edge cases. End with a compact recap and, when useful, a final synthesis question.
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.
- 8d ago First seen · 86 lines · 110 tokens per session scan A 45dd5f427654
deep-teach is a skill published in the GitHub repository congmnguyen/claude-code-wsl2-setup (50 stars, last pushed 7d ago), licensed MIT. It adds 110 tokens to every session and 913 once invoked, about $0.0006 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 2026-08-30.
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