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 fikrilal/engineering-agent-skills --skill tutor-codegit clone --depth 1 https://github.com/fikrilal/engineering-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/fikrilal/engineering-agent-skills/tutor-code)<a href="https://agentmods.dev/skills/fikrilal/engineering-agent-skills/tutor-code"><img src="https://agentmods.dev/badge/skills/fikrilal/engineering-agent-skills/tutor-code/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/fikrilal/engineering-agent-skills/tutor-code"><img src="https://agentmods.dev/badge/skills/fikrilal/engineering-agent-skills/tutor-code.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 | $0.00071 | $0.00646 |
| Opus 5.5 | $0.00028 | $0.00258 |
| Sonnet 5.5 | $0.00014 | $0.00129 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
tutor-code 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tutor Code
Teach enough language and framework knowledge for the learner to reason about real repository code. Do not turn a focused question into a generic language course.
Workflow
- Identify the exact learning target and infer the learner's known languages, frameworks, and current depth from the conversation. Ask only when the target or learner context is genuinely ambiguous.
- Read repository instructions and inspect the target in context: declarations, call sites, concrete implementations, tests, and relevant configuration.
- Explain the code's role in the product before explaining syntax.
- Walk through runtime behavior in execution order. Track important values, ownership, mutation, errors, and side effects.
- Isolate only the unfamiliar language or framework constructs needed to understand that behavior.
- Map each construct to a known concept when the structures genuinely correspond. State where the analogy breaks down.
- Explain why this implementation shape is useful here and whether it is a language requirement, framework convention, repository convention, or design choice.
- Stop once the learner can follow the requested code. Add edge cases, tests, or exercises only when requested.
Explanation Depth
Use progressive depth:
- First pass: purpose, runtime story, and only essential syntax.
- Second pass: ownership, types, framework mechanics, and design tradeoffs.
- Deep dive: compiler behavior, memory model, generated code, or advanced internals only when requested or required to answer correctly.
Investigate deeply enough to be correct, but do not front-load deep output.
Output
Default to this compact shape:
- Purpose: what responsibility this code has in the system.
- Runtime story: what happens in execution order.
- Unfamiliar parts: only the syntax or framework concepts blocking understanding, with a precise analogy where useful.
Explain why the shape matters only when it is not obvious. For a short expression, answer directly without manufacturing sections.
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 · 58 lines · 71 tokens per session scan A 1920603ab50a
tutor-code is a skill published in the GitHub repository fikrilal/engineering-agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 71 tokens to every session and 646 once invoked, about $0.0003 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.
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