tutor-code

tutor-code is a skill for Claude Code, Codex from fikrilal/engineering-agent-skills. It costs 71 tokens per session (646 once invoked), scanned A, original, MIT.

A teaching guide for understanding a specific piece of code, language feature, or framework pattern in an unfamiliar technology stack.

In plain words
What is it for?
Use it to understand what code does, why it is structured that way, how it runs, and how its language or framework features relate to familiar ones.
Why use it?
It turns confusing repository code into an explanation connected to concepts the developer already knows, without expanding into an unrelated full course.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/fikrilal/engineering-agent-skills/tutor-code
Any agent
npx skills add fikrilal/engineering-agent-skills --skill tutor-code
Clone the repo
git clone --depth 1 https://github.com/fikrilal/engineering-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for tutor-code

README.md
[![agentmods](https://agentmods.dev/badge/skills/fikrilal/engineering-agent-skills/tutor-code.svg)](https://agentmods.dev/skills/fikrilal/engineering-agent-skills/tutor-code)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 646 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00071 $0.00646
Opus 5 $0.00036 $0.00323
Sonnet 5 $0.00014 $0.00129
Haiku 4.5 $0.00007 $0.00065

Measured 3d ago against content hash 1920603ab50a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

skills/tutor-code/SKILL.md · 58 lines

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

  1. 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.
  2. Read repository instructions and inspect the target in context: declarations, call sites, concrete implementations, tests, and relevant configuration.
  3. Explain the code's role in the product before explaining syntax.
  4. Walk through runtime behavior in execution order. Track important values, ownership, mutation, errors, and side effects.
  5. Isolate only the unfamiliar language or framework constructs needed to understand that behavior.
  6. Map each construct to a known concept when the structures genuinely correspond. State where the analogy breaks down.
  7. Explain why this implementation shape is useful here and whether it is a language requirement, framework convention, repository convention, or design choice.
  8. 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:

  1. Purpose: what responsibility this code has in the system.
  2. Runtime story: what happens in execution order.
  3. 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.

Read the full file on GitHub · 58 lines

Changes

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.

  1. 3d ago First seen · 58 lines · 71 tokens per session scan A 1920603ab50a

Subscribe to this mod's changes

tutor-code is a skill published in the GitHub repository fikrilal/engineering-agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 646 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.

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