luongnv89/claude-howto is a visual, example-based guide to Claude Code, a coding tool that supports agents, hooks, skills, slash commands, and MCP servers. Developers use it to learn Claude Code through practical workflows and copyable templates, including the commands, agents, skills, plugins, and instructions catalogued here.
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 luongnv89/claude-howto --skill claude-mdgit clone --depth 1 https://github.com/luongnv89/claude-howtoWrote 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/luongnv89/claude-howto/claude-md)<a href="https://agentmods.dev/skills/luongnv89/claude-howto/claude-md"><img src="https://agentmods.dev/badge/skills/luongnv89/claude-howto/claude-md/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/luongnv89/claude-howto/claude-md"><img src="https://agentmods.dev/badge/skills/luongnv89/claude-howto/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 3 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00020 | $0.01899 |
| Opus 5.5 | $0.00008 | $0.00760 |
| Sonnet 5.5 | $0.00004 | $0.00380 |
| Haiku 4.5 | $0.00002 | $0.00190 |
Grade A, and why
claude-md 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 6d 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty). User may specify:
create- Create new CLAUDE.md from scratchupdate- Improve existing CLAUDE.mdaudit- Analyze and report on current CLAUDE.md quality- A specific path to create/update (e.g.,
src/api/CLAUDE.mdfor directory-specific instructions)
Core Principles
LLMs are stateless: CLAUDE.md is the main project file loaded into every conversation (alongside auto memory and unscoped rules). It serves as the primary onboarding document for AI agents into your codebase.
The Golden Rules
-
Less is More: Frontier LLMs can follow ~150-200 instructions. Claude Code's system prompt already uses ~50. Keep your CLAUDE.md focused and concise.
-
Universal Applicability: Only include information relevant to EVERY session. Task-specific instructions belong in separate files.
-
Don't Use Claude as a Linter: Style guidelines bloat context and degrade instruction-following. Use deterministic tools (prettier, eslint, etc.) instead.
-
Never Auto-Generate: CLAUDE.md is the highest leverage point of the AI harness. Craft it manually with careful consideration.
Execution Flow
1. Project Analysis
First, analyze the current project state:
-
Check for existing CLAUDE.md files:
- Root level:
./CLAUDE.mdor.claude/CLAUDE.md - Directory-specific:
**/CLAUDE.md - Global user config:
~/.claude/CLAUDE.md
- Root level:
-
Identify the project structure:
- Technology stack (languages, frameworks)
- Project type (monorepo, single app, library)
- Development tools (package manager, build system, test runner)
-
Review existing documentation:
- README.md
- CONTRIBUTING.md
- package.json, pyproject.toml, Cargo.toml, etc.
2. Content Strategy (WHAT, WHY, HOW)
Structure CLAUDE.md around three dimensions:
WHAT - Technology & Structure
- Technology stack overview
- Project organization (especially important for monorepos)
- Key directories and their purposes
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.
- 6d ago Changed 002fe8ddf63b
- 10d ago Changed · +1 lines 3c3309bb2cfa
- 29d ago Changed · +1 lines a6f248ca47c5
- 1mo ago Changed · +1 lines d438c358976c
- 1mo ago First seen · 225 lines · 20 tokens per session scan A ad38cf4093d8
claude-md is a skill published in the GitHub repository luongnv89/claude-howto (45,056 stars, last pushed 6d ago), licensed MIT. It adds 20 tokens to every session and 1,899 once invoked, about $0.0001 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 2026-08-30.
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