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 eitelcj/Claude-Weekend --skill claude-mdgit clone --depth 1 https://github.com/eitelcj/Claude-WeekendWrote 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/eitelcj/claude-weekend/claude-md)<a href="https://agentmods.dev/skills/eitelcj/claude-weekend/claude-md"><img src="https://agentmods.dev/badge/skills/eitelcj/claude-weekend/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/eitelcj/claude-weekend/claude-md"><img src="https://agentmods.dev/badge/skills/eitelcj/claude-weekend/claude-md.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 | $0.00020 | $0.01489 |
| Opus 5.5 | $0.00008 | $0.00596 |
| Sonnet 5.5 | $0.00004 | $0.00298 |
| Haiku 4.5 | $0.00002 | $0.00149 |
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 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 — 213 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 only file automatically included in every conversation. 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.
- 2mo ago First seen · 213 lines · 20 tokens per session scan A 9638d1fc2607
claude-md is a skill published in the GitHub repository eitelcj/Claude-Weekend (2 stars, last pushed 6mo ago), licensed MIT. It adds 20 tokens to every session and 1,489 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 2026-08-31.
claude-md compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| claude-mdeitelcj/Claude-Weekend | Skill | 2 | 6mo ago | MIT | A | 20 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |