Borrowing it
Nothing to install: this file belongs to enowdev/enowx-rag. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/enowdev/enowx-rag/main/CLAUDE.mdgit clone --depth 1 https://github.com/enowdev/enowx-ragWrote 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/instructions/enowdev/enowx-rag/claude-md)<a href="https://agentmods.dev/instructions/enowdev/enowx-rag/claude-md"><img src="https://agentmods.dev/badge/instructions/enowdev/enowx-rag/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/instructions/enowdev/enowx-rag/claude-md"><img src="https://agentmods.dev/badge/instructions/enowdev/enowx-rag/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 | $0.00586 | $0.00586 |
| Opus 5.5 | $0.00234 | $0.00234 |
| Sonnet 5.5 | $0.00117 | $0.00117 |
| Haiku 4.5 | $0.00059 | $0.00059 |
Grade A, and why
enowx-rag 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.
What it actually says
Claude instructions for this project
This project is enowx-rag, a per-project RAG memory MCP server.
Setup command
If the user asks to install the skill or MCP server, run:
mkdir -p ~/.factory/skills/enowx-rag
cp /Users/enowdev/Project/enowx-rag/skill/enowx-rag.md ~/.factory/skills/enowx-rag/skill.md
cd /Users/enowdev/Project/enowx-rag/mcp-server
go build ./cmd/mcp-server
For local backend (TEI fallback):
cd /Users/enowdev/Project/enowx-rag/mcp-server
docker compose up -d qdrant tei-embedding
MCP server config
Voyage AI (recommended):
{
"mcpServers": {
"enowx-rag": {
"command": "/Users/enowdev/Project/enowx-rag/mcp-server/mcp-server",
"env": {
"RAG_VECTOR_STORE": "qdrant",
"RAG_QDRANT_URL": "http://localhost:6333",
"RAG_VOYAGE_API_KEY": "your-voyage-api-key",
"RAG_VOYAGE_MODEL": "voyage-4"
}
}
}
}
Self-hosted TEI:
{
"mcpServers": {
"enowx-rag": {
"command": "/Users/enowdev/Project/enowx-rag/mcp-server/mcp-server",
"env": {
"RAG_VECTOR_STORE": "qdrant",
"RAG_EMBEDDER": "tei",
"RAG_QDRANT_URL": "http://localhost:6333",
"RAG_TEI_URL": "http://localhost:8081"
}
}
}
}
Always use RAG memory
- Before coding: call
rag_retrieve_contextwith project IDenowx-ragand the user's query. - After coding: call
rag_indexto save new facts, design decisions, and patterns under project IDenowx-rag.
Keep index chunks concise and tag metadata such as type:architecture, type:decision, type:howto, or type:snippet.
Reference
- Setup guide: https://github.com/enowdev/enowx-rag/blob/main/README.md
- Skill guide: https://github.com/enowdev/enowx-rag/blob/main/skill/enowx-rag.md
- Agent install guide: https://github.com/enowdev/enowx-rag/blob/main/AGENTS.md
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 · 73 lines · 586 tokens per session scan A dad313f5a98e
enowx-rag CLAUDE.md is an instructions file published in the GitHub repository enowdev/enowx-rag (41 stars, last pushed 7d ago), licensed Apache-2.0. It adds 586 tokens to every session, about $0.0023 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.
enowx-rag CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| enowx-rag CLAUDE.mdenowdev/enowx-rag | Instructions file | 41 | 7d ago | Apache-2.0 | A | 586 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |