Borrowing it
Nothing to install: this file belongs to wavewand/wand. 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/wavewand/wand/main/CLAUDE.mdgit clone --depth 1 https://github.com/wavewand/wandWrote 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/wavewand/wand/claude-md)<a href="https://agentmods.dev/instructions/wavewand/wand/claude-md"><img src="https://agentmods.dev/badge/instructions/wavewand/wand/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/wavewand/wand/claude-md"><img src="https://agentmods.dev/badge/instructions/wavewand/wand/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 | $0.05131 | $0.05131 |
| Opus 5.5 | $0.02052 | $0.02052 |
| Sonnet 5.5 | $0.01026 | $0.01026 |
| Haiku 4.5 | $0.00513 | $0.00513 |
Grade B, and why
wand CLAUDE.md scanned grade B with 1 finding 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.
Reads MCP configurationmediumAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
- Restart Claude Desktop to load the MCP configuration How it starts
The opening of the file, as written. The whole thing — 609 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wand MCP Tool - Claude Context Guide
IMPORTANT: Initial Setup Check
Every Claude instance should perform these steps before proceeding:
-
Verify Wand MCP Server Connection:
claude mcp listExpected output should show:
wand: ... - ✓ Connected -
Test Ollama Integration:
Use mcp__wand__ollama with operation "list_models"This confirms the Ollama server at
http://localhost:11434is accessible (configure via OLLAMA_BASE_URL env var) -
If tools are not available:
- Run the add_to_claude.sh script from the wand directory
- Restart Claude Desktop to load the MCP configuration
- Verify connection again with steps 1 and 2
Overview
Wand is a Model Context Protocol (MCP) server that provides 50+ integrations for AI development workflows. This guide explains how to use Wand's Ollama integration to offload heavy AI tasks to local models while maintaining quality control.
Quick Reference for M1 Max 64GB Setup
# Your optimal settings for most tasks
{
"model": "qwen3:30b-a3b-instruct-2507-q4_K_M", # Best quality
"max_tokens": 4096, # Can go up to 8192+ comfortably
"temperature": 0.2 # Consistency over creativity
}
# For speed-critical simple tasks
{
"model": "qwen2.5-coder:14b-instruct",
"max_tokens": 2048,
"temperature": 0.3
}
Key Insight: With 64GB RAM, prefer single large requests over decomposition. You can generate complete implementations without hitting memory limits.
Available Wand Tools
When Wand is properly configured, you'll have access to MCP tools prefixed with mcp__wand__. The primary tool for AI code generation is:
mcp__wand__ollama
Local AI model execution through Ollama server (default: http://localhost:11434, configure via OLLAMA_BASE_URL)
Core Operations
1. Code Generation (generate operation)
Use this for heavy code generation tasks:
Tool: mcp__wand__ollama
Operation: generate
Parameters:
- prompt: The code generation request
- model: (optional) defaults to "qwen3:30b-a3b-instruct-2507-q4_K_M"
- temperature: (optional) defaults to 0.7
- max_tokens: (optional) defaults to 2048
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 · 609 lines · 5,131 tokens per session scan B 3164e90267d5
wand CLAUDE.md is an instructions file published in the GitHub repository wavewand/wand (3 stars, last pushed 1y ago), licensed MIT. It adds 5,131 tokens to every session, about $0.0205 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads mcp configuration). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
wand CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| wand CLAUDE.mdwavewand/wand | Instructions file | 3 | 1y ago | MIT | B | 5,131 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 144k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,685 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,086 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 281k | today | MIT | A | 4,335 | Codex, OpenCode |