Borrowing it
Nothing to install: this file belongs to mnott/Whazaa. 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/mnott/Whazaa/main/.claude/skills/setup/SKILL.mdgit clone --depth 1 https://github.com/mnott/WhazaaWrote 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/mnott/whazaa/setup)<a href="https://agentmods.dev/skills/mnott/whazaa/setup"><img src="https://agentmods.dev/badge/skills/mnott/whazaa/setup/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/mnott/whazaa/setup"><img src="https://agentmods.dev/badge/skills/mnott/whazaa/setup.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 | $0.00109 | $0.02779 |
| Opus 5.5 | $0.00044 | $0.01112 |
| Sonnet 5.5 | $0.00022 | $0.00556 |
| Haiku 4.5 | $0.00011 | $0.00278 |
Grade B, and why
setup scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Also ensure `~/.claude/settings.json` has `"mcp__aibroker"` in the `permissions.allow` How it starts
The opening of the file, as written. The whole thing — 333 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Whazaa Setup Skill
Complete autonomous setup of Whazaa from a local clone. Ask the user for input only when a QR code scan is required.
Context
Whazaa is the WhatsApp transport adapter for AIBroker — it is not an MCP server itself. Two pieces are involved:
- AIBroker MCP server (
npx -y -p aibroker aibroker-mcp) — started by Claude Code. Provides thewhatsapp_*tools (plustelegram_*,pailot_*,aibroker_*). It reaches Whazaa's watcher over a Unix Domain Socket. - Whazaa watcher daemon (
dist/index.js watch) — a long-running background process that owns the WhatsApp (Baileys) connection and delivers incoming messages to iTerm2 via AppleScript. Managed by macOS launchd ascom.whazaa.watcher.
Running dist/index.js with no subcommand prints usage and exits — it is a CLI, not a
stdio MCP server. Never register whazaa under mcpServers.
The repo path is needed throughout. Determine it before starting:
REPO="$(pwd)" # if already in the repo
# or use the path the user provided
Step 0: Clone (if applicable)
If the user does NOT already have a local clone, clone first:
git clone https://github.com/mnott/Whazaa.git ~/dev/ai/Whazaa
REPO="$HOME/dev/ai/Whazaa"
Use the user's preferred path if specified, otherwise default to ~/dev/ai/Whazaa.
If already in the repo directory, skip this step and set REPO="$(pwd)".
Step 1: Check Prerequisites
Run these checks. Report failures but continue to gather all issues before stopping.
# Node.js version (must be >= 18)
node --version
# macOS check (watcher requires macOS + iTerm2 + AppleScript)
sw_vers -productVersion
# iTerm2 installed
ls /Applications/iTerm.app 2>/dev/null && echo "iTerm2: OK" || echo "iTerm2: NOT FOUND — install from https://iterm2.com"
# ffmpeg (required for TTS voice notes — WAV to OGG conversion)
which ffmpeg && echo "ffmpeg: OK" || echo "ffmpeg: NOT FOUND — install with: brew install ffmpeg"
# whisper (optional — only needed to receive voice notes from phone)
which whisper 2>/dev/null && echo "whisper: OK" || echo "whisper: optional — install with: pip install openai-whisper"
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.
- 1mo ago Changed bfd5f502a4ad
- 2mo ago First seen · 333 lines · 109 tokens per session scan B c3528612af71
setup is a skill published in the GitHub repository mnott/Whazaa (6 stars, last pushed 13d ago), licensed MIT. It adds 109 tokens to every session and 2,779 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
setup compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| setupmnott/Whazaa | Skill | 6 | 13d ago | MIT | B | 109 | Claude Code |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| azure-mgmt-botservice-dotnetmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 78 | Claude Code |
| fastapi-router-pymicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 46 | Claude Code |
| dev-runtimelangwatch/langwatch | Skill | 5.0k | yesterday | Apache-2.0 | A | 172 | Claude Code |
| api-designericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 105 | Claude Code, Codex |
| migrate-segw-to-raparc-mcp/arc-1 | Skill | 252 | yesterday | MIT | A | 106 | Claude Code |