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 agentmods add commands/teddy563/mcwrench/brandgit clone --depth 1 https://github.com/Teddy563/mcwrenchWrote 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/commands/teddy563/mcwrench/brand)<a href="https://agentmods.dev/commands/teddy563/mcwrench/brand"><img src="https://agentmods.dev/badge/commands/teddy563/mcwrench/brand.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00327 |
| Opus 5 | $0.00013 | $0.00163 |
| Sonnet 5 | $0.00005 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
brand 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 3d 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
Use the server-branding skill to build a brand kit for: $ARGUMENTS
- Read
skills/_cache/server-profile.jsonif present (usegamemodefor tone,chatFormatterto pick MiniMessage vs legacy). Otherwise ask only for: name (or brainstorm), vibe/tone, gamemode, and which MOTD/chat plugins are in use. - Follow
references/format-target-matrix.mdto emit each piece in the format its target parses, and build MiniMessage only fromreferences/minimessage-cheatsheet.md. Pick a tone fromreferences/tone-presets.md. - Produce identity + MOTD (both MiniMessage and legacy
&#RRGGBB) + rank ladder; add store, Discord, and in-game text if asked. To expand a gradient to legacy hex, runnode "${CLAUDE_PLUGIN_ROOT}/skills/server-branding/scripts/format.mjs" --to-legacy "<gradient:#a:#b>text</gradient>". - Hand the rank ladder to permissions-helper for LuckPerms tracks; fetch any unfamiliar plugin keys with learn-plugin-docs. Never invent config keys. Keep store/EULA copy compliant.
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.
- 3d ago First seen · 20 lines · 0 tokens per session scan A 99d586f5d287
brand is a command published in the GitHub repository Teddy563/mcwrench (1 stars, last pushed 10d ago), licensed MIT. It adds 26 tokens to every session and 327 once invoked, about $0.0001 per session on Opus 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.
Other commands, from other repositories
migrate-catalog
Guided catalog migration flow. Extract Databricks Unity Catalog / HMS metadata, preview the 18-rule DDL rewrite, then batched replay on AIDP. Asks before destructive replay step.
github-modes
This document describes all GitHub integration modes available in Claude-Flow with ruv-swarm coordination. Each mode is optimized for specific GitHub workflows and includes batch tool integration for maximum efficiency.
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.