Borrowing it
Nothing to install: this file belongs to wbern/agent-instructions. 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/wbern/agent-instructions/main/.claude/commands/gastown-setup.mdgit clone --depth 1 https://github.com/wbern/agent-instructionsWrote 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/wbern/agent-instructions/gastown-setup)<a href="https://agentmods.dev/commands/wbern/agent-instructions/gastown-setup"><img src="https://agentmods.dev/badge/commands/wbern/agent-instructions/gastown-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/commands/wbern/agent-instructions/gastown-setup"><img src="https://agentmods.dev/badge/commands/wbern/agent-instructions/gastown-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 | $0.00025 | $0.01486 |
| Opus 5.5 | $0.00010 | $0.00594 |
| Sonnet 5.5 | $0.00005 | $0.00297 |
| Haiku 4.5 | $0.00003 | $0.00149 |
Grade A, and why
gastown-setup 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
General Guidelines
Output Style
- Never explicitly mention TDD in code, comments, commits, PRs, or issues
- Write natural, descriptive code without meta-commentary about the development process
- The code should speak for itself - TDD is the process, not the product
Beads is available for task tracking. Use mcp__beads__* tools to manage issues (the user interacts via bd commands).
Plan File Restriction
NEVER create, read, or update plan.md files. Claude Code's internal planning files are disabled for this project. Use other methods to track implementation progress (e.g., comments, todo lists, or external tools).
Gas Town Setup
Bootstrap a new Gas Town installation — the multi-agent workspace from Steve Yegge (overview post).
This command leans on the upstream Gas Town docs rather than duplicating install steps that will drift. Your job is to walk the user through the decision points and hand off to the canonical instructions at the right time.
Phase 0: Prerequisite check
Verify the environment before suggesting anything:
| Check | Pass condition |
|---|---|
gt binary present |
command -v gt succeeds |
tmux present |
command -v tmux succeeds |
~/gt/ absent or empty |
First-time install only — don't clobber an existing town |
If ~/gt/ already exists and contains a settings/ or mayor/ dir, stop.
Show the user gt status and let them decide whether to repair, extend, or
nuke before reinstalling. Do not proceed past this point automatically.
If gt is missing, point the user at the install instructions in
gastown/README and exit.
Phase 1: Ask the user which flavor they want
Use AskUserQuestion:
Question: "Which Gas Town flavor do you want to bootstrap?" (header: "Flavor")
Options:
- Default (autonomous) — "Out-of-the-box Gas Town with full autonomous patrols. Higher token burn, more emergent behavior."
- Manual mode (me-and-my-crew preset) — "Apply the wbern/gastown-me-and-my-crew preset: disables autonomous patrols, keeps crew workers only. Lower token burn, you drive the work."
- Skip preset for now — "Just install default Gas Town. I can apply a preset later by visiting the preset repo."
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 · 154 lines · 25 tokens per session scan A d150e1c873c2
gastown-setup is a command published in the GitHub repository wbern/agent-instructions (168 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 1,486 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 2026-08-30.
Other commands, from other repositories
ws
Word summary — anything told at N levels, from N words down to 1 word, for anything: a topic ("russian literature"), a URL, YouTube link, file, pasted text, a question, or "this". A leading number sets N (5 by default). Shortcut for the Fabric skill's WordSummary intent.
cancel-ralph
Cancel active Ralph Loop.
engage.actions
Execute Phase 7 - Actions on Objectives and Goal Achievement.
r
Resume the last handoff and carry on with the outstanding work.
focus
You are an ADHD focus assistant. Help the user commit to ONE task and block mental distractions.
stuck
You are an ADHD-friendly unblocking assistant. Help users get unstuck when they don't know what to do.