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.
git clone --depth 1 https://github.com/TheBeardedBearSAS/claude-craftWrote 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/thebeardedbearsas/claude-craft/docker-compose-setup)<a href="https://agentmods.dev/commands/thebeardedbearsas/claude-craft/docker-compose-setup"><img src="https://agentmods.dev/badge/commands/thebeardedbearsas/claude-craft/docker-compose-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/thebeardedbearsas/claude-craft/docker-compose-setup"><img src="https://agentmods.dev/badge/commands/thebeardedbearsas/claude-craft/docker-compose-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 | $0.00003 | $0.01489 |
| Opus 5.5 | $0.00001 | $0.00596 |
| Sonnet 5.5 | $0.00001 | $0.00298 |
| Haiku 4.5 | $0.00000 | $0.00149 |
Grade A, and why
docker-compose-setup scanned grade A 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
test: ["CMD", "curl", "-f", "http://localhost:3000/health"] How it starts
The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker Compose Einrichtung
Du bist ein Docker Compose Orchestrierungs-Experte. Du musst eine vollständige und optimierte Konfiguration für eine Multi-Service-Umgebung generieren.
Argumente
$ARGUMENTS
Argumente:
- Benötigte Services (z.B. postgres, redis, rabbitmq)
- Kontext: dev, staging, prod
- Tech Stack (z.B. symfony, node, python)
Beispiel: /docker:compose-setup postgres,redis context:dev stack:symfony
Plan-Modus
Der Plan-Modus ist obligatorisch. Vor der Ausführung aktiviert Claude den Plan-Modus, um betroffenen Code zu analysieren, einen Implementierungsplan vorzuschlagen und auf Ihre Validierung zu warten, bevor Änderungen vorgenommen werden.
MISSION
Schritt 1: Anforderungen analysieren
Services und ihre Interaktionen identifizieren:
══════════════════════════════════════════════════════════════
🐳 DOCKER COMPOSE ANALYSE
══════════════════════════════════════════════════════════════
Projekt: {name}
Kontext: {dev|staging|prod}
Stack: {stack}
──────────────────────────────────────────────────────────────
📋 IDENTIFIZIERTE SERVICES
──────────────────────────────────────────────────────────────
| Service | Image | Interner Port | Exponierter Port | Volumes |
|---------|-------|---------------|------------------|---------|
| app | custom | 3000 | 3000 | code |
| db | postgres:16 | 5432 | 5432 (dev) | data |
| redis | redis:7 | 6379 | - | data |
Schritt 2: docker-compose.yml generieren
# docker-compose.yml - Gemeinsame Basis
services:
app:
build:
context: .
dockerfile: Dockerfile
target: development
volumes:
- .:/app:cached
- /app/node_modules
environment:
- NODE_ENV=development
- DATABASE_URL=postgresql://user:password@db:5432/app
- REDIS_URL=redis://redis:6379
depends_on:
db:
condition: service_healthy
redis:
condition: service_healthy
networks:
- backend
db:
image: postgres:16-alpine
environment:
POSTGRES_USER: user
POSTGRES_PASSWORD: password
POSTGRES_DB: app
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U user -d app"]
interval: 10s
timeout: 5s
retries: 5
networks:
- backend
redis:
image: redis:7-alpine
command: redis-server --appendonly yes
volumes:
- redis_data:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 5s
retries: 5
networks:
- backend
networks:
backend:
volumes:
postgres_data:
redis_data:
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.
- 7d ago Changed · -2 lines baae6989cb4b
- 1mo ago First seen · 260 lines · 3 tokens per session scan A 5448104c4a2e
docker-compose-setup is a command published in the GitHub repository TheBeardedBearSAS/claude-craft (107 stars, last pushed 7d ago), licensed MIT. It adds 3 tokens to every session and 1,489 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
test-suite
Run comprehensive test suite with coverage analysis.
standardize-claude-md
Add missing toolkit sections (Related Global Rules, Quick Start) to existing CLAUDE.md.
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.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.