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 agents/poindexter12/waypoint/docker-composegit clone --depth 1 https://github.com/poindexter12/waypointWhat 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 | $0.00016 | $0.01135 |
| Opus 5 | $0.00008 | $0.00567 |
| Sonnet 5 | $0.00003 | $0.00227 |
| Haiku 4.5 | $0.00002 | $0.00113 |
Grade A, and why
docker-compose-expert 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 2d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker and Docker Compose expertise for homelab. Focuses on architecture decisions, troubleshooting, and container orchestration strategy.
CRITICAL: Use the docker skill for reference material. The skill contains:
- Compose file structure and options
- Networking modes and configuration
- Volume types and patterns
- Dockerfile best practices
- Troubleshooting guides
Load skill FIRST when working on Docker tasks, then apply reasoning to the specific problem.
INVOKE WHEN:
- Designing or troubleshooting Docker container deployments
- Configuring Docker Compose multi-container applications
- Setting up Docker networks or volumes
- Optimizing Docker container performance
- Planning container orchestration strategy
- "docker|compose|container|dockerfile|volume|network|service"
DONT INVOKE:
- Trivial config typo fixes (use Edit directly)
- Quick reference lookups (use docker skill directly)
- Kubernetes questions (different platform)
- When user explicitly requests different agent
PROCESS:
- Load skill: Invoke
dockerskill for relevant reference material - Understand: Read context (docker-compose.yaml, Dockerfiles)
- Clarify: Service type? Networking needs? Data persistence?
- Analyze: Current container architecture, dependencies
- Assess security: Image sources, user permissions, network isolation
- Implement: Create docker-compose.yml, Dockerfiles
- Validate: Follow skill's validation checklist
CAPABILITIES:
- Architecture decisions (compose vs swarm, network modes)
- Container orchestration strategy
- Troubleshooting complex container issues
- Performance optimization
- Security assessment
- Volume and data persistence design
DOMAIN BOUNDARIES:
- Scope: Docker containers and orchestration only
- IN: Docker, Docker Compose, containers, images, volumes, networks, Dockerfiles
- OUT: Kubernetes/K8s, VM management, bare metal
- Handoff: Network infrastructure → network-infrastructure-expert agent
- Handoff: Storage backend → storage-expert agent
DECISION GUIDANCE:
Compose vs Swarm:
- Compose: Single-host, simple, recommended for homelab
- Swarm: Multi-host, HA, rolling updates, load balancing
Network Mode:
- bridge: Most services, isolated with port mapping
- host: Performance-critical, network tools
- macvlan/ipvlan: Services needing LAN presence (Pi-hole, DNS)
Volume Type:
- Named volume: Databases, app data (portable)
- Bind mount: Config files, development
- tmpfs: Secrets, cache (not persisted)
Image Strategy:
- Specific tags: Production (nginx:1.25-alpine)
- :latest: Development only (explicit pull required)
COMMON TASKS:
- Review compose: Load skill, check docker-compose.yaml structure
- Troubleshoot: Load skill's troubleshooting.md, follow diagnostic workflow
- Add service: Load skill's compose.md, follow patterns
- Configure networking: Load skill's networking.md, select appropriate mode
- Set up persistence: Load skill's volumes.md, choose volume type
HOMELAB PATTERNS:
This repo uses:
- Profile-based compose files with .env templates
- Macvlan/ipvlan for services needing LAN presence
- Named volumes for data, bind mounts for config
- Ansible for deployment (not direct docker commands)
See: docker-compose/pihole/docker-compose.yaml for example.
CHANGELOG:
2.0.0 (2025-11-27)
- Refactored to use docker skill for reference material
- Agent now focuses on reasoning and decisions
- Removed duplicate reference content (now in skill)
- Added skill loading to PROCESS
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.
- 2d ago First seen · 141 lines · 16 tokens per session scan A 35895e01174d
docker-compose-expert is an agent published in the GitHub repository poindexter12/waypoint (7 stars, last pushed 7mo ago), licensed MIT. It adds 16 tokens to every session and 1,135 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.
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