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 skills/brain-bootstrap/claude-code-brain-bootstrap/dockernpx skills add brain-bootstrap/claude-code-brain-bootstrap --skill dockergit clone --depth 1 https://github.com/brain-bootstrap/claude-code-brain-bootstrapWhat 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 | $0.00462 |
| Opus 5 | $0.00013 | $0.00231 |
| Sonnet 5 | $0.00005 | $0.00092 |
| Haiku 4.5 | $0.00003 | $0.00046 |
Grade A, and why
docker 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.
What it actually says
Docker Skill
Run Docker operations in non-interactive mode.
Usage
/docker ps # List running containers
/docker logs service-name # Tail logs for a service
/docker build # Build the project image
/docker up # docker compose up -d
/docker down # docker compose down
/docker restart service # Restart a specific service
/docker prune # docker system prune -f (no named volumes)
/docker shell service # Open a shell in a running container
Instructions
Determine action from $ARGUMENTS:
| Argument | Action |
|---|---|
ps or (empty) |
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}" | cat |
logs <service> |
docker logs <service> --tail 50 | cat |
build |
Read claude/build.md for build command |
up |
docker compose up -d 2>&1 | tail -20 |
down |
docker compose down 2>&1 |
restart <service> |
docker compose restart <service> 2>&1 |
prune |
docker system prune -f 2>&1 (confirm first) |
shell <service> |
docker exec <container-id> /bin/sh (non-interactive: run a command) |
images |
docker images | cat |
stats |
docker stats --no-stream | cat |
⚠️ Rules:
- NEVER use
docker exec -it(interactive — hangs terminal) - For
shell: run a specific command instead:docker exec <id> /bin/sh -c "ls /app" - For
prune: warn about consequences before running - For
logs: always--tail Nto limit output - Read
claude/build.mdfor project-specific Docker compose file paths and service names
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 · 46 lines · 26 tokens per session scan A de654e81c3bc
docker is a skill published in the GitHub repository brain-bootstrap/claude-code-brain-bootstrap (11 stars, last pushed 4mo ago), licensed MIT. It adds 26 tokens to every session and 462 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 2026-08-30.
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implement
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review-spec
Use after implementing tasks or mid-feature to verify code matches design docs and ensure they are in sync. Detects spec deviations, missing implementations, doc inconsistencies, and outdated docs in design and implementation documentation.
chain-of-verification
Apply Chain-of-Verification (CoVe) prompting to improve response accuracy through self-verification. Use when complex questions require fact-checking, technical accuracy, or multi-step reasoning.
review-design
Review design, implementation, and task documents produced by design. Evaluates document quality, internal consistency, and technical soundness. Use after design completes and before starting implement.
review-code
Code review of current git changes with an expert senior-engineer lens. Detects SOLID violations, security risks, and proposes actionable improvements. Use when performing code reviews.
dependency-handling
TRIGGER when: adding or upgrading any dependency — library, SDK, framework, API, IaC API version (K8s/Terraform/Helm), CRD, or container image. Use BEFORE writing the call. Forces context7/capy lookup instead of guessing.