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/bug-ops/zeph/dockernpx skills add bug-ops/zeph --skill dockergit clone --depth 1 https://github.com/bug-ops/zephWhat 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 | $0.00097 | $0.02338 |
| Opus 5 | $0.00048 | $0.01169 |
| Sonnet 5 | $0.00019 | $0.00468 |
| Haiku 4.5 | $0.00010 | $0.00234 |
Grade A, and why
docker 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
--health-cmd="curl -f http://localhost/ || exit 1" \ How it starts
The opening of the file, as written. The whole thing — 487 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docker Operations
Container Lifecycle
List containers
# Running containers
docker ps
# All containers (including stopped)
docker ps -a
# Quiet mode (IDs only)
docker ps -q
# Filter by status
docker ps -f "status=exited"
# Custom format
docker ps --format "table {{.ID}}\t{{.Names}}\t{{.Status}}\t{{.Ports}}"
Create and run
# Run in foreground
docker run IMAGE
# Run detached with a name
docker run -d --name NAME IMAGE
# Run with port mapping (host:container)
docker run -d -p 8080:80 IMAGE
# Run with environment variables
docker run -d -e KEY=VALUE -e KEY2=VALUE2 IMAGE
# Run with env file
docker run -d --env-file .env IMAGE
# Run interactive shell
docker run -it IMAGE /bin/bash
# Run with auto-remove on exit
docker run --rm IMAGE
# Run with volume mount (bind mount)
docker run -d -v /host/path:/container/path IMAGE
# Run with named volume
docker run -d -v myvolume:/data IMAGE
# Run with read-only filesystem
docker run --read-only IMAGE
# Run with resource limits
docker run -d --memory=512m --cpus=1.5 IMAGE
# Run with restart policy
docker run -d --restart=unless-stopped IMAGE
# Run on a specific network
docker run -d --network=mynet IMAGE
# Run with health check
docker run -d \
--health-cmd="curl -f http://localhost/ || exit 1" \
--health-interval=30s \
--health-timeout=10s \
--health-retries=3 \
IMAGE
Stop, start, restart, remove
# Stop gracefully (SIGTERM, then SIGKILL after timeout)
docker stop CONTAINER
# Stop with custom timeout (seconds)
docker stop -t 30 CONTAINER
# Start a stopped container
docker start CONTAINER
# Restart
docker restart CONTAINER
# Kill immediately (SIGKILL)
docker kill CONTAINER
# Remove stopped container
docker rm CONTAINER
# Force remove running container
docker rm -f CONTAINER
# Remove all stopped containers
docker container prune -f
Execute commands in running containers
# Run command
docker exec CONTAINER COMMAND
# Interactive shell
docker exec -it CONTAINER /bin/bash
# Run as specific user
docker exec -u root CONTAINER COMMAND
# Set environment variable
docker exec -e VAR=value CONTAINER COMMAND
# Set working directory
docker exec -w /app CONTAINER COMMAND
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 · 487 lines · 97 tokens per session scan A b363d6ae3bae
docker is a skill published in the GitHub repository bug-ops/zeph (57 stars, last pushed 7d ago), licensed MIT. It adds 97 tokens to every session and 2,338 once invoked, about $0.0005 per session on Opus 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 2026-08-30.
Other skills, from other repositories
verify
Run Chimeraforge's canonical verification gate end-to-end and report the real output before claiming work done or committing. Failing output gets pasted, fixed, and re-run — never summarized away.
free-model-manager
Free AI model management - discover, download, and manage free/open-source AI models from Ollama, HuggingFace, and other sources.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
test
Detect the project’s test stack, run the narrowest useful tests, create tests when authorized, and report coverage/gaps honestly.
verify
Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.