docker-container-rerun-all

Sequentially check and optionally update all docker run containers that already have fixed recreate commands recorded in long-term memory. Use when the user wants a batch refresh of remembered docker-run-managed containers, wants dynamic discovery from MEMORY.md instead of a hardcoded list, and wants the results grouped into updated, already up-to-date, and failed containers with image tag and image Id change details.

Batch-check remembered docker run containers conservatively.

Use this skill to discover every container that already has a fixed recreate command recorded in long-term memory, then process them one by one with the same image-Id comparison workflow used by docker-container-rerun.

Preconditions

Use this skill only when all of the following are true:

1. The target containers were originally created with docker run, not docker compose.
2. Each target container already has a full fixed recreate command recorded in MEMORY.md.
3. The sibling skill docker-container-rerun is installed and available locally.
4. The current machine can run Docker commands against the target Docker daemon.
5. The user understands that --apply may stop, remove, and recreate containers when image Ids changed.

Do not use this skill when recreate commands are missing, incomplete, reconstructed from memory, or only partially known.

Dependencies

This skill has two explicit dependencies:

• sibling skill: docker-container-rerun
• long-term memory file: MEMORY.md

Required sibling skill

This skill calls the bundled script from the sibling skill directory:

• ../docker-container-rerun/scripts/update_docker_run_container.py

If docker-container-rerun is missing or broken, fix that first before using this skill.

Required MEMORY.md structure

This skill parses container recreate commands from the section header below inside MEMORY.md:

md

## 已记住的 Docker 容器固定重建命令

Under that section, each remembered container entry should include:

1. a list item whose bold label contains the container name in backticks
2. descriptive text mentioning docker run
3. a fenced bash code block containing the exact recreate command

Example entry using autoheal:

md

## 已记住的 Docker 容器固定重建命令

- **`autoheal`**：固定 docker run 重建命令
```bash
docker run -d \
  --name autoheal \
  --restart unless-stopped \
  -e AUTOHEAL_CONTAINER_LABEL=all \
  -e AUTOHEAL_INTERVAL=30 \
  -e AUTOHEAL_START_PERIOD=300 \
  -e CURL_TIMEOUT=30 \
  -v /var/run/docker.sock:/var/run/docker.sock \
  willfarrell/autoheal:latest

text

Keep the recreate command exact. Do not rewrite it from `docker inspect`, and do not omit flags that matter.

## Apply Modes

This skill supports two modes:

### Non-apply mode (default)

Command:

```bash
python3 scripts/run_all_docker_reruns.py

Behavior:

• reads MEMORY.md
• discovers remembered containers dynamically
• pulls the latest image for each remembered container
• compares current image Id vs latest image Id
• reports which containers need recreation
• does not stop, remove, or recreate any container

Use this mode when the user wants a safe inspection pass first.

Apply mode

Command:

bash

python3 scripts/run_all_docker_reruns.py --apply

Behavior:

• performs the same checks as non-apply mode
• for containers whose image Id changed, runs the sibling docker-container-rerun apply workflow
• may stop, remove, and recreate matching containers sequentially
• leaves already up-to-date containers unchanged

Use this mode only when the user explicitly wants real container recreation.

Workflow

1. Read MEMORY.md and locate the section that stores fixed recreate commands for remembered docker run containers.
2. Build the working container list dynamically from memory.
   • Do not hardcode container names in the skill logic.
   • If the user adds more remembered recreate commands later, include them automatically.
3. For each discovered container, preserve the exact remembered docker run command.
4. Process containers sequentially, never in parallel.
5. Use the bundled script to run the same check/apply workflow as docker-container-rerun for each container.
6. Report results in three groups with polished Chinese wording:
   • 已更新
   • 已是最新
   • 执行失败
7. For every updated container, include:
   • container name
   • image reference
   • image tag
   • previous image Id
   • latest image Id
   • version hint when the image tag contains a meaningful version string
8. Prefer a Telegram-friendly Chinese summary instead of dumping raw JSON directly to the user.

Safety Rules

• Treat MEMORY.md as the source of truth for the container list and fixed recreate commands.
• Do not reconstruct missing flags from docker inspect.
• Do not silently edit remembered docker run commands.
• Run containers one by one in sequence.
• If memory parsing fails for a container, put it in the failed group and continue with the next one.
• If the user asked only to create the skill, do not execute updates.
• When actual recreation is requested later, use --apply explicitly.

Bundled Script

Use the bundled script for deterministic batch execution from the skill directory:

bash

python3 scripts/run_all_docker_reruns.py

Add --apply only when the user explicitly wants to recreate containers that need updates:

bash

python3 scripts/run_all_docker_reruns.py --apply

The script will:

• parse remembered containers from MEMORY.md
• discover the current container set dynamically
• call the bundled docker-container-rerun script once per container
• keep execution sequential
• emit JSON with discovered containers, raw per-container results, and grouped summary

Output Format

Prefer a compact Chinese grouped report for chat surfaces.

Recommended Chinese Template

Use a detailed Chinese report by default. Append a final 重点异常提示 section that highlights failed containers, non-running containers, and health states like starting or unhealthy.

text

Docker 容器批量检查结果

本次共处理：<total> 个容器
- 已更新：<updated_count> 个
- 已是最新：<up_to_date_count> 个
- 执行失败：<failed_count> 个

【本次发现的容器】
1. <container_name> - <image>
2. <container_name> - <image>
...

【已更新】
1. <container_name>
   - 镜像：<image>
   - Tag：<tag>
   - Image Id：<old_id> → <new_id>
   - 版本提示：<version_hint_or_无>
   - 当前状态：<status>
   - 健康检查：<health_or_无>
   - 最近日志：<logs_tail_or_无>

【已是最新】
1. <container_name>
   - 镜像：<image>
   - Tag：<tag>
   - Image Id：<same_id>
   - 当前状态：<status>
   - 健康检查：<health_or_无>

【执行失败】
1. <container_name>
   - 原因：<error>

【重点异常提示】
1. <container_name>
   - 异常类型：<health_or_status_or_failure>
   - 说明：<short_reason>

Updated

For each updated container, report:

• container_name
• image
• tag
• current_image_id -> latest_image_id
• version_hint when available
• post-update container status and health if available

Already Up To Date

For each unchanged container, report:

• container_name
• image
• tag
• unchanged image Id

Failed

For each failure, report:

• container_name
• failure reason

Notes

• This skill intentionally depends on MEMORY.md instead of a hardcoded container list.
• This skill intentionally depends on the sibling docker-container-rerun skill for the single-container check/apply workflow.
• Relative paths are used so the skill remains portable after installation, as long as both skill directories keep their normal sibling layout.