AlphaMoatによると、2026-09時点でvetのダウンロード数は4,363、スター数は2で、AIスキル全体5,078件中2,242位、開発では577件中281位です。
| プラットフォーム | インストール数 | ダウンロード数 | スター数 | コメント |
|---|---|---|---|---|
| ClawHub ↗ | 144 | 4202 | 2 | - |
| SkillHub ↗ | 266 | 4363 | 2 | — |
プラットフォームごとに集計方法と集計時点が異なります。
vet は git diff と会話履歴をレビューし、コード変更や会話の中の問題(要求と実装のズレなど)を見つけます。頻繁に実行するほど効果的:論理的な変更単位の直後に必ず実行し、変更をまとめず、頼まれるのを待たないこと。pip install verify-everything(または pipx/uv)でインストール。vet "goal" 単体でも実行でき、--history-loader で OpenCode、Codex、Claude Code のセッション履歴を添付できます(見つけたセッションが現在の会話と一致するか必ず確認)。主なオプション:--base-commit(デフォルト HEAD)、--model、--confidence-threshold(デフォルト 0.8)、--output-format text/json/github、--agentic(ローカルの Claude Code/Codex CLI 経由で分析。遅いが精度は高い傾向)。注意:vet は base コミットからの差分全体を分析するため、他のエージェントの変更が含まれることがあり、本セッション外の指摘は無視してください。vet はテスト実行の代わりにはなりません。
資料公開日 2026-10-27
--history-loader でコーディングセッション履歴を添付し要求と実装のズレを検出--base-commit、--confidence-threshold などで範囲としきい値を調整--agentic モードでローカル Claude Code/Codex CLI 経由の高精度分析スキルのドキュメントをもとに生成した例であり、実際の実行結果ではありません。
2026-09 から集計方法を変更し、同名スキルを作者ごとに分けて集計し、全スキルを対象にしました。破線は変更前の月で、変更後のデータとは直接比較せず、変更をまたぐ増減も計算していません。
| 月 | ダウンロード数 | 前月比 | スター数 |
|---|---|---|---|
| 2026-09 | 4363 | — | 2 |
| 2026-08 | 4122 | +1.7% | 2 |
| 2026-07 | 4052 | +5.4% | 2 |
| 2026-06 | 3843 | +3.0% | 2 |
| 2026-05 | 3732 | — | 2 |
| 2026-03 | 3298 | — | 2 |
作者が公開した元のファイルをテキストのまま表示しています。AlphaMoat による編集や審査はしていません。リンクはクリックできません。コマンドは内容を確認してから実行してください。取得日 2026-10-23。
--- name: vet description: Run vet immediately after ANY logical unit of code changes. Do not batch your changes, do not wait to be asked to run vet, make sure you are proactive. --- # Vet **Run vet immediately after ANY logical unit of code changes. Do not batch changes, do not wait to be asked to run vet, make sure you are proactive.** Vet reviews git diffs and conversation history to find issues in code changes and conversation history. It is most effective when run frequently with conversation history, which helps it catch misunderstandings between what was requested and what was implemented. Despite this, vet is not a replacement for running tests.
## Installation
Install vet using pip, pipx, or uv:
```bash
# Using pip
pip install verify-everything
# Using pipx
pipx install verify-everything
# Using uv
uv tool install verify-everything
# Verify installation:
vet --help
```
## Running Vet
### Standard Usage
Before running vet, determine the correct Python binary:
```bash
$(command -v python3 || command -v python)
```
Use whichever resolves (prefer `python3`). The examples below use `python3`, substitute `python` if that is what your system provides.
**OpenCode:**
```bash
vet "goal" --history-loader "python3 ~/.agents/skills/vet/scripts/export_opencode_session.py --session-id <ses_ID>"
```
**Codex:**
```bash
vet "goal" --history-loader "python3 ~/.codex/skills/vet/scripts/export_codex_session.py --session-file <path-to-session.jsonl>"
```
**Claude Code:**
```bash
vet "goal" --history-loader "python3 ~/.claude/skills/vet/scripts/export_claude_code_session.py --session-file <path-to-session.jsonl>"
```
**Without Conversation History**
```bash
vet "goal"
```
### Finding Your Session
You should only search for sessions from your coding harness. If a user requests you use a different harness, they are likely referring to vet's agentic mode, not the session.
**OpenCode:** The `--session-id` argument requires a `ses_...` session ID. To find the current session ID:
1. Run: `opencode session list --format json` to list recent sessions with their IDs and titles.
2. Identify the current session from the list by matching the title or timestamp.
- IMPORTANT: Verify the session you found matches the current conversation. If the title is ambiguous, compare timestamps or check multiple candidates.
3. Pass the session ID as `--session-id`.
**Codex:** Session files are stored in `~/.codex/sessions/YYYY/MM/DD/`. To find the correct session file:
1. Find the most unique sentence / question / string in the current conversation.
2. Search for your unique message string in ~/.codex/sessions/` to find the matching session file.
- IMPORTANT: Verify the conversation you found matches the current conversation and that it is not another conversation with the same search string.
3. Pass the matched file path as `--session-file`.
**Claude Code:** Session files are stored in `~/.claude/projects/<encoded-path>/`. The encoded path replaces `/` with `-` (e.g. `/home/user/myproject` becomes `-home-user-myproject`). To find the correct session file:
1. Find the most unique sentence / question / string in the current conversation.
2. Search for your unique message string in ~/.claude/projects/` to find the matching session file.
- IMPORTANT: Verify the conversation you found matches the current conversation and that it is not another conversation with the same search string.
3. Pass the matched file path as `--session-file`.
NOTE: The examples in the standard usage section assume the user installed the vet skill at the user level, not the project level. Prior to trying to run vet, check if it was installed at the project level which should take precedence over the user level. If it is installed at the project level, ensure the history-loader option points to the correct location.
## Interpreting Results
Vet analyzes the full git diff from the base commit. This may include changes from other agents or sessions working in the same repository. If vet reports issues that relate to changes you did not make in this session, disregard them, assuming they belong to another agent or the user.
## Common Options
- `--base-commit REF`: Git ref for diff base (default: HEAD)
- `--model MODEL`: LLM to use (default: claude-opus-4-6)
- `--list-models`: list all models that are supported by vet
- Run `vet --help` and look at the vet repo's readme for details about defining custom OpenAI-compatible models.
- `--confidence-threshold N`: Minimum confidence 0.0-1.0 (default: 0.8)
- `--output-format FORMAT`: Output as `text`, `json`, or `github`
- `--quiet`: Suppress status messages and 'No issues found.'
- `--agentic`: Mode that routes analysis through the locally installed Claude Code or Codex CLI instead of calling the API directly. Try this if vet fails due to missing API keys. This is slower so it is not the default, but it often results in higher precision issue identification. `--model` is forwarded to the harness but not validated by vet, as vet doesn't know which models each harness supports.
- `--agent-harness`: The two options for this are `codex` and `claude`. Claude Code is the default.
- `--help`: Show comprehensive list of options
## Updating
The vet CLI, skill files, and export scripts can become outdated as agent harnesses and LLM APIs change.
If this happens, try updating them. Run `which vet` to determine how vet was installed and update accordingly. For the skill files, check which skill directories exist on disk and update them with the latest versions from https://github.com/imbue-ai/vet/tree/main/skills/vet.
## Additional Information
Additional information can be found in the vet repo:
https://github.com/imbue-ai/vet
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データ月:2026-09 · ダウンロード数、スター数、インストール数は公開スキルレジストリ(ClawHub、SkillHub)から月単位で集計しています。詳しくはデータの方法論をご覧ください。