據 AlphaMoat 統計,截至 2026-09,vet 累計下載 4,363 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,242 位,在「開發程式設計」分類(577 個)中排名第 281 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 144 | 4202 | 2 | - |
| SkillHub ↗ | 266 | 4363 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
vet 審查 git diff 和對話歷史來發現程式碼改動與會話中的問題(例如實現與需求之間的誤解),適合頻繁執行——每完成一段邏輯改動就立即跑一次,不要攢批、不要等被要求。透過 pip install verify-everything(或 pipx/uv)安裝。可單獨執行 vet "goal",也可透過 --history-loader 附帶 OpenCode、Codex 或 Claude Code 的會話歷史(注意先核對找到的會話確為當前對話)。常用選項:--base-commit(預設 HEAD)、--model、--confidence-threshold(預設 0.8)、--output-format text/json/github、--agentic(經本地 CLI 分析,較慢但精度常更高)。注意:vet 分析的是自 base commit 起的完整 diff,可能包含其他 agent 的改動,不屬於本會話的告警應忽略;vet 不能替代執行測試。
資料釋出於 2026-10-27
--history-loader 附帶編碼會話歷史以捕捉需求與實現的偏差--base-commit、--confidence-threshold 等選項調整審查範圍與門檻--agentic 模式經本地 Claude Code/Codex CLI 做更高精度分析以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 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 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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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資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。