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vet兽医

Agent Skill

vet 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

105,016

周安装

4,511

GitHub Stars

2

下载量

36,810
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:vet(兽医)
来源仓库:https://github.com/andrewlaack-collab/vet
安装命令:
openclaw skills install vet
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install vet

简介

在代码的任何逻辑单元发生更改后立即运行 vet。不要批量进行更改,不要等待被要求进行兽医检查,确保您积极主动。

SKILL.md

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:

# 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:

$(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:

vet "goal" --history-loader "python3 ~/.agents/skills/vet/scripts/export_opencode_session.py --session-id <ses_ID>"

Codex:

vet "goal" --history-loader "python3 ~/.codex/skills/vet/scripts/export_codex_session.py --session-file <path-to-session.jsonl>"

Claude Code:

vet "goal" --history-loader "python3 ~/.claude/skills/vet/scripts/export_claude_code_session.py --session-file <path-to-session.jsonl>"

Without Conversation History

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.

  1. 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.

  1. 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.

  1. 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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

95.99%
按下载量换算35,334

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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