skills/imbue-ai/vet/SKILL.md
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.
npx skillsauth add aiskillstore/marketplace vetInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
Install vet using pip or uv:
# Using pip
pip install verify-everything
# Using uv (recommended)
uv pip install verify-everything
# Verify installation:
vet --help
OpenCode:
vet "goal" --history-loader "python ~/.agents/skills/vet/scripts/export_opencode_session.py --session-id <ses_ID>"
Codex:
vet "goal" --history-loader "python ~/.codex/skills/vet/scripts/export_codex_session.py --session-file <path-to-session.jsonl>"
Claude Code:
vet "goal" --history-loader "python ~/.claude/skills/vet/scripts/export_claude_code_session.py --session-file <path-to-session.jsonl>"
Without Conversation History
vet "goal"
OpenCode: The --session-id argument requires a ses_... session ID. To find the current session ID, search for the first user message from this conversation in the part files:
grep -rl "UNIQUE_MESSAGE" ~/.local/share/opencode/storage/part/ to find the matching part file.
sessionID field from that part JSON file.--session-id.Codex: Session files are stored in ~/.codex/sessions/YYYY/MM/DD/. Find the correct conversation using the approach described above for opencode that uses textual search.
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). Find the correct conversation using the approach described above for opencode that uses textual search.
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.
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.
--base-commit REF: Git ref for diff base (default: HEAD)--model MODEL: LLM model to use (default: claude-opus-4-6)--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. Slower (~3 min) so not recommended as the default.--help: Show comprehensive list of optionsdevelopment
Apple Human Interface Guidelines for content display components. Use this skill when the user asks about charts component, collection view, image view, web view, color well, image well, activity view, lockup, data visualization, content display, displaying images, rendering web content, color pickers, or presenting collections of items in Apple apps. Also use when the user says how should I display charts, what's the best way to show images, should I use a web view, how do I build a grid of items, what component shows media, or how do I present a share sheet. Cross-references: hig-foundations for color/typography/accessibility, hig-patterns for data visualization patterns, hig-components-layout for structural containers, hig-platforms for platform-specific component behavior.
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