From lrc
Review staged changes in the current repository with the canonical lrc backend. Also use for natural-language requests like "review with lrc", "run lrc review", "review this", "do a code review", or "start a review" when the user intends a LiveReview-backed review flow.
How this skill is triggered — by the user, by Claude, or both
Slash command
/lrc:review [--blocking][--blocking]This skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Execution policy (strict):
Execution policy (strict):
Messaging calibration (strict):
lrc review --staged commits or pushes, treat that as normal successful behavior.Always ensure the backend is present and review-ready before running review commands.
On Windows use the PowerShell tool:
& "${CLAUDE_SKILL_DIR}/../../scripts/ensure-lrc.ps1" -ForReview
On Unix/macOS use the Bash tool:
bash "${CLAUDE_SKILL_DIR}/../../scripts/ensure-lrc.sh" --for-review
If the command above fails because setup is incomplete:
lrc internal claude setup start
lrc internal claude setup submit-key --key "$USER_MESSAGE"
Then run the mapped review command for this request (lrc review --staged, lrc review --staged --blocking-review, or lrc review --commit HEAD).
If the second ensure step still reports setup required immediately after a successful submit-key, do not run exploratory diagnostics. Proceed directly to the mapped lrc review command once.
Do not run exploratory diagnostics (lrc status, ls, cat, etc.) unless one of the two commands above fails.
Do not prefix canonical commands with source ~/.lrc/env &&.
Do not inspect ~/.lrc.toml with Read/file tools to decide readiness. Use only the canonical ensure script and lrc setup flow.
Then map the user request to the canonical command:
lrc review --stagedlrc review --staged --blocking-reviewlrc review --commit HEADDo not use skip or vouch from this skill unless the user explicitly changes intent.
npx claudepluginhub hexmostech/claude-lrc --plugin lrcGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.