Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.
npx skills add https://github.com/arbiterForge/codeArbiter --skill ca-preview
See what codeArbiter would do to your real code before paying any onboarding cost. This is a
read-only dry-run against the current uncommitted diff: it predicts which reviewers the change
would dispatch, runs the checks that need no project rules, and reports. It never writes state.
It requires no $ca-init, no .codearbiter/ directory, and no decompose or create-context
interview. It functions in a repo that never opted in, and it modifies nothing: not the worktree,
not the index, not .codearbiter/. git status is unchanged by a run.
preview.py in diff mode, which wrapscollect_diff from ${CLAUDE_PLUGIN_ROOT}/hooks/_previewlib.py. It unions HEAD-vs-worktree
changes, staged changes, and untracked files (forward-slash paths). Run it from the project
root so _previewlib/_hooklib resolve on the same sys.path:
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/preview.py" diff || python "${CLAUDE_PLUGIN_ROOT}/hooks/preview.py" diff
If the result is empty (clean tree, or not a git repo), print a friendly **"Nothing to
preview"** line and STOP. This is a clean exit, not an error: no stack trace, no failure.
${CLAUDE_PLUGIN_ROOT}/includes/review-matrix.md. That include is the single source of truth
for which reviewer is dispatched when scope touches a given path: do NOT restate, fork, or
inline a second copy of the table here. For each changed path, list the reviewers that WOULD
dispatch and name the triggering path for each. This is the same mapping $ca-review uses, so
the predicted set matches what a real review would dispatch.
preview.py in secrets mode,which wraps scan_secrets from ${CLAUDE_PLUGIN_ROOT}/hooks/_previewlib.py. It reads each
changed file's current content and returns SecretFinding(path, line_no, snippet) for every
credential line, with the secret VALUE already masked to in snippet:
python3 "${CLAUDE_PLUGIN_ROOT}/hooks/preview.py" secrets || python "${CLAUDE_PLUGIN_ROOT}/hooks/preview.py" secrets
Report each finding by path:line_no with its redacted snippet. The snippet arrives already
masked: never reconstruct or print a raw secret value.
Emit one clear report with these parts:
staged, untracked).
for each. These are predicted (would-dispatch), not run here.
path:line_no with theredacted snippet, marked as found (ran locally), at BLOCK severity. State "none found" when the
scan is clean.
$ca-init then$ca-review.
This reports reviewer and gate behavior on the current diff. It makes NO hook-probe claims and says
nothing about whether the install's hooks fire: that is $ca-doctor. Do not blend the two.
$ca-init then $ca-review.$ca-doctor.$ca-btw..codearbiter/;MUST NOT stage or commit. git status MUST be unchanged after a run.
$ca-init, .codearbiter/ state, or thedecompose / create-context interview.
carries only that masked form.
exit, never a stack trace.
(ran locally): it MUST NOT attribute fabricated findings to any predicted reviewer.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take arbiterforge/ca-preview from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.