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From autoreview
Use when the user asks a free-text question about a convention without a concrete file path ("how do I write a command handler here?", "what's the logging policy?"). The agent needs knowledge retrieval, not a review verdict. Skip when a file path is already known (use autoreview:context); skip when the user actually wants a pass/fail verdict on existing code (use autoreview:review); skip when no `.autoreview/` exists — use autoreview:setup first.
How this skill is triggered — by the user, by Claude, or both
Slash command
/autoreview:guideThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> **Cross-platform.** Snippets below use bash-style env-var syntax (`${CLAUDE_PLUGIN_ROOT}`). Claude Code's Bash tool runs Git Bash on Windows so these work as-is; on native PowerShell substitute `$env:CLAUDE_PLUGIN_ROOT`, on cmd use `%CLAUDE_PLUGIN_ROOT%`. Plugin requires Node ≥22 — only assumed binary.
Cross-platform. Snippets below use bash-style env-var syntax (
${CLAUDE_PLUGIN_ROOT}). Claude Code's Bash tool runs Git Bash on Windows so these work as-is; on native PowerShell substitute$env:CLAUDE_PLUGIN_ROOT, on cmd use%CLAUDE_PLUGIN_ROOT%. Plugin requires Node ≥22 — only assumed binary.
Token-based search over rule name / description / body. Returns up to 5 ranked rules with their read: paths. Zero LLM cost.
node ${CLAUDE_PLUGIN_ROOT}/scripts/bin/guide.mjs '<free-text query>'
Output: top 5 matching rules with a one-line "why relevant" plus read: paths. Read them, then answer the user's question citing the rule ids.
Rules are listed using effective frontmatter (post-overlay) — remote rule overrides from remote_rules[].overrides are already merged in. What you see is what the reviewer enforces.
For a known file path, use autoreview:context instead — it filters by trigger (more precise than text similarity).
If output is "no relevant rules found", invoke autoreview:create-rule to author one.
npx claudepluginhub krzysztofdudek/autoreview --plugin autoreviewProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.