Review an implementation plan before coding across architecture, code quality, tests, and performance. Compare concrete options for each issue, explain effort and risks, and choose a direction through an interactive review.
Structured plan review across 4 axes before writing any code (inspired by Garry Tan's workflow)
Review the instructions the agent will receive before you install.
Review the current plan thoroughly before making any code changes. For every issue or recommendation, explain the concrete tradeoffs, give an opinionated recommendation, and ask for user input before assuming a direction.
Use these to guide your recommendations (override with project-specific CLAUDE.md preferences if they exist):
Work through each section sequentially. After each section, pause and ask for feedback before moving on.
Evaluate:
Evaluate:
Evaluate:
Evaluate:
For every specific issue found (bug, smell, design concern, or risk):
Ask if the user wants one of two options:
.claude/rules/ files for project-specific review criteria$ARGUMENTS
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Evaluate Claude Code agents, skills, and commands with weighted quality criteria. Get scores, readiness grades, template comparisons, and practical improvement suggestions in Markdown or JSON reports to guide reviews before release.
Assess a codebase across seven areas, including exposed credentials, security, dependencies, structure, and tests. Receive category scores, findings tied to file locations, and a prioritized improvement plan with smaller tasks that can be completed quickly.
Measure code patterns such as casts to any or disabled lint rules, then run repeated, targeted edits. Keep changes that improve the chosen metric, revert unsuccessful changes, and track results for each improvement loop.
Generate several separate solutions, compare them against criteria fixed in advance, and verify the selected result through executable checks or an independent reviewer. Keep a proof log documenting candidates, evidence, failures, and remaining limits.
Monitor a live application after deployment and compare it with a saved baseline, a record of its earlier state. Check page responses, loading times, and new errors, flag persistent changes, and produce a per-page health report.
Rebuild project context after clearing a conversation or returning to work. Review recent Git history, uncommitted changes, and TODO markers to get a structured summary of project status and suggested next steps.