Process code review findings interactively - fix or skip issues from monty-code-review output. Presents issues in severity order, applies fixes, runs quality checks, and updates review documents with status markers.
Processes code review findings interactively by presenting issues in severity order and applying fixes with quality checks.
/plugin marketplace add diversioteam/agent-skills-marketplace/plugin install process-code-review@diversiotechThis skill is limited to using the following tools:
/monty-code-review:code-review to generate a review document.*_review.md file with severity-tagged issues to process.This skill is the second step in the code review workflow:
Step 1: /monty-code-review:code-review → Creates *_review.md
Step 2: /process-code-review:process-review *_review.md → Fix/skip issues
Step 3: /backend-atomic-commit:pre-commit → Run pre-commit checks and fix issues
Before applying fixes, read local typing policy docs when present (for example
docs/python-typing-3.14-best-practices.md, TY_MIGRATION_GUIDE.md,
AGENTS.md) and align type-check behavior with those rules.
/process-code-review:process-review myfile_review.md - Interactive mode (default)/process-code-review:process-review --dry-run myfile_review.md - Preview only, no changes/process-code-review:process-review --auto myfile_review.md - Auto-fix all issues/process-code-review:process-review --auto --severity=NIT myfile_review.md - Auto-fix only NITs/process-code-review:process-review --severity=BLOCKING api_review.md - Process only BLOCKING issuesWhen this skill is active and you are asked to process a review document:
Read the review file and extract all issues. Look for:
[BLOCKING], [SHOULD_FIX], [NIT]Common patterns to look for:
### [BLOCKING] Issue Title
**Location:** path/to/file.py:L120-L145
**Current code:**
...
**Problem:**
...
**Proposed fix:**
...
Use TodoWrite to track all issues:
Example todo list structure:
[BLOCKING] C1. N+1 Query Pattern - pending
[BLOCKING] C2. Missing Org Scoping - pending
[SHOULD_FIX] S1. Performance Issue - pending
[NIT] N1. Docstring Missing - pending
For each issue, starting with highest severity, display:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[SEVERITY] Issue Title (N of M)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Location: file.py:L120-L145
Current Code:
<code snippet from review>
Problem:
<description of issue>
Proposed Fix:
<suggested code or approach>
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Then ask: Fix this issue or skip it?
Wait for user response before proceeding.
Read the source file to understand current state
Apply the proposed fix using Edit tool
Run quality checks on the modified file:
.bin/ruff check <file> --fix.bin/ruff format <file>Update the review document to mark the issue as FIXED:
### [BLOCKING] Issue Title
**Status:** ✅ FIXED (YYYY-MM-DD)
Update TodoWrite to mark as completed
Move to the next issue
Do NOT modify the source file
Ask for optional reason (or use "Deferred")
Update the review document to mark the issue as IGNORED:
### [BLOCKING] Issue Title
**Status:** ⏭️ IGNORED (YYYY-MM-DD)
**Reason:** [User's reason or "Deferred"]
Update TodoWrite to mark as completed (skipped)
Move to the next issue
After each fix, run quality checks:
ruff check <file> --fix - Auto-fix linting issuesruff format <file> - Format codety if configured; else pyright; else mypy) - Type checkpython manage.py check - Django system checks (if applicable)For touched files, "baseline acceptable" is not allowed. Resolve all active type-gate errors before moving on. If repo policy requires wider type checks before merge, run them before final completion.
If quality checks reveal additional issues, fix them before moving on.
When all issues are processed, provide a summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Review Processing Complete
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Total Issues: 13
✅ Fixed: 8
⏭️ Skipped: 3
📅 Deferred: 2
Files Modified:
- optimo_core/services/wellbeing_service.py
- optimo_core/schemas/wellbeing.py
Next Steps:
Run /backend-atomic-commit:pre-commit to run pre-commit checks and fix issues.
Review document remains uncommitted (working documentation).
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Use these markers when updating review documents:
| Status | Marker | Meaning |
|---|---|---|
| Open | (no marker) | Issue not yet addressed |
| Fixed | ✅ FIXED | Issue has been resolved in code |
| Ignored | ⏭️ IGNORED | Issue intentionally skipped |
| Won't Fix | 🚫 WON'T FIX | Issue acknowledged but will not be fixed |
| Deferred | 📅 DEFERRED | Issue to be addressed in future work |
Always include the date: **Status:** ✅ FIXED (2025-01-15)
Process issues in this order:
[BLOCKING] - Must fix before merge
[SHOULD_FIX] - Important but not blocking
[NIT] - Minor style/structure issues
Before marking a review as complete, verify:
.bin/ruff check --fix.bin/ruff formatParse arguments to adjust behavior:
| Flag | Description |
|---|---|
--dry-run | Show all issues and proposed fixes without modifying any files |
--auto | Apply all fixes without prompting (use with caution) |
--severity=<LEVEL> | Filter to only process issues of specified severity |
| (no flags) | Interactive mode - prompt for each issue (default) |
--severity=BLOCKING - Only process BLOCKING issues--severity=SHOULD_FIX - Only process SHOULD_FIX issues--severity=NIT - Only process NIT issues# Preview all issues without making changes
/process-code-review:process-review --dry-run api_review.md
# Auto-fix everything (careful!)
/process-code-review:process-review --auto api_review.md
# Auto-fix only minor issues, prompt for important ones
/process-code-review:process-review --auto --severity=NIT api_review.md
# Focus on critical issues only
/process-code-review:process-review --severity=BLOCKING api_review.md
# Dry-run to see only BLOCKING issues
/process-code-review:process-review --dry-run --severity=BLOCKING api_review.md
Flags can be combined:
--dry-run --severity=BLOCKING: Preview only BLOCKING issues--auto --severity=NIT: Auto-fix only NITs (safe for minor style fixes)/backend-atomic-commit:pre-commit to run pre-commit checks on staged changesThis skill integrates with:
The three-step workflow ensures:
Use this mode only when the user explicitly asks to post processed findings to GitHub PR comments.
MUST_01: use one authoritative top-level review summary.MUST_02: avoid redundant inline comments (one anchor per root-cause cluster).MUST_03: run pre/post dedupe audit against both endpoints:
/pulls/{pr}/comments/issues/{pr}/commentsMUST_04: keep diagrams/ascii blocks fenced in markdown.MUST_05: if line anchor fails with 422, fallback to file-level inline comment.SHOULD_01: default inline comment cap is 5 unless user requests more.SHOULD_02: prefer editing existing submitted review in place for formatting fixes.SHOULD_03: do not post extra PR-level chatter comments.STEP_01: pre-audit existing reviews and comments by current user.STEP_02: map findings to non-overlapping anchor set.STEP_03: post review/comments once.STEP_04: run duplicate detector and delete redundant comments if any.Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.