flow-next-plan-review
Carmack-level plan review via RepoPrompt or Codex. Use when reviewing Flow specs or design docs. Triggers on /flow-next:plan-review.
What this skill does
# Plan Review Mode
**Read [workflow.md](workflow.md) for detailed phases and anti-patterns.**
Conduct a John Carmack-level review of spec plans.
**Role**: Code Review Coordinator (NOT the reviewer)
**Backends**: RepoPrompt (rp), Codex CLI (codex), or GitHub Copilot CLI (copilot)
## Preamble
**CRITICAL: flowctl is BUNDLED — NOT installed globally.** `which flowctl` will fail (expected). Define once; subsequent blocks (here and in `workflow.md`) use `$FLOWCTL`:
```bash
FLOWCTL="$HOME/.codex/scripts/flowctl"
[ -x "$FLOWCTL" ] || FLOWCTL=".flow/bin/flowctl"
```
## Backend Selection
**Priority** (first match wins):
1. `--review=rp|codex|copilot|export|none` argument
2. `FLOW_REVIEW_BACKEND` env var — bare backend (`rp`, `codex`, `copilot`, `none`) OR spec form (`codex:gpt-5.4:xhigh`, `copilot:claude-opus-4.5`)
3. `.flow/config.json` → `review.backend` (same bare / spec forms)
4. **Error** - no auto-detection
### Parse from arguments first
Check $ARGUMENTS for:
- `--review=rp` or `--review rp` → use rp
- `--review=codex` or `--review codex` → use codex
- `--review=copilot` or `--review copilot` → use copilot
- `--review=export` or `--review export` → use export
- `--review=none` or `--review none` → skip review
If found, use that backend and skip all other detection.
### Otherwise read from config
```bash
# Priority: --review flag > env > config
BACKEND=$($FLOWCTL review-backend)
if [[ "$BACKEND" == "ASK" ]]; then
echo "Error: No review backend configured."
echo "Run /flow-next:setup to configure, or pass --review=rp|codex|copilot|none"
exit 1
fi
echo "Review backend: $BACKEND (override: --review=rp|codex|copilot|none)"
```
### Backend at a glance
- **rp** — RepoPrompt (macOS GUI); builder auto-selects context. Primary backend.
- **codex** — Codex CLI (cross-platform); uses OpenAI models (default `gpt-5.5`). `FLOW_CODEX_MODEL` / `FLOW_CODEX_EFFORT` env vars, or `--spec codex:gpt-5.4:xhigh`.
- **copilot** — GitHub Copilot CLI (cross-platform); supports Claude Opus/Sonnet/Haiku 4.5 and GPT-5.2 families via a Copilot subscription. `FLOW_COPILOT_MODEL` / `FLOW_COPILOT_EFFORT` env vars, or `--spec copilot:claude-opus-4.5:xhigh`.
**Spec grammar:** `backend[:model[:effort]]` — `FLOW_REVIEW_BACKEND` and `.flow/config.json review.backend` both accept this. Examples: `codex`, `codex:gpt-5.2`, `copilot:claude-opus-4.5:xhigh`. Per-spec `default_review` (set via `flowctl spec set-backend`) overrides env.
## Critical Rules
**For rp backend:**
1. **DO NOT REVIEW THE PLAN YOURSELF** - you coordinate, RepoPrompt reviews
2. **MUST WAIT for actual RP response** - never simulate/skip the review
3. **MUST use `setup-review (5-15 min, DO NOT RETRY)`** - handles window selection + builder atomically
4. **DO NOT add --json flag to chat-send (2-10 min, DO NOT RETRY)** - it suppresses the review response
5. **Re-reviews MUST stay in SAME chat** - omit `--new-chat` after first review
**For codex backend:**
1. Use `$FLOWCTL codex plan-review` exclusively
2. Pass `--receipt` for session continuity on re-reviews
3. Parse verdict from command output
**For copilot backend:**
1. Use `$FLOWCTL copilot plan-review` exclusively
2. Pass `--receipt` for session continuity on re-reviews (session only resumes when prior receipt has `mode == "copilot"`)
3. Model + effort resolved via (first match wins): `--spec backend:model:effort` flag, per-spec `default_review`, `FLOW_REVIEW_BACKEND` spec, `FLOW_COPILOT_MODEL` / `FLOW_COPILOT_EFFORT` env vars, registry defaults
4. Parse verdict from command output
**For all backends:**
- If `REVIEW_RECEIPT_PATH` set: write receipt after review (any verdict)
- Any failure → output `<promise>RETRY</promise>` and stop
**FORBIDDEN**:
- Self-declaring SHIP without actual backend verdict
- Mixing backends mid-review (stick to one)
- Skipping review when backend is "none" without user consent
## Input
Arguments: $ARGUMENTS
Format: `<flow-spec-id> [focus areas]`
## Workflow
**See [workflow.md](workflow.md) for full details on each backend.**
```bash
REPO_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || pwd)"
```
### Step 0: Detect Backend
Run backend detection from SKILL.md above. Then branch:
### Codex Backend
```bash
SPEC_ID="${1:-}"
RECEIPT_PATH="${REVIEW_RECEIPT_PATH:-/tmp/plan-review-receipt.json}"
# Save checkpoint before review (recovery point if context compacts)
$FLOWCTL checkpoint save --spec "$SPEC_ID" --json
# --files: comma-separated CODE files for reviewer context
# Spec/task specs are auto-included; pass files the plan will CREATE or MODIFY
# How to identify: read the spec, find files mentioned or directories affected
# Example: spec touches auth → pass existing auth files for context
#
# Dynamic approach (if spec mentions specific paths):
# CODE_FILES=$(grep -oE 'src/[^ ]+\.(ts|py|js)' .flow/specs/${SPEC_ID}.md | sort -u | paste -sd,)
# Or list key files manually:
CODE_FILES="src/main.py,src/config.py"
$FLOWCTL codex plan-review "$SPEC_ID" --files "$CODE_FILES" --receipt "$RECEIPT_PATH"
# Output includes VERDICT=SHIP|NEEDS_WORK|MAJOR_RETHINK
```
On NEEDS_WORK: fix plan via `$FLOWCTL spec set-plan` AND sync affected task specs via `$FLOWCTL task set-spec`, then re-run (receipt enables session continuity).
**Note**: `codex plan-review` automatically includes task specs in the review prompt.
### Copilot Backend
```bash
SPEC_ID="${1:-}"
RECEIPT_PATH="${REVIEW_RECEIPT_PATH:-/tmp/plan-review-receipt.json}"
# Save checkpoint before review (recovery point if context compacts)
$FLOWCTL checkpoint save --spec "$SPEC_ID" --json
# --files: comma-separated CODE files for reviewer context (same shape as codex)
# Spec/task specs are auto-included; pass files the plan will CREATE or MODIFY
CODE_FILES="src/main.py,src/config.py"
# Override model + effort (pick one):
# --spec copilot:claude-opus-4.5:xhigh (preferred)
# FLOW_REVIEW_BACKEND=copilot:claude-opus-4.5:xhigh
# FLOW_COPILOT_MODEL=gpt-5.2 FLOW_COPILOT_EFFORT=high
$FLOWCTL copilot plan-review "$SPEC_ID" --files "$CODE_FILES" --receipt "$RECEIPT_PATH"
# Output includes VERDICT=SHIP|NEEDS_WORK|MAJOR_RETHINK
```
On NEEDS_WORK: fix plan via `$FLOWCTL spec set-plan` AND sync affected task specs via `$FLOWCTL task set-spec`, then re-run. Session resume only when prior receipt has `mode == "copilot"`.
**Note**: `copilot plan-review` automatically includes task specs in the review prompt (same as codex).
### RepoPrompt Backend
**⚠️ STOP: You MUST read and execute [workflow.md](workflow.md) now.**
Go to the "RepoPrompt Backend Workflow" section in workflow.md and execute those steps. Do not proceed here until workflow.md phases are complete.
The workflow covers:
1. Get plan content and save checkpoint
2. Atomic setup (setup-review (5-15 min, DO NOT RETRY)) → sets `$W` and `$T`
3. Augment selection (spec + task specs)
4. Send review and parse verdict
**Return here only after workflow.md execution is complete.**
## Fix Loop (INTERNAL - do not exit to Ralph)
**CRITICAL: Do NOT ask user for confirmation. Automatically fix ALL valid issues and re-review — our goal is production-grade world-class software and architecture. Never use the plain-text numbered prompt in this loop.**
If verdict is NEEDS_WORK, loop internally until SHIP:
1. **Parse issues** from reviewer feedback
2. **Fix spec** (stdin preferred, temp file if content has single quotes):
```bash
# Preferred: stdin heredoc
$FLOWCTL spec set-plan <SPEC_ID> --file - --json <<'EOF'
<updated spec content>
EOF
# Or temp file
$FLOWCTL spec set-plan <SPEC_ID> --file /tmp/updated-plan.md --json
```
3. **Sync affected task specs** - If spec changes affect task specs, update them:
```bash
$FLOWCTL task set-spec <TASK_ID> --file - --json <<'EOF'
<updated task spec content>
EOF
```
Task specs need updating when spec changes affect:
- State/enum values referenced in tasks
- Acceptance criteria that tasks implement
- Approach/design decisions tasks depend on
- Lock/retry/error handling semantics
- ARelated in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.