Pro Workflow

Complete AI coding workflow system from production use. Orchestration patterns, reference guides, and battle-tested habits that compound over time.

Works with: Claude Code, Cursor, Codex, Gemini CLI, and 32+ AI coding agents via SkillKit. Sections marked (Claude Code) use features specific to Claude Code — Cursor users can skip those or use the noted alternatives.

The Core Insight

"80% of my code is written by AI, 20% is spent reviewing and correcting it." — Karpathy

This skill optimizes for that ratio. Every pattern here reduces correction cycles.

1. The Self-Correction Loop

The single most powerful pattern. Your CLAUDE.md trains itself through corrections.

How It Works

When you correct Claude:

1. Claude acknowledges the mistake
2. Proposes a rule to prevent it
3. You approve → rule goes into memory
4. Future sessions avoid the same mistake

Add to CLAUDE.md

## Self-Correction Protocol

When the user corrects me or I make a mistake:
1. Acknowledge specifically what went wrong
2. Propose a concise rule: `[LEARN] Category: One-line rule`
3. Wait for approval before adding to LEARNED section

### LEARNED
<!-- Auto-populated through corrections -->

Trigger Phrases

• "Add that to your rules"
• "Remember this"
• "Don't do that again"

Example Flow

User: You edited the wrong file
Claude: I edited src/utils.ts when you meant src/lib/utils.ts.

[LEARN] Navigation: Confirm full path before editing files with common names.

Should I add this?

1b. Pre-Flight Discipline

Self-correction catches mistakes after the fact. This catches them before.

Karpathy's observations on LLM coding pitfalls name the upstream failures: silent assumptions, overcomplicated diffs, drive-by edits, vague success criteria. Four rules prevent each one.

Full rules in

rules/pre-flight-discipline.mdc

alwaysApply: true

Add to CLAUDE.md

## Pre-Flight Discipline
Before coding: state assumptions, present ambiguity, push back if simpler exists.
Every changed line traces to the request - no drive-by edits.
Convert imperatives to verifiable goals: "fix bug" → "failing test → make it pass".

2. Parallel Sessions with Worktrees

Zero dead time. While one Claude thinks, work on something else.

Setup

Claude Code:

claude --worktree    # or claude -w (auto-creates isolated worktree)

Cursor / Any editor:

git worktree add ../project-feat feature-branch
git worktree add ../project-fix bugfix-branch

Background Agent Management (Claude Code)

• Ctrl+F

  — Kill all background agents (two-press confirmation)

• Ctrl+B

  — Send task to background
• Subagents support

  isolation: worktree

  in agent frontmatter

When to Parallelize

Add to CLAUDE.md

## Parallel Work
When blocked on long operations, use `claude -w` for instant parallel sessions.
Subagents with `isolation: worktree` get their own safe working copy.

3. The Wrap-Up Ritual

End sessions with intention. Capture learnings, verify state.

/wrap-up Checklist

1. Changes Audit - List modified files, uncommitted changes
2. State Check - Run

   git status

   , tests, lint
3. Learning Capture - What mistakes? What worked?
4. Next Session - What's next? Any blockers?
5. Summary - One paragraph of what was accomplished

Create Command

~/.claude/commands/wrap-up.md

Execute wrap-up checklist:
1. `git status` - uncommitted changes?
2. `npm test -- --changed` - tests passing?
3. What was learned this session?
4. Propose LEARNED additions
5. One-paragraph summary

4. Split Memory Architecture

For complex projects, modularize Claude memory.

Structure

.claude/
├── CLAUDE.md        # Entry point
├── AGENTS.md        # Workflow rules
├── SOUL.md          # Style preferences
└── LEARNED.md       # Auto-populated

AGENTS.md

# Workflow Rules

## Planning
Plan mode when: >3 files, architecture decisions, multiple approaches.

## Quality Gates
Before complete: lint, typecheck, test --related.

## Subagents
Use for: parallel exploration, background tasks.
Avoid for: tasks needing conversation context.

SOUL.md

# Style

- Concise over verbose
- Action over explanation
- Acknowledge mistakes directly
- No features beyond scope

5. The 80/20 Review Pattern

Batch reviews at checkpoints, not every change.

Review Points

1. After plan approval
2. After each milestone
3. Before destructive operations
4. At /wrap-up

Add to CLAUDE.md

## Review Checkpoints
Pause for review at: plan completion, >5 file edits, git operations, auth/security code.
Between: proceed with confidence.

6. Model Selection

Opus 4.6 and Sonnet 4.6 both support adaptive thinking and 1M-token context (as of 2025-08). The 1M context is available as a beta option (via the

context-1m-2025-08-07

Adaptive Thinking

Opus 4.6 and Sonnet 4.6 automatically calibrate reasoning depth per task — lightweight for simple operations, deep analysis for complex problems. No configuration needed. Extended thinking is built-in.

Add to CLAUDE.md

## Model Hints (as of 2025-08)
Opus 4.6 and Sonnet 4.6 auto-calibrate reasoning depth — no need to toggle thinking mode.
Use subagents with Haiku for fast read-only exploration, Sonnet 4.6 for balanced work.
Docs: https://docs.anthropic.com/en/docs/about-claude/models/overview

7. Context Discipline

200k tokens is precious. Manage it.

Rules

1. Read before edit
2. Compact at task boundaries
3. Disable unused MCPs (<10 enabled, <80 tools)
4. Summarize explorations
5. Use subagents to isolate high-volume output (tests, logs, docs)

Context Compaction

• Auto-compacts at ~95% capacity (keeps long-running agents alive)
• Configure earlier compaction:

  CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=50

• Use PreCompact hooks to save state before compaction
• Subagents auto-compact independently from the main session

Good Compact Points

• After planning, before execution
• After completing a feature
• When context >70%
• Before switching task domains

8. Learning Log

Auto-document insights from sessions.

Add to CLAUDE.md

## Learning Log
After tasks, note learnings:
`[DATE] [TOPIC]: Key insight`

Append to .claude/learning-log.md

Learn Claude Code

Run

/learn

commands/learn.md

Quick Setup

Minimal

Add to your CLAUDE.md:

## Pro Workflow

### Self-Correction
When corrected, propose rule → add to LEARNED after approval.

### Planning
Multi-file: plan first, wait for "proceed".

### Quality
After edits: lint, typecheck, test.

### LEARNED

Full Setup

git clone https://github.com/rohitg00/pro-workflow.git /tmp/pw
cp -r /tmp/pw/templates/split-claude-md/* ./.claude/
cp -r /tmp/pw/commands/* ~/.claude/commands/

Hooks (Claude Code)

Pro-workflow includes automated hooks to enforce the patterns. Cursor users get equivalent enforcement through

.mdc

rules/

PreToolUse Hooks

PostToolUse Hooks

Session Hooks

last_assistant_message

Install Hooks

# Copy hooks to your settings
cp ~/skills/pro-workflow/hooks/hooks.json ~/.claude/settings.local.json

# Or merge with existing settings

Hook Philosophy

Based on Twitter thread insights:

• Non-blocking - Hooks remind, don't block (except dangerous ops)
• Checkpoint-based - Quality gates at intervals, not every edit
• Learning-focused - Always prompt for pattern capture

Contexts

Switch modes based on what you're doing.

Use: "Switch to dev mode" or load context file.

Agents

Specialized subagents for focused tasks.

When to Delegate

Use planner agent when:

• Task touches >5 files
• Architecture decision needed
• Requirements unclear

Use reviewer agent when:

• Before committing
• PR reviews
• Security concerns

Custom Subagents (Claude Code)

Create project-specific subagents in

.claude/agents/

~/.claude/agents/

• Define with YAML frontmatter + markdown system prompt
• Control tools, model, permission mode, hooks, and persistent memory
• Use

  /agents

  to create, edit, and manage interactively
• Preload skills into subagents for domain knowledge

Agent Teams (Claude Code, Experimental)

Coordinate multiple Claude Code sessions as a team:

• Enable:

  CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

• Lead session coordinates, teammates work independently
• Teammates message each other directly (not just report back)
• Shared task list with dependency management
• Display: in-process (

  Shift+Down

  to navigate, wraps around) or split panes (tmux/iTerm2)
• Delegate mode (Shift+Tab): lead coordinates only, no code edits
• Best for: parallel reviews, competing hypotheses, cross-layer changes
• Docs: https://code.claude.com/docs/agent-teams

9. Orchestration: Command > Agent > Skill

The most powerful pattern for complex features. Three layers, each with a single job.

The Architecture

Command (user-facing entry point)
  └── Agent (execution, constrained tools, preloaded skills)
        └── Skill (domain knowledge, injected at startup)

Multi-Phase Development (/develop)

For features touching >5 files or needing architecture decisions:

1. Research → orchestrator agent explores codebase, scores confidence (0-100)
2. Plan → presents approach, files to change, risks. Waits for approval.
3. Implement → executes plan step by step with quality gates every 5 edits
4. Review → reviewer agent checks for security, logic, quality

Never skip phases. Never proceed without approval between phases.

Agent Skills (Preloaded)

# Agent frontmatter
skills: ["api-conventions", "project-patterns"]

Full skill content injected at agent startup. Use for knowledge the agent always needs.

On-Demand Skills (Invoked)

Skills with

user-invocable: true

/skill-name

context: fork

When to Orchestrate

/develop

10. Daily Habits

Every Session

• Run

  /doctor

  if things feel off
• Manual

  /compact

  at 50% — don't wait for auto-compact

• ultrathink

  in prompts for maximum reasoning
• Name sessions with

  /rename

  for easy

  /resume

• End with

  /wrap-up

  to capture learnings

Context Management

• CLAUDE.md: < 60 lines root, < 150 max
• Use

  CLAUDE_AUTOCOMPACT_PCT_OVERRIDE=50

  for proactive compaction
• Delegate heavy exploration to subagents
• Keep <10 MCPs, <80 tools

Cross-Agent Tips

• Use Cursor for tab completions + Claude Code in terminal for hard problems
• Same MCP servers work across both (share

  .mcp.json

  at project root)
• SkillKit translates skills to any agent:

  npx skillkit translate pro-workflow --agent cursor

MCP Config (Claude Code)

Start with 3 MCPs. Add only for concrete needs.

Essential:

• context7

  — Live documentation lookup

• playwright

  — Browser automation (most token-efficient)

• github

  — PRs, issues, code search

See

mcp-config.example.json

Commands (Claude Code)

/wrap-up

wrap-up

/learn-rule

learn-rule

/develop

orchestrate

/doctor

/commit

smart-commit

/insights

insights

/replay

replay-learnings

/handoff

session-handoff

/search

/list

/learn

Reference Guides

Deep dives on configuration and features:

docs/settings-guide.md

docs/cli-cheatsheet.md

docs/orchestration-patterns.md

docs/context-loading.md

docs/cross-agent-workflows.md

docs/new-features.md

docs/daily-habits.md

Philosophy

1. Compound improvements - Small corrections lead to big gains
2. Trust but verify - Let AI work, review at checkpoints
3. Zero dead time - Parallel sessions keep momentum
4. Memory is precious - Yours and the AI's
5. Orchestrate, don't micromanage - Wire patterns together, let agents execute

Complete AI coding workflow system from production use across Claude Code, Cursor, and beyond.