跳到主要内容
知仓学习社ZHICANG

pro-workflow

Complete AI coding workflow system. Orchestration patterns, 18 hook events, 8 agents, cross-agent support, reference guides, and searchable learning…

写文件严重 0 · 高危 2rohitg00/pro-workflow

它会碰到什么

扫了多少1 个文本文件,16 KB
它会碰到什么写文件
命中总数2 处
命中统计严重 0 · 高 2 · 中 0 · 低 0
逐条看命中(2 条严重或高危)
  • SKILL.md:363identity-config-write
    cp ~/skills/pro-workflow/hooks/hooks.json ~/.claude/settings.local.json
  • SKILL.md:499identity-config-write
    - Same MCP servers work across both (share `.mcp.json` at project root)

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

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 skills add. 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.

| Rule | Prevents |

|------|----------|

| Surface, don't assume | Wrong interpretation, hidden confusion, missing tradeoffs |

| Minimum viable code | 200-line diffs that should be 50, speculative abstractions |

| Stay in your lane | Drive-by refactors, "improvements" to adjacent code |

| Verifiable goals | Endless re-clarification, "make it work" loops |

Full rules in rules/pre-flight-discipline.mdc (alwaysApply: true). Pairs with self-correction: pre-flight stops the mistake, self-correction captures the lesson when one slips through.

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

| Scenario | Action |

|----------|--------|

| Waiting on tests | Start new feature in worktree |

| Long build | Debug issue in parallel |

| Exploring approaches | Try 2-3 simultaneously |

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

Current lineup (2026): Fable 5, Opus 4.8, Sonnet 5, and Haiku 4.5. The flagship tiers carry a 1M-token context; Haiku 4.5 is 200K. Frontier models converged, so the harness and the effort setting decide output quality more than the model choice. See [references/models-2026.md](../../references/models-2026.md) for strings, prices, and routing.

| Task | Model | Effort |

|------|-------|--------|

| Quick fixes, lookups | Haiku 4.5 | low |

| Features, balanced work | Sonnet 5 | high |

| Refactors, architecture, hard debug | Opus 4.8 | xhigh |

| Long-horizon autonomous builds | Fable 5 | high / xhigh |

Effort and adaptive thinking

Fixed thinking budgets are retired on the current tiers. Control depth with effort (low through xhigh to max); xhigh is the default for coding and agentic work. Adaptive thinking lets the model calibrate reasoning per step with no fixed budget. Run grunt subagents at low effort on Haiku and keep the reasoning path on the capable tier.

Add to CLAUDE.md

## Model Hints
Route by task: Haiku 4.5 for lookups, Sonnet 5 for features, Opus 4.8 for
architecture and hard debugging, Fable 5 for long-horizon builds.
Effort is the lever, not thinking budgets: xhigh for coding, low for subagents.

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 for a topic-by-topic guide covering sessions, context, CLAUDE.md, subagents, hooks, and more (see commands/learn.md). Official docs: https://code.claude.com/docs/


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 in the rules/ directory.

PreToolUse Hooks

| Trigger | Action |

|---------|--------|

| Edit/Write | Track edit count, remind at 5/10 edits |

| git commit | Remind to run quality gates |

| git push | Remind about /wrap-up |

PostToolUse Hooks

| Trigger | Action |

|---------|--------|

| Code edit (.ts/.js/.py/.go) | Check for console.log, TODOs, secrets |

| Test commands | Suggest [LEARN] from failures |

Session Hooks

| Hook | Action |

|------|--------|

| SessionStart | Load LEARNED patterns, show worktree count |

| Stop | Context-aware reminders using last_assistant_message |

| SessionEnd | Check uncommitted changes, prompt for learnings |

| ConfigChange | Detect when quality gates or hooks are modified mid-session |

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.

| Context | Trigger | Behavior |

|---------|---------|----------|

| dev | "Let's build" | Code first, iterate fast |

| review | "Review this" | Read-only, security focus |

| research | "Help me understand" | Explore, summarize, plan |

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


Agents

Specialized subagents for focused tasks.

| Agent | Purpose | Tools |

|-------|---------|-------|

| planner | Break down complex tasks | Read-only |

| reviewer | Code review, security audit | Read + test |

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/ or user-wide in ~/.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

All four phases run in order. Each phase requires explicit user approval before the next phase begins.

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 are called via /skill-name. Use context: fork for isolated execution that doesn't pollute main context.

When to Orchestrate

| Scenario | Pattern |

|----------|---------|

| Feature > 5 files | /develop with orchestrator |

| Bug investigation | debugger agent |

| Quick exploration | scout agent (background) |

| Code review | reviewer agent |

| Simple task | Just do it directly |


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)
  • skills add installs to any agent: npx skills add rohitg00/pro-workflow

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 for setup and curated recommendations.


Commands (Claude Code)

| Command | Purpose | Cursor Equivalent |

|---------|---------|-------------------|

| /wrap-up | End-of-session ritual | wrap-up skill |

| /learn-rule | Extract correction to memory | learn-rule skill |

| /develop | Multi-phase feature build | orchestrate skill |

| /doctor | Health check | — |

| /commit | Smart commit with quality gates | smart-commit skill |

| /insights | Session analytics and patterns | insights skill |

| /replay | Surface past learnings | replay-learnings skill |

| /handoff | Session handoff document | session-handoff skill |

| /search | Search learnings by keyword | — |

| /list | List all stored learnings | — |

| /learn | Topic-by-topic Claude Code guide | — |


Reference Guides

Deep dives on configuration and features:

| Guide | Topics |

|-------|--------|

| references/settings-guide.md | All settings keys, permission modes, hierarchy, sandbox, env vars |

| references/cli-cheatsheet.md | Every CLI flag, keyboard shortcut, slash command |

| references/orchestration-patterns.md | Command > Agent > Skill architecture, frontmatter reference |

| references/context-loading.md | CLAUDE.md monorepo loading, agent memory, skills discovery |

| references/cross-agent-workflows.md | Claude Code + Cursor config mapping, background agents |

| references/new-features.md | Voice mode, agent teams, checkpointing, new hook events |

| references/daily-habits.md | Session habits, debugging tips, terminal setup, anti-patterns |


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.

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

它属于哪个仓库

星标★ 2,870
本站分层T1
该仓技能数41
原文件路径skills/pro-workflow/SKILL.md

同一个仓库里的其他技能

看这个仓库的全部 41 个技能