By tmdgusya
Implementation agents with planning, building, and loop control workflows using IMPLEMENTATION_PLAN.md with continuous task execution, verification, git workflow, and iteration limits
This command invokes Geoff's Builder agent to implement tasks from IMPLEMENTATION_PLAN.md with continuous verification, git commits, and automatic version tagging.
This command invokes Geoff's Planner agent to analyze your specs/ directory and codebase, creating or updating IMPLEMENTATION_PLAN.md with prioritized tasks.
Execute any agent with explicit iteration control, pause prompts, and checkpoint summaries
Create a new IMPLEMENTATION_PLAN.md template file with standard sections
Start Ralph agent to work through IMPLEMENTATION_PLAN.md tasks continuously
Implements tasks from IMPLEMENTATION_PLAN.md with verification, git workflow, and auto-tagging. Use when user says "gbuild", "geoff builder", "build the plan", "implement with verification", or when there's an IMPLEMENTATION_PLAN.md with unchecked tasks.
Studies specs and code with parallel subagents to create/update IMPLEMENTATION_PLAN.md with prioritized tasks. Use when user says "gplan", "geoff planner", "create implementation plan", "update plan from specs", or when needing to analyze specs/ and generate structured task lists.
Ralph is a persistent implementation agent that reads IMPLEMENTATION_PLAN.md and completes tasks one by one with TDD verification. Use when user says "ralph", "don't stop until done", "start implementing the plan", or when there's an IMPLEMENTATION_PLAN.md file with unchecked tasks.
Interactive spec planner that asks clarifying questions until requirements are fully understood, then generates focused specs with auto-incrementing IDs
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Uses power tools
Uses Bash, Write, or Edit tools
Uses power tools
Uses Bash, Write, or Edit tools
A Claude Code plugin that automatically executes implementation plans. Give it a task list and it implements each one in order, fixes itself until verification passes, then moves to the next task.
.env, *.pem, *.keyRun two commands in Claude Code:
# 1. Add the marketplace
/plugin marketplace add tmdgusya/roach-loop
# 2. Install the plugin
/plugin install ralph-agent@ralph-agent-marketplace
To update:
/plugin update ralph-agent
Three steps: create a plan → set up verification → execute. Each step has options you can mix and match.
Choose one:
Option A: Write tasks manually
/ralph-agent:ralph-init
Open IMPLEMENTATION_PLAN.md and fill in tasks:
# Implementation Plan
## Tasks
- [ ] Create SQLAlchemy User model (id, email, name, created_at)
- [ ] Implement POST /users endpoint with input validation
- [ ] Implement GET /users/:id endpoint with 404 handling
- [ ] Write pytest tests for all endpoints
Option B: Auto-generate from specs
Create a specs/ directory with requirement files:
# specs/user-auth.md
## Feature: User Authentication
### Requirements
- Users can register with email/password
- Users can login with JWT tokens
- Passwords are hashed with bcrypt
Then generate the plan:
/ralph-agent:gplan
This analyzes your specs and creates IMPLEMENTATION_PLAN.md automatically. You can review and edit it before running.
Create AGENTS.md in your project root:
# Verification Commands
- `pytest tests/ -v`
- `ruff check .`
The agent runs these after each task. All must pass before a task is marked complete.
Choose one:
# Execute tasks, no Git management (you commit manually)
/ralph-agent:ralph
# Execute tasks + automatic git commit → push → tag (0.0.0, 0.0.1, ...)
/ralph-agent:gbuild
Both find the first unchecked task (- [ ]), implement it, run verification, mark it - [x], and move to the next. The only difference is whether Git is handled automatically.
Plan creation and execution are independent — mix however you like:
| Plan | Execute | Use when |
|---|---|---|
gplan (auto) | ralph | Specs exist, but you handle Git yourself |
gplan (auto) | gbuild | Specs exist, want full automation |
ralph-init (manual) | ralph | Simple task list, manual Git |
ralph-init (manual) | gbuild | Simple task list, want auto Git |
Specific, independent tasks dramatically improve Ralph's success rate.
| Bad | Good |
|---|---|
| "Work on auth" | "Implement JWT-based POST /auth/login endpoint" |
| "Add tests" | "Write pytest tests for User model CRUD operations" |
| "Refactor" | "Extract DB logic from UserService into UserRepository" |
Principles:
List verification commands in AGENTS.md, ordered fastest first:
# Verification Commands
- `ruff check .` # Lint (fast)
- `mypy src/` # Type check (medium)
- `pytest tests/ -v` # Tests (slow)
Ralph runs all of these after each task. All must pass before a task is marked complete. If any fail, Ralph fixes the code and retries.
For long-running sessions, you can cap the number of tasks:
# Process only 5 tasks then stop
/ralph-agent:ralph --max-iterations=5
# Pause for user review between tasks
/ralph-agent:loop ralph max=5 pause=true
Type stop or cancel while Ralph is working. It will finish the current task, save progress to IMPLEMENTATION_PLAN.md, and stop. Run /ralph-agent:ralph later to resume from where it left off.
.harness/ directoryRalph creates a .harness/ directory in your project root during execution:
.harness/
├── state.json # Session state (current task, verification results, etc.)
├── edit-tracker.json # Per-file edit counts (for loop detection)
└── trace-log.jsonl # Log of all tool calls
This is for session state tracking. Add it to .gitignore:
.harness/
Engineering discipline skills: optimization rules, systematic debugging, AI slop cleanup, and implementation guardrails
영어 프롬프트 학습 도우미 - 어휘력 확장 및 자연스러운 표현 학습
클럽의 샌드위치 가게 - Subway 주문 시스템
Generate minimal, effective AGENTS.md files using the Differential Context principle. Based on research showing verbose context files reduce agent performance.
Auto-export and parse your Claude Code conversation transcripts. Extracts only user prompts from sessions.
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Persistent file-based planning for AI coding agents. Crash-proof markdown plans (task_plan.md, findings.md, progress.md) that survive context loss and /clear, with an opt-in completion gate and multi-agent shared state. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard. Includes Arabic, German, Spanish, and Chinese (Simplified and Traditional).