todo-manage
Manage and organize TODO.md at project root - plan features, track progress, mark tasks complete, and clean up completed items. Use when pla
Open source Repository Open in the app JSON README (API)
About
Manage and organize TODO.md at project root - plan features, track progress, mark tasks complete, and clean up completed items. Use when planning tasks, organizing work, reviewing priorities, or manag
Details
- Kind
- Agent skills
- Topic
- No topic detected
- Publisher
- sorryhyun
- Origin
- majiayu
- Category
- ferramentas
- Stars
- 13
- Forks
- 2
- Last push
- 2025-12-31T05:50:01Z
- Repository state
- ativo
- Language
- Python
- License
- Apache-2.0
- Added
- 2026-09-01 17:05:58
- Updated
- 2026-09-01 17:05:58
- Origin id
sorryhyun/dipeo/.claude/skills/todo-manage@main
README
# DiPeO, Diagrammed People (agents) & Organizations (agent system)
* The whole codebase was created by vibe-coding, with Claude code & Codex.
> Start with `dipeo ask --to "the command you want to ask" --and-run`
* This will generate diagram and run it as you want to create.
### Why diagram?
* To show how it is **structured**, and how it works **in realtime**.
* For consistent outputs, rather than asking to code.
### Hmm, so can I tweak it?
<div style="text-align: center;"><img src="/docs/pics/img.png" width="85%" alt=""></div>
* Definitely. You can just run `make dev-web` and tweak it in `localhost:3000`
* The whole procedure works inside your computer. Nothing is in cloud or somewhere in network.
### How about the diagram file?
* You can see the diagram file in `.yaml`
<details>
<summary>The diagram file content we created looks like...</summary>
```yaml
version: light
nodes:
- label: start
type: start
position:
x: 330
y: 200
trigger_mode: manual
- label: printer
type: person_job
position:
x: 632
y: 231
default_prompt: say hi
max_iteration: 3
memorize_to: ALL_MESSAGES
person: person 1
- label: endpoint
type: endpoint
position:
x: 0
y: 437
file_format: txt
save_to_file: true
file_path: files/results/total.txt
connections:
- from: start
to: printer
content_type: raw_text
- from: printer
to: endpoint
content_type: raw_text
persons:
person 1:
service: openai
model: gpt-5-nano-2025-08-07
api_key_id: APIKEY_52609F
```
</details>
* For example, the diagram you generated with `dipeo ask ...` will be placed in `projects/dipeodipeo/generated`
* We support `.light.yaml` format which will format the diagram in readable format.
### How can I start?
```bash
# Clone the repository first
make install # Install all dependencies (installs uv if needed)
make graphql-schema # Generate GraphQL types
make dev-all # Start both frontend and backend servers
```
### Ok. So is there a rule for diagram? Or, would you explain more detail?
* Yes, here is the documentary in detail.
- [Full Documentation Index](docs/index.md) - Complete list of guides and technical documentation
- [User Guide](docs/README.md) - Getting started with DiPeO diagram editor
- We are developing some interesting projects using `dipeo` itself. Take a look at [projects](docs/projects)
---
> DiPeO(daɪpiːɔː) is a **monorepo** for building, executing, and monitoring AI‑powered agent workflows through an intuitive visual programming environment. The repository is composed of a feature-based React **frontend** (apps/web/), a domain-driven FastAPI **backend** (apps/server/), and a CLI **tool** (apps/server/src/dipeo_server/cli/) that work together to deliver real‑time, multi‑LLM automation at scale.
## 핵심 기능
1. LLM과 작업 블록의 분리를 통한 직관적인 컨텍스트 관리
2. diagram의 yaml 형태 표현 및 실행 tool 제공
3. 다이어그램 엔드포인트를 활용한 A2A canvas 제공 (구현 예정)
For motivations, guide, details in Korean, read [Korean docs](docs/index.md)
### Code Generation (For Development)
If you need to modify the codebase or add new features:
```bash
# After modifying TypeScript specifications in /dipeo/models/src/
cd dipeo/models && pnpm build # Build TypeScript models
make codegen # Generate code (includes parse-typescript)
make diff-staged # Review changes
make apply-syntax-only # Apply staged changes
make graphql-schema # Update GraphQL types
```
## Major Features
### 1. Claude Code Integration
DiPeO features built-in support for Anthropic's Claude Code SDK, enabling seamless integration with Claude's advanced AI capabilities. Simply configure your diagram with Claude Code agents:
```yaml
persons:
Frontend Generator:
service: claude-code
model: claude-code
api_key_id: APIKEY_CLAUDE
system_prompt: |
You are an expert React/TypeScript engineer.
Generate clean, production-ready code.
```
**Key Benefits:**
- Streaming-first architecture for real-time responses
- Built-in conversation management
- Automatic retry logic with exponential backoff
- Context manager pattern for efficient resource usage
For detailed setup and usage, see [Claude Code Integration Guide](docs/integrations/claude-code.md).
### 2. Frontend Auto - Rapid Application Generation
Generate complete, production-ready React applications in 30 minutes with Frontend Auto. This streamlined system creates fully deployable frontends with modern tech stack:
```bash
# Generate a complete chat application
dipeo run projects/frontend_auto/consolidated_generator --light --debug --timeout=120
# Generate with specific variant (e.g., e-commerce, analytics, banking)
dipeo run projects/frontend_auto/consolidated_generator --light --debug --timeout=120 \
--input-data '{"config_file": "variants/ecommerce_config.json"}'
```
**Generated Features:**
- React 18 + TypeScript + Vite
- Tailwind CSS styling
- TanStack Query for data fetching
- React Router v6 navigation
- Complete component architecture (atoms/molecules/organisms)
- Mock API with real-time features
- Vercel-ready deployment configuration
**Available Variants:** Chat applications, e-commerce stores, analytics dashboards, banking portals, CMS systems, healthcare portals, learning platforms, project management tools, and more.
For comprehensive details, see the Frontend Auto project files in `projects/frontend_auto/`.
### 3. Multi-LLM Support
Beyond Claude Code, DiPeO supports multiple LLM providers:
**Ollama (Local Models):**
```yaml
persons:
Frontend Generator:
service: ollama
model: gpt-oss:20b
api_key_id: APIKEY_OLLAMA
system_prompt: |
You are an expert React/TypeScript engineer.
Generate clean, production-ready code.
```
**Custom APIs and Services:**
- Notion integration
- Custom LLM endpoints via cURL
- Any RESTful API service
Thanks to our schema-driven integration system, adding new external API features is straightforward. See `integrations/` directory for examples.
For local model examples, see [Ollama example](examples/simple_diagrams/simple_iter_ollama.light.yaml).
### `dipeo` - Run Diagrams with CLI
#### Run existing diagrams
```bash
# Run diagram with automatic server startup
dipeo run examples/simple_diagrams/simple_iter --light --debug --timeout=25
# Run with specific diagram file
dipeo run examples/simple_diagrams/simple_iter.light.yaml --light --debug
# Run with input data
dipeo run [diagram] --input-data '{"key": "value"}' --light --debug
```
#### Generate diagrams from natural language
```bash
# Generate a diagram from natural language request
dipeo ask --to "create csv preprocessor" --timeout=90
# Generate and immediately run the created diagram
dipeo ask --to "create csv preprocessor" --and-run --timeout=90
# With additional options
dipeo ask --to "build data pipeline" --and-run --timeout=120
```
**Note**: The `dipeo ask` command uses AI to generate DiPeO diagrams from your natural language description. Generation typically takes 150-250 seconds due to multiple LLM calls.
#### Convert Claude Code Sessions to Diagrams
```bash
# List your recent Claude Code sessions
dipeocc list --limit 50
# Convert the latest session to a DiPeO diagram
dipeocc convert --latest
# Convert a specific session by ID
dipeocc convert <session_id> --output-dir projects/claude_code/
# Watch for new sessions and auto-convert them
dipeocc watch --interval 30 --auto-execute
# View session statistics
dipeocc stats <session_id>
```
**Options:**
- `--format`: Output format (light/native/readable, default: light)
- `--merge-reads`: Combine consecutive file reads into single nodes
- `--simplify`: Remove intermediate results for cleaner diagrams
This feature enables you to automatically transform your Claude Code interactions into reusable DiPeO diagrams, making your AI workflows reproducible and shareable.
#### Export Diagrams to Standalone Python Scripts
```bash
# Export a diagram to a Python script that runs without DiPeO
dipeo export examples/simple_diagrams/simple_iter.light.yaml output.py --light
# Run the exported script directly
python output.py
```
**Supported Features:**
- LLM calls (person_job nodes) → Direct OpenAI/Anthropic API calls
- Database operations → File I/O
- Code execution → Inline Python
- Control flow → Native Python structures
The exported scripts are self-contained and only require Python 3.10+ and the `openai`/`anthropic` packages. Perfect for deploying DiPeO workflows as standalone applications.
For detailed usage and examples, see [Diagram-to-Python Export Guide](docs/features/diagram-to-python-export.md).
## Requirements
- **Python 3.13+** (required for uv support)
- **Node.js 22+** with **pnpm 10+** (not npm/yarn)
- **uv** package manager (auto-installed via `make install`)
- Default LLM: `gpt-5-nano-2025-08-07`