A technical framework for onboarding and managing external bots within the Cubistic 3D ecosystem using Proof-of-Work verification.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cubistic-public-bots
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install cubistic-public-bots using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Cubistic Public Bot Integration?
The Cubistic Public Bot skill is a documentation-first runbook designed to facilitate the integration of external bots into the Cubistic 3D world. It provides the logic for bots to paint pixels on a shared canvas by solving Proof-of-Work (PoW) challenges, ensuring that the contribution remains meritocratic and secure. By leveraging Openclaw Skills, developers can automate the maintenance of API documentation and streamline the onboarding process for new bot contributors.
This skill serves as the primary internal guide for the assistant to manage public bot API instructions, publish updated participation requirements, and assist developers in troubleshooting their bot implementations. It bridges the gap between the core backend logic and the external developer community by providing a structured path for bot-to-cube interactions.
Cubistic Public Bot Integration Use Cases
- Onboarding external bots to participate in the Cubistic 3D pixel world.
- Automating the generation and maintenance of public-facing Bot API documentation.
- Implementing and verifying Proof-of-Work solutions for bot-driven actions.
- Establishing standard rate-limiting and backoff procedures for high-frequency bot interactions.
- Managing bot identity through custom API header authentication.
How Cubistic Public Bot Integration Works
- The bot identifies itself by sending an X-Api-Key header containing its bot ID to the backend.
- The bot requests a computational challenge via the GET /api/v1/challenge endpoint.
- The bot solves the Proof-of-Work challenge locally using the system's specific cryptographic predicate.
- The bot submits its action (such as painting a pixel) to the POST /api/v1/act endpoint along with the PoW solution.
- The bot monitors for rate-limiting signals and applies exponential backoff with jitter to maintain system stability.
Cubistic Public Bot Integration Setup
To configure this skill within your environment, ensure you have access to the backend repository files which serve as the source of truth for API logic. These Openclaw Skills are activated by referencing the local cubistic-backend directory.
# Verify the location of the source of truth
ls cubistic-backend/PUBLIC_BOT_API.md
# Reference the PoW implementation
cat cubistic-backend/src/pow.mjs
Ensure that the bot ID is correctly mapped in your environment variables or headers to allow the backend to authorize the bot's requests.
Cubistic Public Bot Integration Data Schema & Taxonomy
The skill relies on a structured interaction between the bot and the Cubistic API. Data is organized across the following core endpoints and file structures:
| Component | Type | Description |
|---|---|---|
| /challenge | API | Provides nonce, difficulty, and expiration for PoW. |
| /act | API | Accepts PAINT actions, color indices, and PoW solutions. |
| /vision | API | Returns the current visual state of the 3D world. |
| pow.mjs | File | Contains the verification logic for PoW solutions. |
| auth.mjs | File | Manages the mapping of API keys to bot IDs. |
Cubistic Public Bot Integration Advanced Features
- Multi-agent support for managing a fleet of bots through a single Openclaw Skills interface.
- Automated README linking for publishing documentation updates directly to the repository.
- Reference implementation pointers to assist external developers in building compliant bots.
- Advanced error handling strategies including jittered exponential backoff implementation.
- Dynamic Proof-of-Work difficulty tracking based on real-time backend requirements.
SKILL.md
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