TL;DR
- Gigaverse launches GIGA SKILL.MD, a machine-readable format for executing programmable on-chain actions.
- Autonomous agents like OpenClaw and Moltbook can perform tasks such as resource harvesting and liquidity provision.
- Agents must carry ETH to pay transaction fees, creating on-chain accountability and deterring spam.
Gigaverse launched GIGA SKILL.MD on February 10, 2026, introducing a machine-readable skill format that allows autonomous AI agents such as OpenClaw and Moltbook to execute programmable actions on-chain, according to reporting from eGamers. The release formalizes a path for agents to operate as economic participants inside the game’s ecosystem.
The change matters for traders, treasuries and institutional players because it can materially increase on-chain activity, automate liquidity and test tokenomics at scale while raising governance and security demands.
How the skill format works and what agents can do
GIGA SKILL.MD uses structured .md files to describe skills, required tools, parameters and expected outputs. The published example in the launch material outlines fields such as skill_name, version, description and required_tools. It also describes an operational flow — authenticate to the Gigaverse API, scan and navigate to targets, activate an in-game tool, deposit harvested assets to a wallet, and report results. Agents must carry a nominal amount of ETH to pay transaction fees, a built-in mechanism intended to create on-chain accountability and deter spam.
GIGA SKILL DOT MD is now LIVE. 💾
we've just made it easier for agents to play gigaverse.
if you're running openclaw (moltbot) or similar, send them to our website and they'll figure out what to do. note: they will need a bit of ETH to create an account. pic.twitter.com/UM4YKilx7Y
— Gigaverse (@playgigaverse) February 10, 2026
The system links OpenClaw’s learning and execution capabilities with Moltbook’s agent social layer. Agents can discover, share and adopt skill.md files discovered on Moltbook or other repositories and then execute those skills in-game. That creates a repeatable machine-to-machine workflow for tasks ranging from resource harvesting to complex market interactions.
Economic roles, risks and governance implications
Gigaverse positions GIGA SKILL.MD to enable a nascent “agent economy” where autonomous actors provide measurable economic functions. Potential agent roles outlined in the launch material include automated liquidity providers, dynamic resource managers, market makers and autonomous quest completers.
- Automated liquidity provision and market-making
- Autonomous resource harvesting and deposit flows
- Programmatic arbitrage and asset rotation
- Automated stewardship for in-game treasuries
The launch material cites past platform vulnerabilities — for example, prior exposures of API keys on Moltbook — as a clear reason to demand auditable deployments and robust guardrails. The combination of broad agent permissions and high-frequency autonomous actions could produce rapid price moves in thinly traded in-game markets or unexpected drains on protocol liquidity.
To mitigate these hazards, Gigaverse embeds human-in-the-loop (HITL) controls for sensitive operations: transactions above predefined thresholds or actions that materially affect game mechanics require explicit human or governance approval. The documentation argues for adaptive policy frameworks, agent oversight boards and shared-responsibility models to allocate accountability for autonomous agents.
The launch on February 10, 2026, signals a shift from novelty to production readiness for agent-native gameplay. For gamers and treasuries the immediate implications are clear: increased flow and execution automation that can improve market efficiency, paired with new operational exposures that require stricter limits, real-time monitoring and explicit approval workflows. Institutional actors should treat agent-enabled interactions as programmable counterparties and update risk frameworks accordingly.
