aavegotchi-gbm-skillView, create, cancel, bid, and claim Aavegotchi GBM auctions on Base mainnet (8453). Subgraph-first discovery (Goldsky), with onchain verification + executio...
Install via ClawdBot CLI:
clawdbot install cinnabarhorse/aavegotchi-gbm-skillGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Accesses sensitive credential files or environment variables
$PRIVATE_KEYCalls external URL not in known-safe list
https://github.com/aavegotchi/aavegotchi-gbm-skillAI Analysis
The skill accesses sensitive credentials (PRIVATE_KEY) and interacts with external APIs/subgraphs, but all operations are consistent with its stated purpose of managing GBM auctions on Base. Safety rules enforce dry-run defaults, onchain verification, and input validation, mitigating most risks.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 1, 2026
An NFT marketplace integrates this skill to allow users to participate in Aavegotchi GBM auctions directly from their platform. It automates bidding and claiming processes, enhancing user engagement by providing real-time auction data and secure transaction execution. This reduces friction for users who want to acquire or sell Aavegotchi NFTs without leaving the marketplace interface.
A DeFi protocol uses this skill to enable users to bid on Aavegotchi NFTs as part of a yield farming strategy, where holding specific NFTs boosts rewards. It automates auction monitoring and bidding based on predefined criteria, optimizing capital allocation. This adds a gamified layer to yield farming, attracting users interested in both DeFi and NFT ecosystems.
A gaming guild employs this skill to manage Aavegotchi NFT auctions for its members, facilitating collective bidding on high-value assets to share ownership. It ensures secure, onchain verification and execution, minimizing risks of outbidding or errors. This streamlines asset acquisition for guilds, enabling efficient resource pooling and strategic investment in gaming assets.
A trading bot developer incorporates this skill to create automated systems that bid on Aavegotchi GBM auctions based on market trends and price signals. It leverages subgraph data for real-time auction discovery and onchain safety checks to prevent losses. This allows for high-frequency, algorithmic trading in the NFT space, targeting arbitrage opportunities and portfolio diversification.
An educational platform uses this skill as a hands-on example for teaching Web3 development, covering topics like subgraph queries, onchain interactions, and security best practices. Students learn to build and deploy similar tools, gaining practical experience with smart contracts and decentralized applications. This bridges the gap between theory and real-world application in blockchain education.
Offer a software-as-a-service platform where users subscribe to access automated bidding and management tools for Aavegotchi GBM auctions. Revenue is generated through monthly or annual subscription fees, with tiered plans based on features like advanced analytics or higher transaction limits. This model targets power users and institutions seeking efficiency and reliability in NFT trading.
Provide a service that charges a small percentage fee on each successful bid or claim transaction facilitated through the skill. Revenue is earned directly from user transactions, incentivizing the service to optimize success rates and security. This aligns with user interests by only charging when value is delivered, making it attractive for occasional traders and high-volume users alike.
License the skill to enterprises such as NFT marketplaces, DeFi platforms, or gaming companies for integration into their existing products. Revenue comes from one-time licensing fees or ongoing support contracts, tailored to the scale and customization needs of each client. This model leverages the skill's robust safety features and subgraph integration to enhance third-party offerings.
💬 Integration Tip
Ensure all environment variables are securely configured, especially PRIVATE_KEY and BASE_MAINNET_RPC, and always test with DRY_RUN=1 before broadcasting transactions to avoid costly errors.
Scored Apr 19, 2026
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