near-batch-sender_skill

Overview

This skill provides batch operations for NEAR blockchain accounts, enabling token sends, NFT transfers, and reward claims with built-in cost estimation and progress tracking. It simplifies repeating transactions by consuming structured JSON inputs and estimating gas before execution. The tool focuses on safe bulk workflows for developers, operators, and DAO treasuries.

How this skill works

You provide a sender account and a JSON file that lists recipients, transfers, or claims. The skill parses the file, constructs NEAR batch transactions, estimates gas and fees, and then executes each action while reporting progress. It supports three main modes: send (native token transfers), nft (token transfers across contracts), and claim (collecting rewards or airdrops).

When to use it

• Distributing payroll, payouts, or token airdrops to many NEAR accounts at once.
• Moving multiple NFTs from a single operator account to different recipients.
• Claiming many pending rewards or airdrops in one run to save manual steps.
• Estimating gas and fee exposure before executing a large batch.
• Automating recurring bulk transfers for DAO or community treasuries.

Best practices

• Validate your JSON file locally and include only intended accounts to avoid mistakes.
• Run the estimate command first to confirm total gas and fees before sending transactions.
• Test with a small subset or on a testnet before executing large mainnet batches.
• Monitor progress output and log transaction hashes for auditing and retries.
• Limit batch size per run to reduce risk and allow partial retries on failures.

Example use cases

• Send monthly token stipends to contributors by providing a recipients JSON.
• Transfer multiple NFTs from a collection contract to winners after a contest.
• Claim accumulated validator or protocol rewards for many accounts in one operation.
• Estimate total cost of a planned airdrop to budget funds before execution.
• Automate payroll disbursement from a DAO multisig operator using scheduled runs.