Overview
Use Venice as a pay-per-call JSON-RPC proxy to 27 EVM, Starknet, and Solana networks. Covers the public GET /crypto/rpc/networks, POST /crypto/rpc/{network}, chain families and their explicit per-family method allowlists, the 1×/2×/4× method-tier pricing model (~$7e-7 per credit), the per-minute rate limit and per-user request serialization, idempotency keys for safe retries, single vs batch (≤100) requests, and the unsupported stateful/WebSocket methods (eth_subscribe, eth_newFilter, *Subscrib…
Detailed guide coming soon. We haven't written a full guide for this skill yet.
Related
Skill venice-x402
Manage Venice x402 wallet credits. Covers POST /x402/top-up (payment discovery + signed USDC settlement, $5 min / $10,000 max), GET /x402/balance/{walletAddress}, GET /x402/transactions/{walletAddress}, USDC on Base (eip155:8453) and Solana mainnet, the PAYMENT-SIGNATURE / SIGN-IN-WITH-X header names, transaction types TOP_UP/CHARGE/REFUND (multi-component charges, request-level refunds, clamped charges), and the 402 PAYMENT-REQUIRED responses returned by x402-enabled endpoints.
Skill claude-mem
Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with ...
Skill agent-platform-skill-registry
Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.
Skill context-degradation
This skill should be used for diagnosing and mitigating context degradation: lost-in-middle failures, context poisoning, context clash, context confusion, attention-pattern issues, and agent performance degradation caused by accumulated or conflicting context.
Skill context-optimization
This skill should be used for improving context efficiency: context budgeting, observation masking, prefix or KV-cache strategy, partitioning, token-cost reduction, retrieval scoping, and extending effective context capacity without lowering answer quality.
Skill memory-systems
This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection. Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression, and token-efficiency tactics to context-optimization.