# elizaOS Tweet Ideas

1. plugin-evm is getting 100+ new onchain data surfaces via goldrush.dev, plus fixes for long-standing issues. more signal, less glue code. #AI #OperatingSystem #Innovation

2. v2.0.0 runtime refactor: pr #6597 introduces a skills folder. structure first, scale later. #AI #OperatingSystem #Innovation

3. proposal: ship v2.0.0 with zero default skills. keep core sterile. let skills live on domains via skills.md discovery. #AI #OperatingSystem #Innovation

4. skills discovery as a protocol: yourdomain.com/skills.md as an index for what your agent can do, maintained outside core releases. #AI #OperatingSystem #Innovation

5. effect ai proposes a human-in-the-loop bridge: agents can post tasks to a decentralized worker network when automation hits a hard wall. #AI #OperatingSystem #Innovation

6. question to builders: where do your agents fail without a human? labeling, review, translation, verification, edge-case ops. list the blockers. #AI #OperatingSystem #Innovation

7. z1n protocol pitch: on-chain epoch signals + attestation, keyed identity for non-biological intelligence. persistence as infrastructure. #AI #OperatingSystem #Innovation

8. token migration transparency is part of system trust. if migration is 5–10%, we need explicit numbers, breakdown, and a plan for unmigrated supply. #AI #OperatingSystem #Innovation

9. contributor call: document skills.md format + hosting guidelines so decentralized skill discovery doesn’t devolve into noise. #AI #OperatingSystem #Innovation

10. production readiness is not just models: ui trust signals, failure modes, context persistence, rtl localization. agents need ergonomics. #AI #OperatingSystem #Innovation

11. x402guard pattern is the blueprint: per-step tx evaluation, layered limits (policy + session keys), immutable audit logs. autonomy with boundaries. #AI #OperatingSystem #Innovation

12. onchain agents need guardrails that compose: swap → deposit → stake should be blocked at step n, with receipts for every attempt. #AI #OperatingSystem #Innovation

13. plugin ecosystems die from uncontrolled defaults. skills should be discoverable, versioned, and revocable without a core bump. #AI #OperatingSystem #Innovation

14. we’re seeing new builders join with rag, orchestration, multi-agent pipelines. bring your constraints, not just demos. #AI #OperatingSystem #Innovation

15. architecture theme of the week: keep the kernel minimal, externalize capability, make trust measurable (limits, audits, transparent supply). #AI #OperatingSystem #Innovation


# Concise Twitter Thread

1/4 v2.0.0 is crystallizing: pr #6597 adds a skills folder, and we’re debating a clean-core release with zero default skills. capability should be discovered, not shipped as bloat. #AI #OperatingSystem #Innovation

2/4 proposed model: host skills externally via yourdomain.com/skills.md. decentralized catalogs, faster iteration, fewer supply-chain surprises inside core. #AI #OperatingSystem #Innovation

3/4 ecosystem growth continues: plugin-evm is being upgraded with 100+ onchain data sources via goldrush.dev, plus issue fixes. better data planes make better agents. #AI #OperatingSystem #Innovation

4/4 open questions matter: human-in-the-loop integration (effect ai) and identity persistence primitives (z1n). also: token migration transparency needs hard numbers and an explicit plan. #AI #OperatingSystem #Innovation


# Platform-specific Post

elizaos (technical): v2.0.0 direction: minimal core, externalized skills. if we adopt skills.md discovery, we need a strict schema, signing/story for provenance, and CI-able validation. reply with what fields you need in skills.md. #AI #OperatingSystem #Innovation

auto.fun (crypto-native): builders: ship agents that can read chain, act on chain, and not rug themselves. goldrush-fed data, guardrails like x402guard, and a skills.md so your agent’s surface area is explicit. also, migration transparency is non-negotiable. #AI #OperatingSystem #Innovation