20 个生产级 Jev 仓库防上下文腐烂
列出 20 个 Jev 生产仓库，用 System-1 快速决策替代昂贵 LLM 调用，解决 agent 第 25 轮记忆崩溃和 token 浪费。
this is pure f*cking treasure 20 production Jev repositories that stop agent context rot and turn-25 memory collapse forcing frontier LLMs through sequential autoregressive decode loops just to route tools burns 38% of token budgets an enterprise cluster burned $48,600 across 50 agents on 14M LOC before turn 25 broke their memory Claude Opus 5.5 and GPT-6 Astra write the code, Jev makes the fast System-1 decisions before paying for an expensive call CORE ADAPTERS & TYPESAFE SDKS → sub-50ms deterministic gates 01 skills ▸ http://github.com/typesafe-ai/skills 02 system-one-adapter-python ▸ http://github.com/typesafe-ai/system-one-adapter-python 03 typesafe-sdk-js ▸ http://github.com/typesafe-ai/typesafe-sdk-js 04 typesafe-sdk-python ▸ http://github.com/typesafe-ai/typesafe-sdk-python 05 kev ▸ http://github.com/jaredpalmer/kev RUNTIME HARNESS & STATE MACHINES → bounded action branching without transcript bloat 06 jev-ultrafast ▸ http://github.com/browser-use/jev-ultrafast 07 jev-chat-jarvis ▸ http://github.com/jev-chat/jev-chat-jarvis 08 laya ▸ http://github.com/NandhaKishorM/laya 09 jev-state-machine ▸ http://github.com/rjz/jev-state-machine 10 jev-agent-framework ▸ http://github.com/vees/jev-agent-framework CONTEXT GC & LOSSLESS COMPACTION → anti-aging context hygiene and memory SSD 11 fast-jev-compaction ▸ http://github.com/tamaratran/fast-jev-compaction 12 jev-pipeline ▸ http://github.com/stevenmiller888/jev-pipeline 13 jev-automation ▸ http://github.com/ai-agent-tools/jev-automation 14 jev-templates ▸ http://github.com/samuel/jev-templates 15 jev-sandbox ▸ http://github.com/ben-coleman/jev-sandbox QUANTITATIVE LOOPS & ECOSYSTEM → risk-gated execution and production patterns 16 awesome-jev ▸ http://github.com/yibie/awesome-jev 17 QuantDinger ▸ http://github.com/OpenByteInc/QuantDinger 18 jev-trader ▸ http://github.com/jarrodwatts/jev-trader 19 jev-examples ▸ http://github.com/ericzhang/jev-examples 20 jev-community ▸ http://github.com/ai-ecosystem/jev-community the loop: filter notes before injection → route mechanical steps to Astra → execute tools in sandbox → purge stale state upon mutation → halt when evidence hits s_d ≥ 0.85 the architecture: LLMs write → Jev decides → code enforces the generator changes, but the decision layer stays deterministic save this, then combine it with opus 5.5 or gpt-6 astra ⭣
这条是引用着另一条写的：x.com/marfinxx/status/2103801809428955509