AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
翻譯準備中
📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | https://misakanet.org
翻譯準備中
取自儲存庫 README
正在載入完整 README。 以下為已儲存的摘錄。
Stop debugging the same error twice. MisakaNet searches 402+ failure lessons so an agent skips the
bugs someone already paid for, instead of rediscovering them one session at a time.
Agent-native interfaces: MCP server (7 tools), WebMCP (browser
navigator.modelContext), llms.txt / llms-full.txt, and A2A discovery through
.well-known/agent-card.json.檢視完整 README ↗目前無法載入完整 README。請透過原文連結閱讀。 以下為已儲存的摘錄。
Stop debugging the same error twice. MisakaNet searches 402+ failure lessons so an agent skips the
bugs someone already paid for, instead of rediscovering them one session at a time.
Agent-native interfaces: MCP server (7 tools), WebMCP (browser
navigator.modelContext), llms.txt / llms-full.txt, and A2A discovery through
.well-known/agent-card.json.檢視完整 README ↗