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SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
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SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
数据叙事:用可视化/上下文/说服结构把数据变成推动决策的故事。受 wshobson/agents(38k★ MIT)启发。
数据库表设计:主键/规范化/索引/数据类型/约束/性能模式,PostgreSQL 重点 + 通用规范。受 wshobson/agents(38k★ MIT)启发。
数据集整理:清洗、质量筛选、多样性、拆分与标注,LLM 微调前置。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
AI coding delivery trust layer for governance-aware coding agents — zcode plugin packaging. The plugin surface lives in skills/ and commands/; this file only provides the npm package identity expected by the zcode plugin host.
Claude Code compatibility layer for DeepSeek Harness: load .claude skills/commands/agents and install plugins from Claude Code marketplaces as native dsh skills.
Vision-first MCP for text-only Agents, using Agnes AI for image understanding with experimental generation and editing.
Multi-agent dashboard skill for DeepSeek Harness -- status reports, task tracking, progress visualization
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
Unified Editor runtime for DeepSeek Harness, powered by MCP Apps
June dual-persona agents (June-M / June-S) for DeepSeek Harness: a dsh bundle that installs the june-m and june-s agent presets plus the git-backup and june-style skills.
DSH plugin bridging agents to the Xcode headless MCP service (xcrun mcpbridge) over stdio JSON-RPC, exposing Xcode build/test/preview/simulator tools as agent tools. Zero runtime dependencies.
DeepSeek Harness 项目组插件:在一个会话中跨多个项目文件夹工作——读写组内文件、运行命令、查看各项目 AGENTS.md;每个项目可带一句说明,AI 据此快速定位目录。项目组跟随工作区(每个工作区独立默认选择),组内文件路径默认允许读写。官方安装:dsh plugin --profile web add。
DeepSeek Harness-native Roblox Studio MCP companion: Settings UI listing connected Studio instances, active-instance selection exposed to the agent as runtime context, plus live visibility into Studio's official Script Sync and agent guidance for file-first editing.
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
Use ZenMux models in DeepSeek Harness with OAuth login, model search, and protocol-aware routing
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
Four-layer long-term memory for DeepSeek Harness (L0 conversation → L1 atoms → L2 scenes → L3 persona) with auto-recall and auto-capture — adapted from TencentCloud/TencentDB-Agent-Memory