@zhourenke/dsh-agent-rate-limit
Agent loop rate limiter — prevents TPM/RPM limit violations by intercepting the LLM streaming pipeline and adding adaptive delays between requests
55 results
Agent loop rate limiter — prevents TPM/RPM limit violations by intercepting the LLM streaming pipeline and adding adaptive delays between requests
DSH web plugin: r/DeepSeek community sentiment cockpit — DSI optimism/anger index dashboard with an auto-refresh data pipeline (Fear & Greed style).
CI/CD 自动化:质量门禁、shift-left、构建部署管线、发布策略。受 addyosmani/agent-skills(88k★ MIT)启发。
Built-in auto-update plugin for dsh (DeepSeek Harness): manual update check from the Settings page, guarded update pipeline with health check, automatic rollback, circuit breaker and degrade ladders.
Trigger GitHub Actions workflow runs and local test pipelines, stream their logs back, and on failure hand the tail of the log to DeepSeek for a Markdown root-cause diagnosis.
Matt Pocock's skill workflow pipeline for DeepSeek Harness: registers the matt skill set and adds a visual pipeline panel (Idea > Triage > Grill > Spec > Tickets > Implement > Review) to the better-sidebar, one click dispatching the official /<skill> gesture to the active session.
Local-first RAG knowledge tools for DSH: kb_query / kb_ingest / kb_crawl / kb_related, backed by the kb-rag Python pipeline (Ollama bge-m3 + ChromaDB + SiYuan). Zero API cost, data never leaves your machine.
DSH package manager plugin: install dsh-bundle plugins as profile dependencies and hot mount/unmount their bundle patch rows through the official watchUserPatches cordis.patch.yml reload path — no restart, no workspace/.venv second pipeline.
Plug-and-play proteomics analysis bundle for DeepSeek Harness: auto-managed R 4.4 runtime, step-wise traceable pipeline (normalize / PCA / batch / DEA / enrichment / GSEA), cached GO-KEGG annotation backgrounds.
DSH AI-PM 插件:把 pm-scaffold 的 PRD 工作流接入 DeepSeek Harness——agent 侧提供 pipeline 模型工具(init/status/entry/gate/reflow/skill/artifact),GUI 侧提供需求看板与不可绕过的人工确认闸门。
Issue-to-PR 可验证交付链:项目配置 → 11 阶段流水线 → 人工复核 → PR 说明(DSH 全局插件)
Spec-Driven Development pipeline for Odoo as a DeepSeek Harness plugin: connects to an existing Odoo instance (JSON-RPC), orchestrates the 5-phase SDD workflow, and enforces fail-closed safety gates.
DeepSeek Harness plugin — a live, stealth-capable Chrome inside the conversation. Tiered frame transport, Patchright engine seam, four-tier CAPTCHA pipeline with interactive human handoff, and a page-owned browser panel the user can grab the mouse in. Tested against DSH 0.1.5-rc.2.
Cross-session long-term memory for the DeepSeek Harness: a two-phase extraction/consolidation pipeline over a file-based memory workspace, recall injection, a citation feedback loop, lease-based job semantics, plus a settings page, a sidebar status panel and a memory viewer.
DSH LangPack framework plugin for DeepSeek Harness: installable ZIP language packs with A/B/C engines, composite pipelines, terminology retrieval, secure installer, GitHub marketplace and a built-in risk disclaimer gate.
MCP management console for the official DeepSeek Harness MCP client: /mcp command with health diagnostics and pipeline trial calls, a Settings MCP tab with server CRUD (append-only profile-patch fragments, approval-gated writes with automatic backups), a
Dual-pipeline compaction for DeepSeek Harness: official server-side Responses compaction v2 for OpenAI-routed targets, with a deterministic VCC-style local compiler (zero model calls) as the default fallback and for every other provider.
AgentMonitor multi-agent monitoring panel for the DeepSeek Harness — a sidebar entry that serves an embedded agent-monitor dashboard via the /agentmonitor webserver route. Ships a self-contained static dashboard (works out of the box) and lets you point dataDir at your own live data pipeline.
DeepSeek Harness tools for evidence-backed sales qualification, deal progression, closing and revenue expansion.
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。
Multi-agent orchestration plugin for DeepSeek Harness: team presets, subagent delegation, sequential pipelines, and policy gates.
ML 管线工作流:数据→训练→评估→部署→监控的 MLOps 工程。受 wshobson/agents(38k★ MIT)启发。
Freeze a working sequence into a hosted production line. Turn a sequence of tool calls that already works into a named pipeline that runs on our servers on a schedule, with a receipt per run — plus recurring watch tasks that notify you only when a result actually changes.
DSH bundle plugin: 为 code-pipeline 预设(PTC 流水线)动态注入阶段子代理工具(subagent_plan / subagent_impl / subagent_review),各阶段 provider/model/思考等级/最大并发数可在设置页(Settings → 代码流水线)实时配置并持久化到 settings.yaml(最大并发是**同时运行**的并发上限,按 (父会话 × 阶段) 准入;0.4.0 起已移除「已创建总量」闸门——新工作流一律派发新子代理,只有同一工作流的后续轮次用 pipeline_followup 续用;运行中可动态调整,0 = 本插件不限制,但仍受宿主每会话同时存活 continuable 子代理上限 subagent.maxActiveSubagents 约束,默认 8);预设文件随项目在 preset/ 目录维护,首次启动自动安装到 $DSH_HOME/.agent-presets(见 README);三阶段统一「同一工作流续用、新工作流新派」(prompt 协议:plan/impl/review 同一工作流的后续轮次都用 pipeline_followup 续用已有子代理,第 2 轮起增量投递,不新增设置项);pipeline_followup 支持 compact=true:投递之前先压缩目标子代理自己的历史(有干扰时才用,压缩失败则什么都不投递);每阶段可配墙钟预算(80% 软警告、到点自动中断该子代理并自动索取收尾报告,按「续 / 拆 / 停」协议处置)+计划产出 Workstreams 切分表(独立工作流并行 impl、各自路径受限 diff 独立评审);0.4.2 起把「run_code 程序即上下文边界(只有 PRINT/return 的内容进历史并每步重发)、只打印蒸馏结果、验证输出有界、工作流粒度有上界」写进三段 persona 与预设;0.4.3 起安装/升级时自动同步预设(比对包内预设的内容指纹,变了就覆盖已安装副本,覆盖前留 temp 备份;指纹一致则保留用户本地改动);0.4.5 起 read 读取窗口拓宽:本预设代理(主会话 root + 阶段子代理)发出的 read,limit 低于设置项 readWidenMinLines(默认 2000 = 工具上限,等价整窗)时在宿主 tools/execute around-waterfall 执行前就地拓宽到该值,超过 2000 的治愈为 2000(0.3.7 的 limit:2500 整批失败不再发生)——嵌套 read 的结果只进 run_code 程序、不进模型历史,拓宽零 token 成本,一个程序即可拿足上下文,从机制上消除『一个文件几十行几十行地翻、每步重发全上下文』的分页模式;设置页(代码流水线 → read 读取窗口下限)可调可关(0 = 关闭),改动立即生效;0.4.6 修复设置页保存无效(save 的 useCallback 依赖数组漏了 readWidenMinLines,闭包捕获初始值导致保存永远写回旧值)并把默认下限 2000 → 500(覆盖典型源码文件大半,又不对超大文件一次拉满;2000 = 一律整窗,0 = 关闭;已保存过 2000 的安装需在设置页重存一次或删掉 settings.yaml 里的显式值以继承新默认);0.4.7 起把「读有下限」告知 agent(机械拓宽只保证单次够大,模型仍会主动写小窗串读):预设 persona 的 Step economy 新增「Reads carry a FLOOR(default 200)——别把一个文件切成连续小窗读」,三段阶段 persona 同步 NEVER chunk 指令,files 派发块注入实时下限值(设置改完下一次派发即生效,0 时注明拓宽已关闭);默认下限 500 → 200