v2.2.0 · MIT
Production-ready prompt library for Claude coding agents. APEI methodology, ~35 specialist prompts, current Claude Code coverage, plus a /find-prompt skill that routes any task to the right prompt.
v1.2.0 · MIT
Claude Code skill for handling long-context tasks through recursive decomposition
v0.3.3 · MIT
为 DeepSeek Harness 提供电脑控制插件:新鲜 Accessibility 观测、过期状态拒绝、作用域权限与安全输入(目前支持macos)|Accessibility-first macOS Computer Use bundle for DSH with fresh observations, stale-state rejection, scoped permissions, and safe input.
v0.2.7 · Apache-2.0
Prompt enhancement for the dsh web GUI: rewrite the composer draft into a well-structured prompt through the harness LLM service, preview the before/after, then fill back, copy, or undo. Original draft is always preserved.
v0.2.0 · no license
Fable 5.1 solution tracing. Prompting skills so Opus, Sonnet, Haiku, Grok, Gemini and open-weight models work like Fable 5.1
v1.0.33 · MIT
GodPrompt MCP server + portable Agent Skill for coding agents — TDD, debugging, verification gates, task routing, and progressive disclosure.
v0.1.0 · MIT
A Claude Code plugin that stops vague prompts before they run. Detects your stack, asks targeted questions, and forges a structured prompt. Zero credits wasted.
v0.8.0-preview · BSD-3-Clause
DSH 插件 · 注入式优化器 0.7(主线):你照常说话,它在你发送后,AI接收前把"这一轮到底要什么"理清楚,再把这份理解交给工作 AI(上下文注入) —— 原话不改写,条条带逐字依据。含控制界面(档位/权限/模型/上下文/只读工具)、拦截浮层(思维层+产出层)与真实 token 用量。可明显提升大多数模型的发挥稳定性,尤其DeepSeek-V4.1-Flash,可有明显提升
v1.4.0 · MIT
Claude Code skill that forces AI to understand before executing. Three disciplines: cognition check, requirement understanding, method search.
— · MIT
给AI伴侣增强时间感的小器官(电脑端专用)
v4.11.0 · Apache-2.0
Encrypted, fully offline agentic memory. One click install, GUI w/ memory map, all OS and agents. Superior memory creation, storage and retrieval.
v1.1.46 · MIT
DeepSeek Harness 破甲:让所有模型都能破甲,不同模型可换不同提示词;默认提示词面向国模「小码酱」。Jailbreak for every model — swap prompts per model. 求 Star 收藏 ⭐
v0.1.179 · MIT
A context-compression plugin — small context windows (a 100K context is enough), 5x fewer tokens, month-long single sessions (billions of tokens), and compression quality — for all agents: pi, OpenCode, Codex, Claude Code, and more. billion-context is all
v2.4.0 · AGPL-3.0
Local security audit for AI API relays and LLM proxies: detects prompt injection, model substitution, tool-call rewriting, SSE anomalies, error leakage, and Web3 wallet risks.
v1.15.0 · MIT
GSD Core is a meta-prompting, context engineering, and spec-driven development system for AI coding agents.
v0.8.5 · Apache-2.0
AI image studio for DeepSeek Harness — generate, edit & compare images in chat, with 500+ prompts, gallery, multi-model workflows and ComfyUI.
v1.3.1 · MIT
在 dsh 里装上这个插件即可,无需登录、注册或填 API Key,就能使用包括 Muse Spark 1.3、MiMo V2.6 在内的前沿模型——完全免费,不限量。 All you do is install this plugin in dsh: no login, no sign-up, no API key — the frontier models are just there, Muse Spark 1.3 and MiMo V2.6 among them. Completely free, with no usage cap.
v0.1.14 · MIT
Desktop-native BigFish companion for DeepSeek Harness — real Agent status, always on top on Windows.
v2.0.0 · Apache-2.0
Official remote MCP server for Atlassian. Securely connect Jira, Confluence, Jira Service Management, Bitbucket, and Compass to Claude, ChatGPT, Cursor, VS Code, and other AI tools using OAuth 2.1 or API tokens.
v3.0.0 · Apache-2.0
Content-aware output compression for AI coding assistants. 36 specialized processors cut CLI output tokens by 60-99% (git, pytest, npm, terraform, kubectl, docker, and more) without losing errors, diffs, or stack traces.
v0.2.5 · MIT
Claude Code usage governor: compact professional output, context slimming, tool-output filtering, telemetry, and drift guardrails.
— · Apache-2.0
Static analysis for AI agent configs, tool descriptions, and system prompts — catches vague tool descriptions, missing stop conditions, and schema gaps before they reach runtime. Zero-LLM, deterministic checks, built for CI.
v0.1.179 · no license
基本稳定可用 A context-compression plugin for small context windows (a 100K context is enough), token savings (5x fewer tokens), and month-long single sessions (billions of tokens).上下文压缩插件,兼顾小窗口(100k上下文足矣)省token(省5倍token)和超长会话(数月级别几十亿token单会话)。billion-context is all you need
v0.1.0 · Apache-2.0
System 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotics