gsd
claudePhase-based dev framework: roadmaps, plans, execution, verification, debugging.
57 commands · 18 agents
Route to GPT, Gemini, Kimi, DeepSeek, Perplexity for cross-model work; Jev decision model for yes/no, choice and scoring.
Plugin ai-gateways from marketplace hamidun in JHamidun/claude-code-config-pack. Commands read from the repo's manifest — 26 days ago.
deepseekDeepSeek API (deepseek-chat): кодогенерация, reasoning, 128K контекст. Триггеры: «дипсик», «спроси deepseek», «дешёвая кодогенерация».
gemini-3-proGoogle AI API (GOOGLE_API_KEY): Gemini text 2M контекст, embeddings, TTS, grounding. Триггеры: «gemini api», «спроси gemini». НЕ картинки→image-generation.
jevJev (TypeSafe): решения вместо LLM — да/нет, выбор из N, шкала за 0,3 с. Триггеры: «классифицируй», «отранжируй», «проверь перед публикацией», «jev». НЕ генерация текста.
kimiKimi у Moonshot (KIMI_API_KEY, модель kimi-k3): глубокий reasoning, код-анализ, алгоритмы. Триггеры: «спроси кими», «Kimi K2», «Kimi K3».
multi-model-gatewayПрогон через Claude, GPT и Gemini разом (AI Gateway) + GPT-6 Astra через Codex CLI. Триггеры: «спроси GPT», «второе мнение», «cross-model», «астра», «через кодекс», «codex exec».
perplexityPerplexity веб-поиск и research с источниками: дефолт pplx-max.py по подписке Max. Триггеры: «перплексити», «поищи в вебе с источниками».
/ai-gateways:kimi-reasoningГлубокий reasoning через Kimi (модель kimi-k3): алгоритмы, трудные баги, архитектура, математика. Триггеры: «спроси kimi». Агент-обёртка → kimi-algorithm-specialist.
gemini-agentGemini 3.1/3.0 tasks via AI Gateway — long context, multimodal, deep research, Google ecosystem
gpt-agentЗадачи семейства OpenAI через AI Gateway: GPT-6 Astra и линейка 5.6 — второе мнение против Claude, строгий JSON по схеме, function calling
kimi-algorithm-specialistExpert in algorithms, data structures, and computational optimization — deep reasoning via Kimi K2 for math and algorithmic problems
Phase-based dev framework: roadmaps, plans, execution, verification, debugging.
57 commands · 18 agents
Same content as video-media, fetched as a sparse git-subdir clone of this monorepo. Reference entry for the git-subdir source format - install either this or video-media, not both.
53 skills · 3 commands · 9 agents
Python/JS/TS dev, database design, API docs, build fix, git workflow, architecture agents.
17 skills · 16 commands · 10 agents
8-role production pipeline (brief to QC), generation (Runway), avatars (HeyGen/D-ID), edit, download, export, subtitles, transcripts.
31 skills · 3 commands · 9 agents
n8n, AWS, Telegram bots, Zoom, Pinecone, DeepL, Home Assistant, webhooks.
24 skills · 6 commands · 2 agents
Bug/cleanup/deps/reuse/security health audits, security audit, threat hunting, finding and vetting third-party skills before install.
9 skills · 6 commands · 12 agents
Claude API and SDK documentation skill for building LLM-powered applications
19 skills
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
2 skills · 2 commands · 2 agents · 1 MCP server
Security review for Claude-generated code. Pattern-based warnings on edits, LLM-powered diff review on Stop, and an agentic commit reviewer that catches injection, XSS, SSRF, hardcoded secrets, and 25+ other vulnerability classes.
hooks
agentic-flow (external: maintained in ruvnet/agentic-flow, pinned to commit d19737b, plugin 3.4.0): the agentic-flow MCP server pinned to [email protected] (ReasoningBank learning, ecosystem tools prompt_injection_scan, swarm_partition_tasks, sublinear_solve, sublinear_pagerank and ecosystem_status, multi-provider routing, autopilot learning; readonly profile by default, no tool pre-approved), 2 agents, 4 skills, /agentic-flow-status, and a mod guard on agentic_flow_agent with /agentic-flow-guard
4 skills · 1 command · 2 agents · 1 MCP server
Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.
1 skill
Query Trackio projects, runs, and metrics using the `trackio` CLI. Use when the user needs to list projects/runs/metrics, get summaries, or retrieve metric values from local Trackio databases. Supports both human-readable and JSON output formats. Covers project discovery, run inspection, metric querying, and system metrics. Designed for LLM agents and automation scripts.
1 skill
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