Generates complete Godot 4 projects from a natural-language game description: it designs the architecture, generates assets, writes C# code, runs the project, captures screenshots for visual QA, and iterates until a runnable game repo is produced. Requires API keys and Godot .NET.
Runs automated, parallel SEO audits inside Claude Code and emits prioritized, testable action plans across technical SEO, content quality (E‑E‑A‑T), Schema.org markup, AI-search (GEO/AEO), local and e-commerce SEO. Operates with 25 sub-skills and 18 specialist agents; optional MCP extensions add live data.
Provides cross-platform semantic memory for AI coding agents by turning human-editable Markdown logs into a rebuildable Milvus “shadow” index and syncing memories across plugins (Claude Code, OpenClaw, OpenCode, Codex). Supports progressive retrieval, hybrid dense+BM25+RRF search, smart deduplication, live sync, and local ONNX embeddings.
Provides a local MCP server that returns precise, symbol-level code (functions, classes, imports) via tree-sitter parsing so AI agents send only the bytes they need—commonly cutting code-reading token usage 95%+ and enabling compact packed responses for further savings.
Turns authorized ad-account exports or reads into dated, source-grounded audits, channel and budget plans, creative briefs, experiments, monitoring, and versioned JSON reports. Read-only by default; supports twelve ad platforms and drafts safe account changes behind capability, verification, and rollback gates.
Turns a single Claude Code session into a coordinated game-development studio by providing 49 specialized AI agents, 72 slash-command skills, automated hooks and path-scoped rules. Includes tiered roles, engine-specific agent sets (Godot/Unity/Unreal) and templates to keep design, QA and release in sync.
Lets any LLM operate a ComfyUI instance: generate and iterate images/video/audio, manage models and custom nodes, and edit the live graph in natural language. Local-first control plane with a sidebar agent, multi-provider LLM support, and installer packs for ready workflows.
Encodes production-grade engineering workflows (spec, plan, build, test, review, ship) as reusable "skills" so AI coding agents follow consistent development practices. Packaged as per-skill SKILL.md files and slash commands for integration with agents and CLIs. Suited for teams embedding engineering guardrails into agent-driven dev workflows.
Provides reusable “skill” instruction bundles that teach AI coding tools how to author, query, and operate Microsoft Fabric workloads via REST APIs, T-SQL, KQL and notebooks. Includes Copilot CLI/Claude/Cursor integrations, workload-focused bundles, and optional MCP configurations for live data access.
Provides portable agent 'skills' that steer code-generating agents toward higher-quality UI: stronger layout, typography, spacing and image-reference boards. Ships adjustable dials for design variance, motion and density and image→code pipelines for agent-led frontends.
Local-first session analytics for AI coding agents: discover, search, and track token usage and estimated costs across Claude Code, Codex, Forge and 20+ other agents. Single binary / desktop app that runs locally (no cloud accounts) with fast, SQLite-backed queries and optional PostgreSQL/DuckDB sync.
Dramatically reduces AI agents' context usage by sandboxing large tool outputs and indexing only relevant snippets into a searchable SQLite FTS5 (BM25) knowledge base, improving session continuity and privacy. Deploys cross-platform hooks and sandbox tools to cut context size by ~98% and avoid dumping raw logs into the model's window. ([github.com](https://github.com/mksglu/context-mode/blob/main/README.md?utm_source=openai))