Extracts local chat logs, code context, diffs, and tool outputs from AI coding assistants and exports them as ML-ready JSONL. Auto-discovers common storage locations and handles SQLite/JSONL formats; scan extracted files for secrets before sharing.
Packages Hugging Face ML tasks—dataset creation, model training, evaluation, Hub ops, Spaces deployment—as portable Agent Skills. Each is a SKILL.md folder agents load on demand, running unchanged across Claude Code, Codex, Gemini CLI, and Cursor.
Fifteen reusable agent skills for curating LLM context windows, treating attention decay—not token capacity—as the real constraint. A routing layer benchmarked at 0.92 top-1 accuracy selects the right skill for each task.
Intercepts and blocks destructive git, filesystem and CLI commands before they execute when run by AI coding agents. Offers sub-millisecond hook latency, 50+ modular rule packs, heredoc/inline-script AST scanning, agent-specific integrations and configurable bypass/allow-once workflows.
Provides an installable library of 1,340+ SKILL.md playbooks for AI coding assistants, with an installer CLI, bundles, workflows and plugin-friendly distributions for Claude Code, Cursor, Codex, Gemini CLI and more.
Provides a desktop app and an MCP endpoint to share AI skills, plugins, and connected services across agents and teams. Includes a local-first workspace for macOS/Windows/Linux, an MCP that integrates with Codex/Claude/Cursor, and an org control plane for publishing capabilities and managing access.
A curated, security-first registry of verified, tested skills you can install into AI coding agents. Each skill is human-curated, scanned (Snyk/static analysis), and integrity-locked; delivered via a CLI and optional MCP server to multiple agents (Claude Code, Cursor, Copilot, etc.).
Provides a manifest-driven marketplace of official Cursor plugins for developer workflows and agent integrations. Each plugin lives in its own directory with a .cursor-plugin manifest; examples include agent skills, PR review canvases, SDK integrations, CI/team tooling, and orchestration for parallel agent work.
Improves Claude Code's coding behavior with a single CLAUDE.md that prescribes four practical rules—Think Before Coding, Simplicity First, Surgical Changes, and Goal-Driven Execution—to reduce LLM assumptions, overengineering, and unrelated edits.
A curated collection of reusable 'skills' that let LLM-driven coding agents perform common .NET/C# tasks — build diagnosis, debugging, testing, data access, upgrades, MAUI, and AI/ML workflows. Implements the Agent Skills standard and is published for agent marketplaces (Copilot CLI, Claude Code, Cursor).
Equips AI coding agents with reusable AWS skills (deployment, serverless, Amplify, SageMaker) by packaging agent skills, MCP servers, hooks, and references so agents invoke vetted workflows instead of bloating prompts.
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.