Automates decompiling APK/AAR/JAR and extracting HTTP APIs — Retrofit endpoints, OkHttp calls, hardcoded URLs, and auth patterns — so you can document and reproduce an app's network surface without source code. Integrates jadx/Vineflower/Fernflower and scripts for call-flow tracing.
Collection of small, composable agent skills that extend LLM-based agents for planning, development, and tooling — installable via npx and designed to turn higher-level tasks (PRDs, TDD, refactors, triage) into reproducible agent actions.
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.
A collection of Markdown 'skills' that convert LLM-based agents into specialists for French administrative workflows — accounting, taxes, invoicing, notary work and audits. Ships agent-agnostic skills, Qonto/Stripe connectors, FEC output and 2026 e-invoicing guidance.
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.
Creates human-directed teams of AI agents (via GitHub Copilot) that live in your repo, persist knowledge, and coordinate development work. Key features: repo-first persistence, watch/triage automation, and an extensible CLI/SDK — alpha software, Copilot-dependent.
Turns natural-language directions into end-to-end video editing workflows: LLM-powered planning, media search/organization, ASR rough-cut, and reusable Style Skills for consistent storytelling. Integrates agent Skills (OpenClaw/Claude Code) and optional AIGC transitions.
A TypeScript framework for building programmable, headless autonomous agents with a harness-centric runtime. Includes an SDK and CLI, virtual sandboxes (just-bash) with optional full container sandboxes, provider-agnostic model settings, and connectors for CI/Daytona/MCP—suited for deployable agent runtimes.
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.
Autonomous white-box AI pentester for web apps and APIs. It reads your source code, maps the running app, then runs specialized agents that fire real proof-of-concept exploits for injection, XSS, SSRF, and auth flaws — reporting only what it can exploit.
Runs a persistent, self-modifying AI agent locally with durable identity, memory, and versioned history across tasks. Provides native desktop and headless CLI runtimes, coordinated subagent swarms, configurable remote or local GGUF models, and reviewed self-evolution via Git.