Provides a single MCP endpoint that lets AI coding agents search AWS docs, run sandboxed Python scripts, and make authenticated AWS API calls with enterprise guardrails like IAM condition keys, CloudWatch metrics, and CloudTrail auditing.
Terminal-native AI coding assistant optimized for the deepseek-v4 model. Provides configurable "thinking" modes and reasoning-intensity controls, agent skills for extensibility, MCP integration, and a shared config with a VSCode plugin.
Explains AI coding jargon in plain English, giving concrete engineering meanings for terms like context window, tool call, and attention degradation. Structured as a browsable dictionary with pragmatic examples and guidance for developers building LLM-driven systems.
Parses local AI coding-assistant session logs and presents a privacy-first dashboard that surfaces practice scores, anti-patterns, code-output metrics, skill discovery, and context-health checks. Runs as a VS Code extension or a GitHub Copilot canvas; requires building/installing the VSIX.
Applies an "ADHD-friendly" output style to coding assistants so answers lead with the next action, present numbered steps, and avoid burying results. Packaged as a reusable skill/plugin for coding-agent workflows (examples: Claude Code, Codex) and guided by a 10-rule style set.
Reviews Git diffs or entire files via a CLI that combines deterministic pipelines (precise file selection, bundling, rule matching) with an LLM agent to produce line-level review comments. Includes built-in security rules and integrations for multiple LLM providers, designed for CI and large changesets.
A GGUF-format 9B LLM fine-tuned for code generation and agentic tool-calling that uses Multi-Token Prediction (MTP) and draft heads to increase throughput and long-range planning. Intended for local inference and research/experimental coding workflows; Apache‑2.0 license.
Terminal-native AI coding agent that reads and edits code, runs shell commands, searches files, fetches web pages, and determines next steps from interactive feedback. Delivered as a single-binary TUI with video input, subagents, a plugin marketplace, and IDE (ACP) integration.
Runs an external, reviewable coding-agent harness that turns intent into repeatable software work: clarifies requirements, builds reviewed plans, executes in tmux-backed sessions, and collects durable verification. Ships Telegram/Discord delivery, a research REPL, and optional desktop-control tools; beta-stage.
Centralizes indexing and management of local AI coding-agent sessions so you can search, view full context, migrate, resume, and restore conversations across agents and devices. Supports extensible local sources, AI summaries, optional Supabase sync, and Skills management.
Measures how coding agents explore repositories by asking them to return a ranked, line-level list of code regions relevant to an issue under a fixed line budget. Covers 848 issues across 203 repos and 10 languages; evaluates coverage, ranking, and context-efficiency to isolate exploration quality.
Provides a locally runnable, quantized GGUF release of Gemma 4 12B fine-tuned for Python coding with chain-of-thought distilled from Composer 2.5 and supplemented by Fable 5. Multiple quant options for low‑VRAM setups and execution‑verified training traces. Not safety‑aligned; validate before production.