ARGI [/ˈɑːr.dʒiː/]: Agent Runtime and Graph Intelligence 🚀
A best-practices template for AI-assisted development at scale. It turns your repository into institutional infrastructure where AI agents can work sustainably — converging around documentation as a stable attractor across sessions, long cycles, and multi-role collaboration
CLEAR Context OS is the maintenance layer your second brain never had: ownership boundaries enforced mechanically, staleness surfaced on a schedule, drift propagated across linked docs, a dispatcher that learns from your clicks. One source of truth per topic. Searchable. Task-aware.
Compact coding-agent context without summarizing it away. Verbatim, offline, with a receipt and recall for every cut. CLI, MCP server, Claude Code plugin. MIT.
Declarative framework for orchestrating multi-model Agentic pipelines with context engineering and quality gates.
Hyperdrive DCF (Design Cascading Framework) — a top-down methodology for rapid POC generation and idea validation, with every change tracked and synced back to the requirements spec with precision. Validated requirements then cascade through architecture and module specs to generate fully traced, test-gated production code. Powered by Claude Code.
Turn AI coding chats into a source-controlled workflow: AGENTS.md, rules, skills, verification gates, and adapters for Codex, Claude Code, and Cursor.
Knowledge as code for teams where agents implement: decisions and rules in markdown, approved by humans, checked in CI, and found by agents in seconds.
Open source, free, private, local, generative co-intelligence scaffold
Make every agent session start smarter than the last. A Claude Code skill for end-of-session knowledge maintenance.
Cheap, honest watchman for AI coding agents, by Shashikant. Catches stuck agent loops, suggests /clear or /compact when your work changes, and proves token savings with a randomized holdout. System 1 decision model, System 2 LLM, you decide. For Claude Code, GitHub Copilot, Cursor, Windsurf. In development.
CRUMB is the copy-paste AI handoff format. Switch AIs without losing the plot.
An evidence-driven runtime for AI coding agents, coordinating delegated exploration, context, and traceable evidence around the primary agent.
Version control for coding agents: decisions and dead ends anchored to code, plus token-budgeted context packs. Works with Claude Code, Codex, Gemini via MCP.
An Agent-safe context compressor for DeepSeek Harness. It semantically preserves critical tool outputs such as errors, file paths, JSON payloads and command results, instead of mechanically truncating the context.
Interactive RAG Context Ingestion & Chunking Diagnostics Workbench evaluating semantic coherence via Gemini 3.8 Flash.
Day 6: Memory Architectures - Context Engineering Workshop
Explicit-context synthesis for Obsidian: select exactly what the model sees, preserve source snapshots, and synthesize with OpenAI.
Local, deterministic MCP server for writing agents. Indexes InkOS/Markdown/TXT/EPUB into a rebuildable SQLite/FTS5 index and answers with SHA-256-verifiable evidence excerpts under token budgets. No LLM inside, never writes back.
Case study in LLM behaviour architecture, context engineering, failure analysis, and evaluation for long-context conversational AI systems.
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