An open standard for capturing the WHY in git history

C.O.N.T.EX.T is designed to compress complex, multi-domain conversations into machine-optimized "Carry-Packets." These packets achieve a crystallization point of 0.15 entity/token, ensuring that a receiving model can reconstruct the original context with near-perfect fidelity.

Offline context handoff between coding agents. Read local histories into fresh sessions; source stores stay unchanged. Stdlib-only Python, not live session restore.

Claude Code skill for session handoffs — survives context compaction, chain-links across sessions.

(HAM) Memory system for AI coding agents. Cut token usage by 80% by scoping context to directories.

Living project docs for coding agents: keep guides, progress logs, change maps, and handoff context updated as your repo evolves.

Agent skills for coding CLIs, multi-agent runtimes, context engines, MCP extensions, and terminal tooling. Instead of using claude code's source code, give your agent skills to create your own!

Claude Code skills and workflows, optimized for context-efficiency and skill quality. Skills ranging from cloud infrastructure to design to advanced maths.

Hand Claude a PRD. Get a working feature back. One story per subagent, fresh context every time.

A Claude skill that writes the accurate prompts for any AI tool. Zero tokens or credits wasted. Full context and memory retention

Skills, prompts, and instructions for building AI agents on top of Dynatrace production context

A Claude Code skill that 10x's your effective context window by dispatching tasks to background AI workers.

Long-horizon agent skill for Claude Code / Cursor / Codex / Grok Build — multi-task ledger loop, host-portable, clean-context supervisor, verified gates. Markdown library (loop-graph), not a framework.

Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors

Re-anchor long conversations that drift through repeated local corrections.

Turn Claude Code into its own Meta-Harness — a skill that evolves the scaffolding around a fixed model (memory, retrieval, context, prompts) via a native propose→score→Pareto loop. Native reimplementation of Meta-Harness (Lee et al. 2026).

Optimized GitHub skill for coding agents: fewer tool calls, less context burned, lower cost, faster answers. One bounded call each for PR state, review threads, and CI failures.

An IOS Simulator Skill for ClaudeCode. Use it to optimise Claude's ability to build, run and interact with your apps, and to proxy xcodebuild to save token and context wastage.

Persistent memory for Claude Code — 3-5x longer sessions, 60-80% fewer wasted tokens. Branch-aware, self-healing, token-efficient.

Tinder for your Claude Code skills, subagents and MCP servers. Swipe away what wastes context, scan for prompt injection, get honest token costs. Fixes what it finds and actually deletes. Zero dependencies, Claude Code + Codex.

You.com skills and plugins for web search, content extraction, research, finance, and integration discovery, helping AI agents build with up-to-date web context.

13 installable skills for Claude Code, OpenAI Codex, and Hermes, for finding your unknowns before they get expensive: blindspot pass, brainstorms, interviews, references, plans, notes, pitches, a merge quiz, plus a context audit, agent interface design, and progressive disclosure.

AI agent skills for building, operating and troubleshooting Apache Kafka applications. Topic audit, consumer lag, schema review, security, connectors and DLQ

Agent Skills for Meta Quest/Horizon OS VR Development