Agent harness for long-running AI coding tasks — orchestrates Claude Code & GitHub Copilot across repositories 🍩

A framework for executing long-running AI agent tasks with structured feature lists and progress tracking.

Java-native runtime for long-running AI agents with live execution control, human approvals, and audit trails.

Production 3-agent harness for autonomous multi-hour software builds. Planner + Generator + Evaluator with parallel fleet execution, circuit-breaker stagnation detection, and graceful resume.

watches the watchers: a monitoring system for long-running Claude Code agents

Codex-derived source release for an opt-in session compact route that preserves durable handoff state across repeated compactions.

Codex skill for designing and scaffolding durable agent harness projects, with a Ralph Loop preset and upgrade-friendly doctrine.

Continuity for AI agent work that outgrows one chat.

Claude Code plugin for long-running agent workflows with progress tracking, feature checklists, and git checkpoints

Evidence-bound workflow diagnostics and certified lower-bound reporting for long-running AI agent pipelines. Improve agent workflow throughput without changing the model.

Production-ready workspace setup for long-running OpenClaw AI agents. Artifact workflow, secrets management, memory optimization, and battle-tested patterns.

Theory-to-experiment lab for search stability in long-running agents under finite context, with exact simulator tests and lightweight mechanistic probe tasks.

Observable-only workflow memory for long-running agents: promotes raw short-term traces into verified, receipt-bound workflow memory without relying on hidden meta-evaluators.

🤖 Agent Skills compliant skill for autonomous AI agents that parse PRDs into tasks and execute them. Works with Cursor, OpenCode, Claude & any AI framework. Features state persistence, dependency management, error recovery.

Pi extension that gives coding agents persistent /goal workflows with branch-aware state, source imports, progress tools, and explicit start handoffs.

Personal website of Iris Shen, focused on memory, evaluation, orchestration, and runtime systems for long-running AI agents.

Local-first, model-agnostic workflow optimizer for long-running AI agents: observable JSONL ledgers, deterministic reducers, no-meta gates, and receipt-backed self-improvement without LLM judges or model-weight updates.

Certified Memory Governance Layer for long-running AI agents: strict receipts, append-only ledgers, authority gates, retrieval filtering, telemetry replay, and safe adapters for Mem0, Graphiti, LangMem, and LangGraph.