# Awesome Loop Engineering v0.7.0

Awesome Loop Engineering v0.7.0 turns the implementation kit into a clear path from a recurring problem to a validated contract and a working runtime starter.

The collection now maps 545 sources across the operating layer that discovers work, delegates it, verifies results, persists state, and decides what happens next.

## What Is Included

- 545 source-audited resources linked to canonical works
- 20 operational patterns organized by build, operate, optimize, and govern use cases
- 20 schema-validated loop contracts, one for every pattern
- 8 runtime starters: 3 dependency-light executables and 5 copy/paste runtime templates
- an interactive Resource Atlas for filtering by goal, lifecycle stage, artifact type, and evidence class
- CSV and JSONL exports mirrored as a Hugging Face dataset
- 8 language entry points

## What Changed Since v0.6.0

- Added five distinct operational patterns: benchmark optimization, accessibility regression, knowledge freshness, performance regression, and authorized adversarial red teaming.
- Added a schema-valid contract and worked scenario for every new pattern.
- Reorganized the pattern library into four operating domains with a symptom, verified outcome, and guidance for choosing between similar loops.
- Rebuilt the contract catalog around the questions implementers actually need: when to use a loop, what triggers it, which deterministic gate decides done, and what receipt survives.
- Added four end-to-end worked paths for CI repair, knowledge refresh, queue processing, and read-only threshold monitoring.
- Added two executable starters: a JSONL queue worker with idempotent state and a read-only threshold monitor with bounded polling and evidence-backed escalation.
- Clarified that the starter library contains three executables and five copy/paste runtime templates, avoiding an unsupported claim that every artifact is a standalone program.
- Updated the website, social preview, translations, release metadata, and Hugging Face dataset to the same counts.

## Why This Matters

A resource list explains what exists. An implementation kit should also help a reader act.

The v0.7.0 path is explicit:

1. Name the recurring problem.
1. Choose an operational pattern.
1. Adapt its validated contract.
1. Select a runtime starter.
1. Let external evidence, durable state, a hard budget, and human escalation govern the loop.

The goal remains bounded, reviewable, evidence-driven repetition, not unlimited autonomy.

## Explore And Reuse

- [Explore the Resource Atlas](https://chaoyue0307.github.io/awesome-loop-engineering/#resources)
- [Choose an operational pattern](https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/README.md)
- [Adapt a validated contract](https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/README.md)
- [Run a starter](https://github.com/ChaoYue0307/awesome-loop-engineering/tree/main/examples/runnable)
- [Use the Hugging Face dataset](https://huggingface.co/datasets/cy0307/awesome-loop-engineering)
- [Contribute a source or correction](https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/CONTRIBUTING.md)

Corrections are especially valuable. If a summary is inaccurate or a stronger canonical source exists, use the annotation-correction form or open a pull request.

## Repository

[github.com/ChaoYue0307/awesome-loop-engineering](https://github.com/ChaoYue0307/awesome-loop-engineering)