Sync 968-resource release from GitHub

README.de.md

@@ -28,7 +28,7 @@ Ein Loop entdeckt Arbeit, übergibt sie an einen oder mehrere Agenten, prüft da
 
 Loop Engineering umfasst wiederkehrende KI-Agenten- und Coding-Agent-Systeme mit expliziten Auslösern, Verifikation und dauerhaftem Zustand. Software-Event-Loops, Regelungstechnik, Growth Loops, generische Automatisierung und nicht-KI-bezogene Feedback-Loops gehören nicht dazu.
 
-Starte mit 956 Ressourcen, 22 operativen Loop-Patterns, 22 schemavalidierten Loop-Contracts und 8 Runtime-Startern (3 ausführbare Programme und 5 anpassbare Vorlagen), ergänzt durch eine Community-Galerie und 8 Sprachen.
+Starte mit 968 Ressourcen, 22 operativen Loop-Patterns, 22 schemavalidierten Loop-Contracts und 8 Runtime-Startern (3 ausführbare Programme und 5 anpassbare Vorlagen), ergänzt durch eine Community-Galerie und 8 Sprachen.
 
 ## Mentales Modell
 

README.es.md

@@ -28,7 +28,7 @@ Un loop descubre trabajo, lo delega a uno o más agentes, verifica el resultado,
 
 Loop Engineering abarca sistemas recurrentes de agentes de IA y coding agents con disparadores explícitos, verificación y estado duradero. No incluye event loops de software, teoría de control, growth loops, automatización genérica ni feedback loops no relacionados con IA.
 
-Empieza con 956 recursos, 22 patrones operativos, 22 loop contracts validados por esquema y 8 puntos de partida de runtime (3 ejecutables y 5 plantillas listas para adaptar), además de una galería comunitaria y 8 idiomas.
+Empieza con 968 recursos, 22 patrones operativos, 22 loop contracts validados por esquema y 8 puntos de partida de runtime (3 ejecutables y 5 plantillas listas para adaptar), además de una galería comunitaria y 8 idiomas.
 
 ## Modelo Mental
 

README.fr.md

@@ -28,7 +28,7 @@ Un loop découvre du travail, le délègue à un ou plusieurs agents, vérifie l
 
 Loop Engineering couvre les systèmes récurrents d'agents IA et de coding agents avec des déclencheurs explicites, une vérification et un état durable. Il n'inclut ni les event loops logiciels, ni la théorie du contrôle, ni les growth loops, ni l'automatisation générique, ni les feedback loops sans rapport avec l'IA.
 
-Commencez avec 956 ressources, 22 patterns opérationnels, 22 loop contracts validés par schéma et 8 points de départ d'exécution (3 exécutables et 5 modèles prêts à adapter), ainsi qu'une galerie communautaire et 8 langues.
+Commencez avec 968 ressources, 22 patterns opérationnels, 22 loop contracts validés par schéma et 8 points de départ d'exécution (3 exécutables et 5 modèles prêts à adapter), ainsi qu'une galerie communautaire et 8 langues.
 
 ## Modèle Mental
 

README.ja.md

@@ -28,7 +28,7 @@ Loop は作業を発見し、1 つ以上の agents に委任し、結果を確
 
 Loop Engineering は、明示的なトリガー、検証、永続状態を備えた反復型 AI agent / coding agent システムを対象とします。software event loop、制御理論、growth loop、一般的な workflow automation、非 AI の feedback loop は含みません。
 
-956 件の監査済みリソース、22 個の運用パターン、22 個の schema 検証済み loop contract、8 個の runtime starter（3 個の実行ファイルと 5 個の適応可能なテンプレート）から始められます。コミュニティ gallery と 8 言語の導入も利用できます。
+968 件の監査済みリソース、22 個の運用パターン、22 個の schema 検証済み loop contract、8 個の runtime starter（3 個の実行ファイルと 5 個の適応可能なテンプレート）から始められます。コミュニティ gallery と 8 言語の導入も利用できます。
 
 ## メンタルモデル
 

README.ko.md

@@ -28,7 +28,7 @@ Loop 는 작업을 발견하고, 하나 이상의 agents 에게 위임하고,
 
 Loop Engineering 은 명시적 트리거, 검증, 지속 상태를 갖춘 반복 AI agent / coding agent 시스템을 다룹니다. software event loop, control theory, growth loop, 일반적인 workflow automation, 비 AI feedback loop 는 포함하지 않습니다.
 
-956개의 감사된 리소스, 22개의 운영 loop 패턴, 22개의 스키마 검증 loop contract, 8개의 runtime starter(실행 파일 3개와 적용 가능한 템플릿 5개)로 바로 시작할 수 있습니다. 커뮤니티 gallery 와 8개 언어 안내도 제공합니다.
+968개의 감사된 리소스, 22개의 운영 loop 패턴, 22개의 스키마 검증 loop contract, 8개의 runtime starter(실행 파일 3개와 적용 가능한 템플릿 5개)로 바로 시작할 수 있습니다. 커뮤니티 gallery 와 8개 언어 안내도 제공합니다.
 
 ## 멘탈 모델
 

README.pt-BR.md

@@ -28,7 +28,7 @@ Um loop descobre trabalho, delega para um ou mais agentes, verifica o resultado,
 
 Loop Engineering abrange sistemas recorrentes de AI agents e coding agents com gatilhos explícitos, verificação e estado durável. Não inclui event loops de software, teoria de controle, growth loops, automação genérica nem feedback loops sem relação com IA.
 
-Comece com 956 recursos, 22 patterns operacionais, 22 loop contracts validados por schema e 8 starters de runtime (3 executáveis e 5 templates prontos para adaptação), além de uma galeria comunitária e 8 idiomas.
+Comece com 968 recursos, 22 patterns operacionais, 22 loop contracts validados por schema e 8 starters de runtime (3 executáveis e 5 templates prontos para adaptação), além de uma galeria comunitária e 8 idiomas.
 
 ## Modelo Mental
 

README.zh-CN.md

@@ -32,7 +32,7 @@ Prompt engineering 改进你对模型说什么。Context engineering 改进模
 
 Loop Engineering 专指具备明确触发、外部验证和持久状态的可重复 AI-agent 与 coding-agent 系统，不包括软件事件循环、控制论、增长循环、通用 workflow automation 或非 AI feedback loop。
 
-可直接从 956 篇论文、官方文档、工具、benchmark 与实践指南，22 个操作模式、22 个经 schema 校验的 loop contracts 和 8 个 runtime starters（3 个可直接执行，5 个可复制改造）开始，并通过社区 gallery 和 8 种语言入口继续探索。
+可直接从 968 篇论文、官方文档、工具、benchmark 与实践指南，22 个操作模式、22 个经 schema 校验的 loop contracts 和 8 个 runtime starters（3 个可直接执行，5 个可复制改造）开始，并通过社区 gallery 和 8 种语言入口继续探索。
 
 ## 一句话定位
 

assets/MEDIA_KIT.md

@@ -14,11 +14,11 @@ The original 1200x630 cover presents Loop Engineering as the operating layer abo
 
 ### One Sentence
 
-Awesome Loop Engineering is a field guide and implementation kit for recurring AI-agent systems, connecting 956 resources to 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.
+Awesome Loop Engineering is a field guide and implementation kit for recurring AI-agent systems, connecting 968 resources to 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.
 
 ### Short Paragraph
 
-Awesome Loop Engineering maps how recurring AI agents discover work, act with scoped tools, pass independent verification, preserve state, and decide whether to retry, hand off, or stop. Readers can explore 956 papers, official docs, tools, benchmarks, and guides, then build from 22 patterns, 22 schema-checked contracts, and 8 runtime starters.
+Awesome Loop Engineering maps how recurring AI agents discover work, act with scoped tools, pass independent verification, preserve state, and decide whether to retry, hand off, or stop. Readers can explore 968 papers, official docs, tools, benchmarks, and guides, then build from 22 patterns, 22 schema-checked contracts, and 8 runtime starters.
 
 ### What Distinguishes It
 

data/README.md

@@ -1,6 +1,6 @@
 # Dataset Exports
 
-Download all 956 resources as deterministic tabular exports.
+Download all 968 resources as deterministic tabular exports.
 
 - `resources.csv` - Tabular export for spreadsheets and ad hoc analysis.
 - `resources.jsonl` - JSON Lines export and source for the Hugging Face Parquet build.

data/arxiv_publication_audit.csv

@@ -1,5 +1,7 @@
 row_id,arxiv_id,resource_title,arxiv_title,arxiv_year,status,published_title,publication_date,publication_year,publication_venue,publisher,doi,published_url,record_url,metadata_source,match_score,checked_on
 ale-0023,2607.14890,"Proof-or-Stop: Don't Trust the Agent, Trust the Evidence -- Loop Engineering for Verifiable Evidence-Gated Lifecycle Control","Proof-or-Stop: Don't Trust the Agent, Trust the Evidence -- Loop Engineering for Verifiable Evidence-Gated Lifecycle Control",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
+ale-0076,2601.08815,Agent Contracts: A Formal Framework for Resource-Bounded Autonomous AI Systems,Agent Contracts: A Formal Framework for Resource-Bounded Autonomous AI Systems,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
+ale-0077,2607.03702,Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry,Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0108,2210.03629,ReAct: Synergizing Reasoning and Acting in Language Models,ReAct: Synergizing Reasoning and Acting in Language Models,2023,published,ReAct: Synergizing Reasoning and Acting in Language Models,2023,2023,International Conference on Learning Representations (ICLR),International Conference on Learning Representations,,https://openreview.net/forum?id=WE_vluYUL-X,https://openreview.net/forum?id=WE_vluYUL-X,OpenReview proceedings record,1.000,2026-07-17
 ale-0109,2303.11366,Reflexion: Language Agents with Verbal Reinforcement Learning,Reflexion: Language Agents with Verbal Reinforcement Learning,2023,published,Reflexion: Language Agents with Verbal Reinforcement Learning,2023,2023,Advances in Neural Information Processing Systems 36 (NeurIPS),Neural Information Processing Systems Foundation,10.52202/075280-0377,https://proceedings.neurips.cc/paper_files/paper/2023/hash/1b44b878bb782e6954cd888628510e90-Abstract-Conference.html,https://doi.org/10.52202/075280-0377,NeurIPS proceedings and DOI records,1.000,2026-07-17
 ale-0110,2303.17651,Self-Refine: Iterative Refinement with Self-Feedback,Self-Refine: Iterative Refinement with Self-Feedback,2023,published,Self-Refine: Iterative Refinement with Self-Feedback,2023,2023,Advances in Neural Information Processing Systems 36 (NeurIPS),Neural Information Processing Systems Foundation,,https://proceedings.neurips.cc/paper_files/paper/2023/hash/91edff07232fb1b55a505a9e9f6c0ff3-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2023/hash/91edff07232fb1b55a505a9e9f6c0ff3-Abstract-Conference.html,NeurIPS proceedings record,1.000,2026-07-17
@@ -186,6 +188,8 @@ ale-0443,2607.27443,Leveraging Trajectory Graphs for Pre-Execution Error Diagnos
 ale-0444,2607.28609,OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models,OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0445,2607.28271,Agentic Method for Deterministic Validation of Legacy Code Migration,Agentic Method for Deterministic Validation of Legacy Code Migration,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0446,2607.27849,"Safety-Gated Agentic Supervisory Control on a Coupled Distillation Benchmark: Regime Map, Auditable Gate, and Co-Design Findings","Safety-Gated Agentic Supervisory Control on a Coupled Distillation Benchmark: Regime Map, Auditable Gate, and Co-Design Findings",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
+ale-0458,2608.11772,Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction,Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
+ale-0459,2606.04990,From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents,From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0300,2607.05189,When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0301,2607.05029,Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0302,2607.02514,Distributed Attacks in Persistent-State AI Control,Distributed Attacks in Persistent-State AI Control,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
@@ -229,10 +233,10 @@ ale-0424,2607.19837,Know Your Agent: Reconnaissance-Driven Pentesting of AI Agen
 ale-0425,2607.19433,The Chronos Vulnerability: Temporal Persistence and Memory-Based Deception in Agentic AI,The Chronos Vulnerability: A Taxonomy of Temporal Persistence and Memory-Based Deception in Agentic AI,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-23
 ale-0439,2607.20759,IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests,IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-24
 ale-0440,2607.20827,Auditing Provenance Sensitivity in LLM Agent Action Selection,Auditing Provenance Sensitivity in LLM Agent Action Selection,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-24
-ale-0441,2607.21325,"Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation","Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-24
+ale-0524,2607.21325,"Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation",Cryptographically verifiable authorization for autonomous AI agents: A falsifiable hypothesis and proof-of-concept,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0450,2607.20891,Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions,Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-25
 ale-0451,2607.21518,"Same Dangerous Objective, Opposite Advice: Direct Exposure versus Multi-Agent Mediation","Same Dangerous Objective, Opposite Advice: Direct Exposure versus Multi-Agent Mediation",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-25
-ale-0482,2607.23999,ContainmentBench: Trace-Based Evaluation of Post-Injection Containment in Tool-Using LLM Agents,ContainmentBench: Trace-Based Evaluation of Post-Injection Containment in Tool-Using LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
+ale-0535,2607.23999,ContainmentBench: Trace-Based Evaluation of Post-Injection Containment in Tool-Using LLM Agents,ContainmentBench: Trace-Based Evaluation of Post-Exposure Containment in Tool-Using LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0483,2607.24625,Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents,Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
 ale-0484,2607.22868,What Can Be Enforced? A Theory of Certified Runtime Safety for Tool-Using Agents,What Can Be Enforced? A Theory of Certified Runtime Safety for Tool-Using Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
 ale-0485,2607.23586,Are You Still the Agent I Authorized? Earned Authority under a Fixed Ceiling for Evolving Agents,Are You Still the Agent I Authorized? Earned Authority under a Fixed Ceiling for Evolving Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
@@ -256,6 +260,8 @@ ale-0547,2607.27294,AgentS4D: Benchmarking Runtime Risks across the Execution Li
 ale-0548,2607.28103,MIND: Lightweight and Effective Memory Injection Defense for LLM Agents via Intent-Aware Information Bottleneck,MIND: Lightweight and Effective Memory Injection Defense for LLM Agents via Intent-Aware Information Bottleneck,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0549,2607.27636,HALO: Heterogeneous Admission through Localized Obligations for Safe Agentic Execution,HALO: Heterogeneous Admission through Localized Obligations for Safe Agentic Execution,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0551,2607.26314,StealthBench: Measuring Operational Stealth in Autonomous Offensive-Security Agents,StealthBench: Measuring Operational Stealth in Autonomous Offensive-Security Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-07
+ale-0565,2605.05846,LoopTrap: Termination Poisoning Attacks on LLM Agents,LoopTrap: Termination Poisoning Attacks on LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
+ale-0566,2605.06812,Towards Security-Auditable LLM Agents: A Unified Graph Representation,Towards Security-Auditable LLM Agents: A Unified Graph Representation,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0345,2601.12030,ARC: Active and Reflection-driven Context Management for Long-Horizon Agents,ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,2026,published,ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,2026,2026,Findings of the Association for Computational Linguistics: ACL,Association for Computational Linguistics,10.18653/v1/2026.findings-acl.930,https://aclanthology.org/2026.findings-acl.930/,https://doi.org/10.18653/v1/2026.findings-acl.930,ACL Anthology and DOI records,1.000,2026-07-17
 ale-0346,2603.07670,"Memory for Autonomous LLM Agents: Mechanisms, Evaluation, and Emerging Frontiers","Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0347,2604.08224,"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
@@ -321,6 +327,8 @@ ale-0640,2607.27958,Σ-Mem: An Online Reliability Memory for LLM-based Multi-Age
 ale-0643,2607.26784,SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution,SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-07
 ale-0651,2607.01935,A-TMA: Decoupling State-Aware Memory Failures in Long-Term Agent Memory,A-TMA: Decoupling State-Aware Memory Failures in Long-Term Agent Memory,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-10
 ale-0652,2605.25535,Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents,Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-10
+ale-0661,2607.00151,SmoothAgent: Efficient Long-Horizon LLM-Based Agent Serving with Lookahead Context Engineering,SmoothAgent: Efficient Long-Horizon LLM-Based Agent Serving with Lookahead Context Engineering,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
+ale-0662,2512.05470,Everything is Context: Agentic File System Abstraction for Context Engineering,Everything is Context: Agentic File System Abstraction for Context Engineering,2025,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0396,2604.11378,From Agent Loops to Structured Graphs: A Scheduler-Theoretic Framework for LLM Agent Execution,From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0398,2603.11445,Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework,Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,2026,published,Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,2026,2026,ICLR Workshop on Multi-Agent Learning: Generalization and Adaptation in Intelligence (MALGAI),International Conference on Learning Representations,,https://openreview.net/forum?id=WUmz4LUbvU,https://openreview.net/forum?id=WUmz4LUbvU,ICLR workshop OpenReview record,1.000,2026-07-17
 ale-0399,2603.22386,From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
@@ -402,7 +410,7 @@ ale-0639,2607.20926,SciExplore: Evaluating Autonomous Agents from Scientific Nav
 ale-0640,2607.21447,RUMBA: Russian User Memory Benchmark,RUMBA: Russian User Memory Benchmark,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-25
 ale-0693,2607.22368,Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI,Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
 ale-0694,2607.24054,Success Is Not Self-Explanatory: Auditing Success Provenance in Agent Evaluation,Success Is Not Self-Explanatory: Auditing Success Provenance in Agent Evaluation,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
-ale-0695,2607.22015,Are Production Cloud Skills Adequately Tested? Measuring and Governing Skill Test Coverage in Practice,Are Production Cloud Skills Adequately Tested? Measuring and Governing Skill Test Coverage in Practice,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
+ale-0804,2607.22015,Are Production Cloud Skills Adequately Tested? Measuring and Governing Skill Test Coverage in Practice,Are Production Cloud Skills Adequately Tested? Measuring and Governing Skill Test Adequacy in Practice,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0746,2607.23332,AlloBench: Measuring Online Tool Allocation Capability in LLM Agents,AllocBench: Measuring Online Tool Allocation Capability in LLM Agents,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-04
 ale-0697,2607.23123,SQBench: A Benchmark for Evaluating Task Delivery by Language-Model Agents in Production-Oriented Workflows,SQBench: A Benchmark for Evaluating Task Delivery by Language-Model Agents in Production-Oriented Workflows,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
 ale-0698,2607.23722,E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios,E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-29
@@ -427,6 +435,7 @@ ale-0803,2607.27929,Meta-Task: Turning Terminal Task Synthesis into a Terminal T
 ale-0821,2605.27922,Harness-Bench: Measuring Harness Effects Across Models in Realistic Agent Workflows,Harness-Bench: Measuring Harness Effects across Models in Realistic Agent Workflows,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-10
 ale-0822,2602.22769,AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications,AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-10
 ale-0823,2604.20006,From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents,From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents,2026,published,From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents,2026,2026,Findings of the Association for Computational Linguistics: ACL 2026,Association for Computational Linguistics,10.18653/v1/2026.findings-acl.1337,https://doi.org/10.18653/v1/2026.findings-acl.1337,https://doi.org/10.18653/v1/2026.findings-acl.1337,Crossref API + DOI record,1.000,2026-08-10
+ale-0834,2604.12162,AlphaEval: Evaluating Agents in Production,AlphaEval: Evaluating Agents in Production,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0482,2607.07052,"Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows","Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0483,2607.08010,Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0485,2607.07689,Agent Delivery Engineering Predictive Reliability Framework,Agent Delivery Engineering Predictive Reliability Framework,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
@@ -443,6 +452,7 @@ ale-0773,2605.01604,"Evaluating Agentic AI in the Wild: Failure Modes, Drift Pat
 ale-0831,2607.28802,Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures,Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0832,2607.27677,Stop Shipping AI Agents on Faith: Capability Is Not Production Readiness,Stop Shipping AI Agents on Faith: Capability Is Not Production Readiness,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
 ale-0833,2607.28317,"One Human, N Agents: Audit-Budget Allocation for LLM Agent Fleets under Miscalibrated, Correlated Confidence","One Human, $N$ Agents: Audit-Budget Allocation for LLM Agent Fleets under Miscalibrated, Correlated Confidence",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-05
+ale-0867,2606.01581,"Agent System Operations: Categorization, Challenges, and Future Directions","Agent System Operations: Categorization, Challenges, and Future Directions",2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-08-13
 ale-0509,2606.17799,Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0510,2603.23994,Understanding the Challenges in Iterative Generative Optimization with LLMs,Understanding the Challenges in Iterative Generative Optimization with LLMs,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17
 ale-0511,2606.13003,The Illusion of Multi-Agent Advantage,The Illusion of Multi-Agent Advantage,2026,preprint-only,,,,,,,,,DBLP and Crossref exact-title audit,,2026-07-17

data/first_seen.json

@@ -405,7 +405,6 @@
   "https://leodemoura.github.io/blog/2026-8-1-postmortem-for-kernel-soundness-bug-14576/": "2026-08-05",
   "https://research.jfrog.com/post/sqlite-critical-cves-or-llm-slops/": "2026-08-05",
   "https://gruhn.me/blog/2026-08-03/": "2026-08-05",
-  "https://github.com/0xwilliamortiz/ratchet": "2026-08-05",
   "https://github.com/disler/super-simple-software-factory": "2026-08-05",
   "https://github.com/DannyMac180/sol-advisor": "2026-08-05",
   "https://arxiv.org/abs/2604.27202": "2026-08-05",
@@ -470,5 +469,18 @@
   "https://arxiv.org/abs/2604.20006": "2026-08-10",
   "https://arxiv.org/abs/2605.25535": "2026-08-10",
   "https://www.diagrid.io/blog/checkpoints-are-not-durable-execution-why-langgraph-crewai-google-adk-and-others-fall-short-for-production-agent-workflows": "2026-08-10",
-  "https://zenity.io/blog/current-events/ai-agent-database-deletion-pocketos": "2026-08-10"
+  "https://zenity.io/blog/current-events/ai-agent-database-deletion-pocketos": "2026-08-10",
+  "https://arxiv.org/abs/2601.08815": "2026-08-13",
+  "https://arxiv.org/abs/2605.05846": "2026-08-13",
+  "https://arxiv.org/abs/2608.11772": "2026-08-13",
+  "https://arxiv.org/abs/2607.03702": "2026-08-13",
+  "https://arxiv.org/abs/2606.04990": "2026-08-13",
+  "https://arxiv.org/abs/2605.06812": "2026-08-13",
+  "https://arxiv.org/abs/2606.01581": "2026-08-13",
+  "https://arxiv.org/abs/2604.12162": "2026-08-13",
+  "https://arxiv.org/abs/2607.00151": "2026-08-13",
+  "https://arxiv.org/abs/2512.05470": "2026-08-13",
+  "https://devblogs.microsoft.com/dotnet/durable-workflows-in-microsoft-agent-framework/": "2026-08-13",
+  "https://docs.langchain.com/oss/python/deepagents/context-engineering": "2026-08-13",
+  "https://cloud.google.com/blog/topics/developers-practitioners/a-methodical-approach-to-agent-evaluation": "2026-08-13"
 }

data/resources.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:87a4303ac944f4194fa3392a95d6c60b25ea784d8b07bf17c8c2f806892e897a
-size 879966
+oid sha256:4c844da8182c578a223d3deed34b053430e10f72bcbc5a309af345618c1d9717
+size 894931

design-qa.md

@@ -77,8 +77,8 @@
 - Phone: 390 x 844, no horizontal overflow. The compact loop keeps all six stations, the moving work packet, legend, outcome key, and stage selector visible without crossing the hero copy.
 - Mobile navigation: opens all nine project links, reports `aria-expanded="true"`, closes on Escape, and restores focus to the menu button.
 - Pattern filter: `accessibility` returns exactly one of the 22 patterns.
-- Resource Atlas: remains idle above the fold, loads on approach or a direct resource anchor, and reports `956 of 956 resources | showing 8` on a fresh mobile load.
-- Resource interactions: the Model loop-layer filter returns 31 of 956 resources (30 papers plus Awesome Loop Models), paginates eight at a time on mobile, and renders Loopie and LoopWM with their 2026 arXiv records and adjacent-scope labels.
+- Resource Atlas: remains idle above the fold, loads on approach or a direct resource anchor, and reports `968 of 968 resources | showing 8` on a fresh mobile load.
+- Resource interactions: the Model loop-layer filter returns 31 of 968 resources (30 papers plus Awesome Loop Models), paginates eight at a time on mobile, and renders Loopie and LoopWM with their 2026 arXiv records and adjacent-scope labels.
 - Resource row schema: desktop exposes Work, Year, Published at, and Evidence; mobile stacks the same labels. A `ReasoningBank` query returns one row with its ICLR venue, arXiv identifier, Tier A evidence, task fit, and source record without horizontal overflow.
 - Scene motion: the canvas frame counter advanced from 640 to 662 over 900 ms. Two canvas crops taken 1.2 seconds apart changed 17.79% of sampled RGB channels.
 - Scene pixels: the current desktop canvas has 7,062 colors with RGB standard deviations of 35.93, 29.76, and 22.29; mobile has 5,755 colors with deviations of 40.73, 30.54, and 19.70. Both renders are nonblank and well contrasted.
@@ -86,8 +86,8 @@
 - Future directions: direct-anchor restoration waits for the Resource Atlas reflow, all three audience tracks remain readable, and the agenda CTA is fully visible at desktop and mobile widths.
 - Console: no page-origin errors or warnings during mobile navigation, pattern filtering, and Resource Atlas interactions.
 - Narrow phone: 320 x 844, document width equals viewport width; the headline stays within 16 px gutters and the Three.js canvas remains fully inside the 288 px content width.
-- Source audit: 956 rows checked; 899 public sources reachable, 6 access-restricted, 51 repository-native, and 0 broken or unreachable as of 2026-08-10 UTC.
-- Data and copy: the website, README, translations, social preview source, release copy, and Hugging Face card all report 956 resources, 22 patterns, 22 contracts, 8 runtime starters, and version 0.9.0. The dataset exposes 50 fields, including `loop_layer` and `scope_fit`.
+- Source audit: 968 rows checked; 913 public sources reachable, 4 access-restricted, 51 repository-native, and 0 broken or unreachable as of 2026-08-13 UTC.
+- Data and copy: the website, README, translations, social preview source, release copy, and Hugging Face card all report 968 resources, 22 patterns, 22 contracts, 8 runtime starters, and version 0.9.0. The dataset exposes 50 fields, including `loop_layer` and `scope_fit`.
 - Semantic scene pass: the desktop hero crop paints 14.61% of pixels beyond the paper background with a 254.71 luminance range; the desktop stack paints 27.83% with a 249.98 range; the mobile hero paints 20.84% with a 229.45 range.
 - Stage interaction: selecting Verify updates `aria-pressed` across all six controls and replaces the live detail with the independent evidence-gate explanation.
 - Progressive enhancement: desktop loads the agent-loop and engineering-stack canvases; mobile loads only the agent-loop canvas and exposes the four-layer text stack. Both target viewports have zero horizontal overflow and no console messages.

docs/index.html

@@ -4,7 +4,7 @@
     <meta charset="utf-8">
     <meta name="viewport" content="width=device-width, initial-scale=1">
     <title>Awesome Loop Engineering</title>
-    <meta name="description" content="Explore 956 resources from model recurrence to governed agent operations, then build with 22 patterns, 22 contracts, and 8 runtime starters.">
+    <meta name="description" content="Explore 968 resources from model recurrence to governed agent operations, then build with 22 patterns, 22 contracts, and 8 runtime starters.">
     <meta name="robots" content="index,follow">
     <meta name="author" content="Chaoyue He">
     <link rel="canonical" href="https://chaoyue0307.github.io/awesome-loop-engineering/">
@@ -15,16 +15,16 @@
     <link href="https://fonts.googleapis.com/css2?family=IBM+Plex+Mono:wght@500;600&amp;family=Inter:wght@400;500;600;700;800&amp;display=swap" rel="stylesheet">
     <meta property="og:type" content="website">
     <meta property="og:title" content="Awesome Loop Engineering">
-    <meta property="og:description" content="Explore 956 papers, docs, tools, benchmarks, and guides, then build recurring agent systems with 22 patterns, 22 contracts, and 8 starters.">
+    <meta property="og:description" content="Explore 968 papers, docs, tools, benchmarks, and guides, then build recurring agent systems with 22 patterns, 22 contracts, and 8 starters.">
     <meta property="og:url" content="https://chaoyue0307.github.io/awesome-loop-engineering/">
-    <meta property="og:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-956-v10.png">
+    <meta property="og:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-968-v10.png">
     <meta property="og:image:width" content="1280">
     <meta property="og:image:height" content="640">
     <meta property="og:image:alt" content="Awesome Loop Engineering: design loops, not just prompts.">
     <meta name="twitter:card" content="summary_large_image">
     <meta name="twitter:title" content="Awesome Loop Engineering">
-    <meta name="twitter:description" content="956 resources from model recurrence to agent operations, plus 22 patterns, 22 contracts, and 8 starters for building reliable loops.">
-    <meta name="twitter:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-956-v10.png">
+    <meta name="twitter:description" content="968 resources from model recurrence to agent operations, plus 22 patterns, 22 contracts, and 8 starters for building reliable loops.">
+    <meta name="twitter:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-968-v10.png">
     <link rel="alternate" type="application/atom+xml" title="Awesome Loop Engineering releases" href="https://github.com/ChaoYue0307/awesome-loop-engineering/releases.atom">
     <link rel="alternate" type="application/atom+xml" title="Awesome Loop Engineering commits" href="https://github.com/ChaoYue0307/awesome-loop-engineering/commits/main.atom">
     <style>
@@ -1307,7 +1307,7 @@
           "https://huggingface.co/datasets/cy0307/awesome-loop-engineering"
         ],
         "license": "https://creativecommons.org/publicdomain/zero/1.0/",
-        "image": "https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-956-v10.png",
+        "image": "https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-968-v10.png",
         "logo": "https://chaoyue0307.github.io/awesome-loop-engineering/assets/awesome-loop-engineering-logo.png",
         "author": { "@type": "Person", "name": "Chaoyue He" }
       }
@@ -1355,7 +1355,7 @@
         "@context": "https://schema.org",
         "@type": "Dataset",
         "name": "Awesome Loop Engineering resources",
-        "description": "Explore 956 resources across model, agent, harness, workflow, operations, and evaluation layers, with publication, contribution, novelty, impact, and evidence fields.",
+        "description": "Explore 968 resources across model, agent, harness, workflow, operations, and evaluation layers, with publication, contribution, novelty, impact, and evidence fields.",
         "url": "https://chaoyue0307.github.io/awesome-loop-engineering/",
         "sameAs": [
           "https://huggingface.co/datasets/cy0307/awesome-loop-engineering",
@@ -1430,7 +1430,7 @@
             <p class="section-label hero-kicker"><i class="icon" data-lucide="repeat-2" aria-hidden="true"></i><span>Field guide for recurring agent systems</span></p>
             <h1>Awesome Loop Engineering</h1>
             <p class="tagline">Design loops, not just prompts.</p>
-            <p class="lead">Explore 956 resources from model recurrence to agent operations, then build with 22 patterns, 22 adaptable contracts, and 8 runtime starters.</p>
+            <p class="lead">Explore 968 resources from model recurrence to agent operations, then build with 22 patterns, 22 adaptable contracts, and 8 runtime starters.</p>
             <div class="actions">
               <a class="button primary" href="https://github.com/ChaoYue0307/awesome-loop-engineering#readme"><i class="icon" data-lucide="book-open" aria-hidden="true"></i>Explore resources</a>
               <a class="button" href="#choose"><i class="icon" data-lucide="compass" aria-hidden="true"></i>Choose a loop</a>
@@ -1493,7 +1493,7 @@
             </div>
           </figure>
           <div class="stats" role="list" aria-label="Field guide at a glance">
-            <div class="stat" role="listitem"><b><i class="icon" data-lucide="library" aria-hidden="true"></i>956</b><span>resources</span></div>
+            <div class="stat" role="listitem"><b><i class="icon" data-lucide="library" aria-hidden="true"></i>968</b><span>resources</span></div>
             <div class="stat" role="listitem"><b><i class="icon" data-lucide="blocks" aria-hidden="true"></i>20</b><span>operational patterns</span></div>
             <div class="stat" role="listitem"><b><i class="icon" data-lucide="file-check-2" aria-hidden="true"></i>20</b><span>loop contracts</span></div>
             <div class="stat" role="listitem"><b><i class="icon" data-lucide="play" aria-hidden="true"></i>8</b><span>runtime starters</span></div>
@@ -1793,9 +1793,9 @@
               <p class="section-label"><i class="icon" data-lucide="library" aria-hidden="true"></i><span>06 / Resource atlas</span></p>
               <h2>Find evidence, not just links.</h2>
             </div>
-            <p class="section-intro">Filter 956 resources by goal, loop layer, lifecycle, artifact type, and evidence class. Open any result to see its contribution, novelty, impact, scope, publication details, and original source.</p>
+            <p class="section-intro">Filter 968 resources by goal, loop layer, lifecycle, artifact type, and evidence class. Open any result to see its contribution, novelty, impact, scope, publication details, and original source.</p>
           </div>
-          <p class="audit-note"><strong>Last source check, 2026-08-10 UTC:</strong> 899 public links opened successfully, 6 required access, 51 point to files in this repository, and none were broken or unreachable. <a href="https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/data/resource_source_audit.csv">View the results</a> or <a href="https://github.com/ChaoYue0307/awesome-loop-engineering/issues/new?template=annotation-correction.yml">report a correction</a>.</p>
+          <p class="audit-note"><strong>Last source check, 2026-08-13 UTC:</strong> 913 public links opened successfully, 4 required access, 51 point to files in this repository, and none were broken or unreachable. <a href="https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/data/resource_source_audit.csv">View the results</a> or <a href="https://github.com/ChaoYue0307/awesome-loop-engineering/issues/new?template=annotation-correction.yml">report a correction</a>.</p>
           <div class="loop-layer-map" aria-label="Where different loop concepts live">
             <div class="loop-layer-item"><span>Inner loop</span><strong>Model recurrence</strong><p>A learned block refines hidden or latent state inside one inference. Included as an adjacent foundation.</p></div>
             <div class="loop-layer-item"><span>Task loop</span><strong>Agent execution</strong><p>The model reasons, calls tools, observes results, and updates working state while solving one task.</p></div>
@@ -1879,7 +1879,7 @@
               <button class="resource-collection" type="button" data-collection="Apply" aria-pressed="false"><i class="icon" data-lucide="package-open" aria-hidden="true"></i>Apply</button>
             </div>
             <div class="resource-summary">
-              <p class="resource-count" id="resource-count" aria-live="polite">Preparing 956 resources...</p>
+              <p class="resource-count" id="resource-count" aria-live="polite">Preparing 968 resources...</p>
               <label>
                 <span class="sr-only">Sort resources</span>
                 <select class="resource-select resource-sort" id="resource-sort">
@@ -2483,7 +2483,7 @@
           loading = true;
           explorer.dataset.indexState = 'loading';
           list.setAttribute('aria-busy', 'true');
-          count.textContent = 'Loading 956 resources...';
+          count.textContent = 'Loading 968 resources...';
           list.replaceChildren(createText('p', 'resource-loading', 'Loading resources...'));
 
           fetch('assets/resources.json')

docs/x-v10-968.html

@@ -0,0 +1,44 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <title>Awesome Loop Engineering: 968 resources from model recurrence to agent operations</title>
+    <meta name="description" content="Explore 968 resources, then build recurring AI-agent systems with 22 patterns, 22 contracts, and 8 runtime starters.">
+    <meta name="robots" content="noindex,follow">
+    <link rel="canonical" href="https://chaoyue0307.github.io/awesome-loop-engineering/x-v10-968.html">
+    <meta property="og:type" content="website">
+    <meta property="og:title" content="Awesome Loop Engineering">
+    <meta property="og:description" content="968 papers, docs, tools, benchmarks, and guides, plus 22 patterns, 22 contracts, and 8 starters for recurring AI-agent systems.">
+    <meta property="og:url" content="https://chaoyue0307.github.io/awesome-loop-engineering/x-v10-968.html">
+    <meta property="og:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-968-v10.png">
+    <meta property="og:image:width" content="1280">
+    <meta property="og:image:height" content="640">
+    <meta property="og:image:alt" content="Awesome Loop Engineering: 968 resources, 22 patterns, 22 contracts, and 8 runtime starters.">
+    <meta name="twitter:card" content="summary_large_image">
+    <meta name="twitter:title" content="Awesome Loop Engineering">
+    <meta name="twitter:description" content="From looped models to verified agent work and bounded operations.">
+    <meta name="twitter:image" content="https://chaoyue0307.github.io/awesome-loop-engineering/assets/social-preview-968-v10.png">
+    <meta name="twitter:image:alt" content="Awesome Loop Engineering: design loops, not just prompts.">
+    <link rel="icon" href="assets/favicon-32.png" type="image/png" sizes="32x32">
+    <style>
+      :root { color-scheme: light; font-family: Inter, ui-sans-serif, system-ui, sans-serif; }
+      body { display: grid; min-height: 100vh; margin: 0; place-items: center; background: #f7f9fc; color: #111827; }
+      main { width: min(88vw, 420px); text-align: center; }
+      img { width: 72px; height: 72px; }
+      p { color: #526176; line-height: 1.6; }
+      a { color: #1d4ed8; font-weight: 700; }
+    </style>
+    <script>
+      window.location.replace("https://chaoyue0307.github.io/awesome-loop-engineering/?utm_source=x&utm_medium=social&utm_campaign=v0.10.0");
+    </script>
+  </head>
+  <body>
+    <main>
+      <img src="assets/awesome-loop-engineering-logo.png" alt="Awesome Loop Engineering">
+      <h1>Awesome Loop Engineering</h1>
+      <p>Opening the interactive Resource Atlas.</p>
+      <p><a href="https://chaoyue0307.github.io/awesome-loop-engineering/?utm_source=x&amp;utm_medium=social&amp;utm_campaign=v0.10.0">Continue to the site</a></p>
+    </main>
+  </body>
+</html>

meta/DISTRIBUTION.md

@@ -8,7 +8,7 @@ Status as of 2026-07-20:
 
 | Surface | Status | Evidence / next action |
 | --- | --- | --- |
-| GitHub release | Complete | [`v0.9.0`](https://github.com/ChaoYue0307/awesome-loop-engineering/releases/tag/v0.9.0) packages 956 resources, 22 patterns and contracts, 8 runtime starters, and explicit model-to-operations scope facets. |
+| GitHub release | Complete | [`v0.9.0`](https://github.com/ChaoYue0307/awesome-loop-engineering/releases/tag/v0.9.0) packages 968 resources, 22 patterns and contracts, 8 runtime starters, and explicit model-to-operations scope facets. |
 | Release announcement | Ready | Publish the v0.9.0 summary from [`posts/launch.md`](../posts/launch.md); [Discussion #9](https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/9) is the low-noise release and contributor feed. |
 | GitHub Explore topic | Complete | [`github/explore#5209`](https://github.com/github/explore/pull/5209) merged the `loop-engineering` topic page. |
 | Canonical Awesome directory | Policy objection | [`sindresorhus/awesome#4339`](https://github.com/sindresorhus/awesome/pull/4339) is open and lint passes, but the owner stated that AI-generated lists are not accepted. Do not treat further visual polish as a path around that policy or misrepresent automated assistance. |
@@ -33,7 +33,7 @@ The Hugging Face dataset [`datasets/cy0307/awesome-loop-engineering`](https://hu
 
 - The mirror tracks the full GitHub tree (docs, patterns, examples, schema, scripts).
 - The dataset mirror includes generated resource sheets at `data/resources.csv` and `data/resources.jsonl`, refreshed from the full English `README.md` by `scripts/export_resource_dataset.py`.
-- The HF copy of `README.md` is a focused dataset card generated from `meta/hf_card_header.yaml` and `meta/hf_card_body.md` by `scripts/build_hf_card.py`. It documents intended uses, evidence fields, limitations, loading examples, and the latest link status without duplicating the 956-row GitHub README.
+- The HF copy of `README.md` is a focused dataset card generated from `meta/hf_card_header.yaml` and `meta/hf_card_body.md` by `scripts/build_hf_card.py`. It documents intended uses, evidence fields, limitations, loading examples, and the latest link status without duplicating the 968-row GitHub README.
 - The YAML header is **HF-only**: it must never be added to the GitHub `README.md`, because the metadata list items break `awesome-lint`.
 - Sync uses `python3 scripts/build_hf_card.py --output <staging>/README.md` followed by `hf upload --type dataset` against a staging copy. The token lives in the local Hugging Face cache; no token is committed.
 - **Upload from a clean checkout, and exclude local artifacts.** `hf upload` mirrors the working directory as it is on disk, so a sync run from a working copy that holds untracked build or QA output publishes that output too, and later syncs never remove it because the CLI does not delete. A July 2026 sync pushed 79 browser-automation files (`.playwright-cli/` console logs and element captures, `output/playwright/` screenshots) that were never part of the GitHub tree; they were removed with `hf repos delete-files`. Sync from a fresh clone, and pass `--exclude ".playwright-cli/*" --exclude "output/*"` alongside the existing exclusions.
@@ -52,7 +52,7 @@ Use GitHub-native discovery in this order.
   ```
 
 - **Pin the repository** on your profile, and add it to your profile README (profile-level promotion).
-- **About description.** Keep this concise value statement aligned with the README and project site: `🔁 Build reliable recurring AI-agent systems: 956 resources, 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.`
+- **About description.** Keep this concise value statement aligned with the README and project site: `🔁 Build reliable recurring AI-agent systems: 968 resources, 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.`
 - **Custom social preview** (repo Settings, Social preview) so shared links lead with the same four durable proof points. This is UI-only; it cannot be set through the API.
 - **Releases and Discussions** provide a lower-noise subscription path. Recommend `Watch -> Custom -> Releases and Discussions`; do not ask readers to watch every repository event.
 
@@ -97,7 +97,7 @@ Use the [English launch article](../posts/launch.md) or [Chinese launch article]
 ```text
 🔁 Awesome Loop Engineering maps how recurring AI agents should act, verify, remember, retry, and stop.
 
-956 resources · 22 patterns · 22 contracts · 8 starters
+968 resources · 22 patterns · 22 contracts · 8 starters
 
 Explore and build:
 https://github.com/ChaoYue0307/awesome-loop-engineering
@@ -107,7 +107,7 @@ https://github.com/ChaoYue0307/awesome-loop-engineering
 
 Attach [`assets/social-preview.png`](../assets/social-preview.png) directly when the platform permits it. The post is 264 characters before platform-specific URL shortening.
 
-For a fresh link card on X or LinkedIn, share <https://chaoyue0307.github.io/awesome-loop-engineering/x-v10-956.html>. The versioned URL points to the current preview image, records the `v0.10.0` campaign, and redirects readers to the interactive site.
+For a fresh link card on X or LinkedIn, share <https://chaoyue0307.github.io/awesome-loop-engineering/x-v10-968.html>. The versioned URL points to the current preview image, records the `v0.10.0` campaign, and redirects readers to the interactive site.
 
 ### Chinese Short Post
 
@@ -131,7 +131,7 @@ Awesome Loop Engineering v0.9.0 is live.
 
 The release includes:
 
-- 956 papers, docs, tools, benchmarks, and guides
+- 968 papers, docs, tools, benchmarks, and guides
 - 29 model-layer resources, including Loopie, labeled as adjacent foundations
 - an interactive Resource Atlas
 - 22 operational patterns and 22 adaptable loop contracts
@@ -148,11 +148,11 @@ https://github.com/ChaoYue0307/awesome-loop-engineering
 Use a regular submission, not Show HN.
 
 ```text
-Title: Awesome Loop Engineering: 956 resources from looped models to agent operations
+Title: Awesome Loop Engineering: 968 resources from looped models to agent operations
 
 I have been mapping recurring AI-agent systems: how work enters, agents act, evidence gates results, state survives, and the system retries, escalates, or exits.
 
-The repository connects 956 papers, docs, tools, benchmarks, and guides across model, agent, harness, workflow, operations, and evaluation layers with 22 operational patterns, 22 adaptable contracts, 8 runtime starters, an interactive Resource Atlas, and a structured Hugging Face dataset. Model-level recurrence is labeled as an adjacent foundation rather than a complete operational loop. Corrections to source links, taxonomy, and summaries are especially welcome.
+The repository connects 968 papers, docs, tools, benchmarks, and guides across model, agent, harness, workflow, operations, and evaluation layers with 22 operational patterns, 22 adaptable contracts, 8 runtime starters, an interactive Resource Atlas, and a structured Hugging Face dataset. Model-level recurrence is labeled as an adjacent foundation rather than a complete operational loop. Corrections to source links, taxonomy, and summaries are especially welcome.
 
 https://github.com/ChaoYue0307/awesome-loop-engineering
 ```

meta/OUTREACH.md

@@ -12,7 +12,7 @@ Use these messages to request sources, operating examples, and accuracy correcti
 ## Short Message
 
 ```text
-Hi <name>, Awesome Loop Engineering connects 956 papers, docs, tools, benchmarks, and guides with reusable patterns for recurring AI-agent systems.
+Hi <name>, Awesome Loop Engineering connects 968 papers, docs, tools, benchmarks, and guides with reusable patterns for recurring AI-agent systems.
 
 If you have an original or official source, a correction, a real-world loop, or a cautionary example, you can contribute here:
 https://github.com/ChaoYue0307/awesome-loop-engineering
@@ -38,7 +38,7 @@ https://github.com/ChaoYue0307/awesome-loop-engineering/issues/new?template=anno
 ## Maintainer Request
 
 ```text
-Hi <name>, Awesome Loop Engineering helps researchers and builders move from 956 papers, docs, tools, benchmarks, and guides to 22 operational patterns, 22 adaptable contracts, 8 runtime starters, and a structured dataset.
+Hi <name>, Awesome Loop Engineering helps researchers and builders move from 968 papers, docs, tools, benchmarks, and guides to 22 operational patterns, 22 adaptable contracts, 8 runtime starters, and a structured dataset.
 
 Would it fit the related-resources policy for <project or newsletter>? I can provide a shorter description or submit through the normal contribution process:
 https://github.com/ChaoYue0307/awesome-loop-engineering

meta/social-preview.html

@@ -79,7 +79,7 @@
         <p>Model / agent / operations</p>
       </div>
       <div class="stats">
-        <div class="stat"><b>956</b><span>Papers, docs, tools + guides</span></div>
+        <div class="stat"><b>968</b><span>Papers, docs, tools + guides</span></div>
         <div class="stat"><b>22</b><span>Operational patterns</span></div>
         <div class="stat"><b>22</b><span>Schema-checked contracts</span></div>
         <div class="stat"><b>8</b><span>Runtime starters</span></div>

posts/launch.md

@@ -2,11 +2,11 @@
 
 Awesome Loop Engineering v0.9.0 maps recurrence from a model's inner computation to an agent's tools and the outer operating loop that verifies, remembers, retries, escalates, and stops.
 
-Explore 956 resources without collapsing looped models, agent execution, harnesses, workflows, and production operations into one idea.
+Explore 968 resources without collapsing looped models, agent execution, harnesses, workflows, and production operations into one idea.
 
 ## What You Can Use
 
-- 956 papers, official docs, tools, benchmarks, and guides linked to the original work
+- 968 papers, official docs, tools, benchmarks, and guides linked to the original work
 - 31 model-layer resources, from Universal Transformers and Huginn to Loopie, LoopCoder, and LoopWM, labeled as adjacent foundations rather than complete agent loops
 - 22 operational patterns organized by build, operate, optimize, and govern use cases
 - 22 schema-checked loop contracts, one for every pattern

posts/launch.zh-CN.md

@@ -2,11 +2,11 @@
 
 Awesome Loop Engineering v0.9.0 建立了一张从模型内部递归、Agent 执行、Harness 到外层运行系统的完整地图。
 
-可浏览 956 篇论文、官方文档、工具、benchmark 与实践指南，同时保持清晰边界：模型内的循环提供自适应计算，但不等于具备外部验证、持久状态、预算、人类交接与退出规则的运行级 Loop。
+可浏览 968 篇论文、官方文档、工具、benchmark 与实践指南，同时保持清晰边界：模型内的循环提供自适应计算，但不等于具备外部验证、持久状态、预算、人类交接与退出规则的运行级 Loop。
 
 ## 可直接使用
 
-- 956 篇论文、官方文档、工具、benchmark 与实践指南，并直接链接原始来源
+- 968 篇论文、官方文档、工具、benchmark 与实践指南，并直接链接原始来源
 - 29 个模型层资源，覆盖 Universal Transformers、Huginn、Loopie、LoopCoder、LoopWM 等方向
 - 20 个按 build、operate、optimize、govern 组织的 operational patterns
 - 20 个经过 schema 校验的 loop contracts，每个 pattern 对应一个

scripts/build_brand_assets.py

@@ -67,7 +67,10 @@ def main() -> None:
                     stale.append(path)
                     continue
                 current = Image.open(path).convert("RGBA")
-                if current.size != output.size or ImageChops.difference(current, output).getbbox():
+                # getbbox() defaults to alpha_only=True on RGBA, so it would compare only the
+                # alpha channel and report a fully recoloured mark as current. Compare colour.
+                difference = ImageChops.difference(current, output)
+                if current.size != output.size or difference.getbbox(alpha_only=False):
                     stale.append(path)
                 continue
             path.write_bytes(payload)