Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

本周的特点是在多个领域进行了高强度的技术重构和基础设施稳定化。主要成果包括：成功将 Gadget 项目迁移至统一的 ccusage 20.x 架构；在 Tianhe2 上为 Error Recovery Benchmark (M16) 建立了统计学严谨的评估协议；以及完成了 Research 模块的大规模 bug 修复。在消费者应用开发方面也取得了显著进展，包括为 Desktop Video 进行了重大的 macOS 风格 UI 重构，并对 TokenMonitor 进行了关键的性能优化，同时解决了 Linux 系统上深层的硬件/驱动冲突问题。

Weekly Overview

Metric	Value
Date Range	2026-06-08 ~ 2026-06-14
Active Days	6 / 7
Total Conversations	21
Projects	18
Tasks Completed	34
Tasks In Progress	4
Total Tokens	757,032,150
Total Cost	$1,011.82
Claude Code Token	726,642,736
Claude Code Cost	$987.17
Codex Token	30,389,414
Codex Cost	$24.65
Daily Average Cost	$168.64

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Accomplishments:

根据 ‘Panorama’ 权威规范（SR + Continuous RP + Fisher Exact Test）重新调整了协议
实现了确定性分层采样 (M16) 并构建了 eval_set_sampler.py
在 Tianhe2 上部署了大规模评估流水线，用于 135k 个验证场景

Blockers:

⚠️ 最初与学术论文指标存在偏差（已通过重新对齐解决）

Gadget Research Module (4 days active) — 🔄 active

Accomplishments:

执行了全面的 58 个 bug 修复计划
从旧有的拆分依赖迁移至统一的 ccusage 20.x 架构
实现了基于源的发现机制和 JSON schema 归一化

Blockers:

⚠️ LLM timeout 崩溃和 cache poisoning 问题（已解决）

Desktop Video (2 days active) — 🔄 active

Accomplishments:

交付了符合 Apple 标准的 macOS System Settings 风格 UI 重构
开发了 7 项新功能，包括自动幻灯片和文件夹支持
通过同步 NSCache seeding 修复了 UI 闪烁问题

Blockers:

⚠️ Sandbox bookmark 作用域不匹配（已解决）

TokenMonitor (3 days active) — 🔄 active

Accomplishments:

通过增量失效逻辑将 CPU 负载降低了约 60 倍
使用带有 hostname 标签的 exports 实现了跨机器使用情况同步
修复了新 Anthropic 系列模型的归一化和定价问题

Blockers:

⚠️ 过时的 archive 数据覆盖了实时日志（已解决）

MIHD / JEPA Research (3 days active) — 🔄 active

Accomplishments:

综合了可操作的研究方向（Visual Action Tokens, Hierarchical WAMs）
通过 100 个 seed 的扫描，证明了 UNI2 encoder 在空间转录组学方面优于 scGPT/TEDDY

Key Tasks

✅ JEPA and Robotics Literature Strategy — 基于对关键论文（MemoryVLA++ 等）的深度结构化分析，综合了结合层次化规划和情境记忆的研究方向。
✅ Error Recovery Benchmark Protocol Realignment — 放弃了源自论文的指标，转而采用 ‘Panorama’ 规范，确保了恢复率的科学有效性。
✅ HP OMEN PC Crash & PCIe Error Diagnosis — 通过解析 WHEA 日志，确认 PCIe Correctable Errors 是由监控软件引起的良性噪声。
✅ Gadget Research Module Bug Remediation — 执行了涵盖异常处理、cache poisoning 和配置不匹配的 58 个 bug 修复计划。
✅ TokenMonitor CPU Hotspot Resolution — 重构了 parser 以实现增量更新而非全量扫描，实现了 60 倍的 CPU 降幅。
✅ ccusage 20.x Migration — 架构转向统一的、与源无关的 token 追踪系统。
✅ STAIG Fusion Benchmarking — 进行统计扫描以验证 UNI2 在空间聚类方面的性能优势。
✅ Desktop Video UI Redesign — 使用 SwiftUI 实现了高保真 macOS 风格的原生设计模式。

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

Solution: 在 common/llm.py 中实现了统一的错误契约，将 timeout 封装为 RuntimeError。

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

Solution: 添加了质量门控（quality gates）并实现了 TTL/唯一请求哈希键，以区分失败状态与成功状态。

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

Solution: 进行了 100 个 seed 的统计扫描，以表征方差并确认 UNI2 的优越性。

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

Solution: 将自签名包替换为 Canonical 签名的内核模块。

Solution: 在 SwiftUI views 中实现了双分支 bookmark 解析和同步 NSCache seeding。

Learnings

Architecture (architecture)

在缓存系统中，区分“瞬时故障”与“永久状态”对于防止持久性数据污染至关重要。
全局数据结构在多租户/多显示环境中会失效；schema 必须具备维度感知能力（例如 device/screen UUIDs）。

Debugging (debugging)

随机算法（如 mclust EM clustering）需要进行多 seed 统计验证，而非单次运行的基准测试。
PCIe Correctable Errors 通常是良性的软件诱发噪声（例如监控工具探测 config space），而非硬件故障。

Domain Knowledge (domain)

在具身智能（embodied AI）中，潜在空间交互（如 V-JEPA）在直观物理和空间聚类方面表现出优于视频扩散模型（video diffusion）的特性。

Tools (tools)

Vite 的依赖优化对文件系统稳定性高度敏感，尤其是在 NTFS/FUSE 挂载点上。

AI Usage Notes

Effective Patterns:

✓ 用于大规模代码审计的多智能体“对抗式”工作流
✓ 用于强制执行严格文档合规性的测试驱动开发（Test-first development）
✓ 当 IDE 失效时，使用低级语言编译器 (swiftc) 作为备选验证工具

Limitations:

✗ 难以自动区分学术论文规范与内部项目策略（需要人工锚定）
✗ 在密集的基准测试分析期间存在 context window 限制
✗ 在没有明确提示的情况下，无法诊断持久层问题（archive 覆盖问题）

Next Week Outlook优先级包括在 Tianhe2 上完成大规模评估运行，完成 MIHD 的 UNI2+staig_fusion 实现，并继续在所有剩余研究模块中进行 ccusage 20.x 集成。此外，预计还将跟进 Desktop Video 的稳定性以及针对新 agents 的潜在 token tracking 扩展。

Token Usage Statistics

Peak Day: 2026-06-13 — $264.26 / 183.6M tokens

Daily Average: $168.64

Weekly Summary 2026-W24

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

Weekly Overview

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Gadget Research Module (4 days active) — 🔄 active

Desktop Video (2 days active) — 🔄 active

TokenMonitor (3 days active) — 🔄 active

MIHD / JEPA Research (3 days active) — 🔄 active

Key Tasks

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]

Learnings

Architecture (architecture)

Debugging (debugging)

Domain Knowledge (domain)

Tools (tools)

AI Usage Notes

Next Week Outlook优先级包括在 Tianhe2 上完成大规模评估运行，完成 MIHD 的 UNI2+staig_fusion 实现，并继续在所有剩余研究模块中进行 ccusage 20.x 集成。此外，预计还将跟进 Desktop Video 的稳定性以及针对新 agents 的潜在 token tracking 扩展。

Token Usage Statistics

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)#

Weekly Overview#

Project Progress#

Error Recovery Benchmark (5 days active) — 🔄 active#

Gadget Research Module (4 days active) — 🔄 active#

Desktop Video (2 days active) — 🔄 active#

TokenMonitor (3 days active) — 🔄 active#

MIHD / JEPA Research (3 days active) — 🔄 active#

Key Tasks#

Problems & Solutions#

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]#

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]#

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]#

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]#

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]#

Learnings#

Architecture (architecture)#

Debugging (debugging)#

Domain Knowledge (domain)#

Tools (tools)#

AI Usage Notes#

Token Usage Statistics#

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

Weekly Overview

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Gadget Research Module (4 days active) — 🔄 active

Desktop Video (2 days active) — 🔄 active

TokenMonitor (3 days active) — 🔄 active

MIHD / JEPA Research (3 days active) — 🔄 active

Key Tasks

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]

Learnings

Architecture (architecture)

Debugging (debugging)

Domain Knowledge (domain)

Tools (tools)

AI Usage Notes

Token Usage Statistics