Weekly Report — 2026-W14 (2026-03-30 ~ 2026-04-05)

This week was characterized by high-intensity synchronization across cross-platform desktop development, HPC research pipeline stabilization, and large-scale robotic dataset generation. Key achievements included a major architectural refactor of the Life-Copilot ecosystem from monolithic routing to a multi-CLI agent orchestration model, the stabilization of TokenMonitor’s Linux UI rendering through fixed-size geometry strategies, and the successful hardening of the Error Recovery Benchmark via per-frame kinematic phase detection and robust data curation. Additionally, critical research discrepancies in spatial transcriptomics and transformer model convergence were resolved through systematic unit normalization and cache auditing, ensuring high-confidence results in both academic and production environments.

Weekly Overview

Metric Value
Date Range 2026-03-30 ~ 2026-04-05
Active Days 6 / 7
Total Conversations 28
Projects 28
Tasks Completed 26
Tasks In Progress 7
Total Tokens 706,758,833
Total Cost $473.84
Claude Code Token 530,743,109
Claude Code Cost $380.31
Codex Token 176,015,724
Codex Cost $93.53
Daily Average Cost $67.69

Project Progress

TokenMonitor Desktop App (5 days active) — ✅ completed

Accomplishments:

  • Resolved Claude parser deduplication overcounting and GitHub Actions silent failures
  • Fixed Linux UI positioning jank and transparent window ghosting using fixed-size architecture and GDK input masking
  • Stabilized Rust-side authoritative window coordinate tracking to eliminate Wayland UI jitter
  • Resolved 21 critical/high PR review items including panic removal and async lock management
  • Successfully triggered native macOS/Windows release workflows (v0.6.1)

Blockers:

  • ⚠️ Linux compositor persistence/artifacting during UI transitions

Life-Copilot Ecosystem Refactor (3 days active) — 🔄 active

Accomplishments:

  • Replaced monolithic semantic routing with multi-CLI subprocess orchestration
  • Implemented Thin Adapter patterns and in-process MCP server exposure via stdio
  • Deployed production-grade structlog audit system with JSONL rotation

Blockers:

  • ⚠️ CLI session state fragmentation and context injection loss

ErrorRecoveryBenchmark (5 days active) — 🔄 active

Accomplishments:

  • Expanded skill taxonomies to 29 subtypes
  • Implemented per-frame kinematic phase detection for better injection sampling
  • Validated a purified dataset of 8 high-confidence recovery demonstrations
  • Implemented dynamic gripper-release success verification and HDF5 fingerprint matching
  • Designed async VLA server evaluation architecture for multi-GPU parallel execution
  • Resolved parallel worker starvation and simulator binding crashes

Blockers:

  • ⚠️ Coarse trajectory segmentation causing missing injection opportunities
  • ⚠️ Cross-architecture MuJoCo float accumulation divergence

MIHD & Academic Research (4 days active) — 🔄 active

Accomplishments:

  • Stabilized pipeline by purging stale STAIG fusion caches
  • Validated scGPT zero-shot retrieval performance
  • Restored ground truth mapping via raw HDF5 gene intersection
  • Architected dual-language manuscript skeletons for spatial transcriptomics
  • Diagnosed and mitigated Crossformer/LiPM metric scaling discrepancies via unit normalization audits
  • Configured SLURM profiles for multimodal fusion pipelines

Blockers:

  • ⚠️ Silent pipeline override failures due to pre-existing binary caches

Gadget Hugo Bilingual Infrastructure (1 days active) — ✅ completed

Accomplishments:

  • Architected native dual-language generation middleware
  • Localized 165+ pages with zero content loss
  • Resolved SRI hash mutations and CRLF/LF normalization conflicts

Crossformer Battery Training (1 days active) — 🔄 active

Accomplishments:

  • Stabilized model convergence via learning rate reduction and gradient clipping
  • Identified and fixed unnormalized target scale issues (mΩ range)

Key Tasks

  • Life-Copilot Architectural Refactor & Multi-CLI Orchestration — Transitioned from legacy monolithic routing to a production-grade multi-CLI agent architecture using Thin Adapter patterns and dynamic system prompt injection via stdio/SSE transport layers.
  • TokenMonitor Cross-Platform & UI Stabilization — Addressed core architecture, CI/CD, and Linux compositor issues including Wayland layout failures and cross-platform PR finalization.
  • Error Recovery Benchmark: Data Curation & Pipeline Optimization — Optimized robotic error scene generation using per-frame kinematic tracking, audited success-check logic, and patched NPZ serialization bugs.
  • MIHD Spatial Transcriptomics Pipeline Validation — Integrated Leiden clustering baselines, resolved embedding non-comparability via HDF5 intersection, and validated scGPT performance.
  • Gadget Hugo Bilingual Infrastructure Deployment — Established a robust dual-language static site pipeline with strict asset preservation and localized over 165 pages.
  • AI Model Reproducibility & Training Stabilization — Diagnosed MAE/MSE deviations and stabilized Crossformer training through domain-specific scale normalization and gradient management.
  • 🔄 Pi0.5 Multi-GPU Policy Evaluation Framework Deployment — Configuring parallel multi-GPU benchmarking pipelines across error scenarios; currently resolving VLA server subprocess deadlocks.

Problems & Solutions

1. TokenMonitor billing overcounting due to mirrored JSONL files and flawed hashing. [TokenMonitor]

Solution: Implemented strict message_id:request_id pairing and a ‘best-wins’ strategy for final token states.

2. Wayland compositor protocol ignored client-side window placement, causing UI misalignment. [TokenMonitor]

Solution: Implemented ball-anchored relative positioning with Rust-side authoritative ’last_rect’ state tracking.

3. Hugo frontend style loss due to SRI hash mutations and line-ending conflicts. [Gadget Hugo]

Solution: Enforced binary preservation via .gitattributes and rebuilt assets with strict CRLF/LF normalization.

4. Stale transient caches causing invalid ground truth labels in MIHD pipeline. [MIHD]

Solution: Implemented forensic timestamp auditing and explicit directory purging before re-execution.

5. Metric divergences in Crossformer/LiPM due to unhandled normalization domains. [MIHD/Crossformer]

Solution: Audited evaluation scripts to ensure metrics are computed on back-translated physical units rather than normalized tensors.

6. Robot trajectory segmentation missing fine-grained injection opportunities. [ErrorRecoveryBenchmark]

Solution: Replaced segment-level heuristics with dynamic per-frame kinematic phase tracking.

7. Parallel data generation pool crashed on single-scene BDDL sampling failures. [ErrorRecoveryBenchmark]

Solution: Implemented lazy task-level environment initialization to isolate failures and prevent pool-wide termination.

8. Subprocess pipe deadlocks during large model initialization in parallel VLA server launches. [ErrorRecoveryBenchmark]

Solution: Redirected heavy stdout/stderr to direct file streams and expanded socket timeouts to accommodate JIT warmup phases.

Learnings

Architecture (architecture)

  • Pipeline override mechanisms fail silently against pre-existing binary caches; timestamp auditing must precede HPC re-execution.
  • Dataset generation architectures must decouple worker allocation from task completion counts for parallel efficiency.
  • Multi-CLI orchestration requires strict fallback abstraction layers; context-aware intent routing needs explicit historical parameters at the boundary as scorers cannot reconstruct temporal dependencies from isolated tokens.

Debugging (debugging)

  • High transformer loss magnitudes and academic metric discrepancies often stem from unnormalized domain units or normalization leakage rather than algorithmic failure.
  • Streaming APIs require deduplication that selects final completion states and isolates request IDs from session metadata.

Tools (tools)

  • SRI integrity is highly sensitive to Git line-ending normalization; use .gitattributes for all web assets.
  • GitHub Actions requires explicit version tags across all tripartite package manifests (package.json, Cargo.toml, tauri.conf.json) to trigger releases.
  • Headless AI agents require explicit bypass permissions and configuration flags for MCP tools, as they often enforce strict interactive boundaries.

Domain Knowledge (domain)

  • Floating-point physics simulations exhibit hardware-dependent drift (e.g., macOS ARM vs Linux x86_64); success criteria must rely on dynamic physical state stability.

AI Usage Notes

Effective Patterns:

  • ✓ Using strict negative constraints for technical translation to preserve YAML/LaTeX boundaries.
  • ✓ ECL-driven constraint planning to reduce contextual degradation in long-running projects.
  • ✓ Using structured analytical prompting for research direction formulation.
  • ✓ Leveraging AI for deep code audits and systematic diff analysis during PR cleaning.
  • ✓ Translating complex architectural human-directives into platform-specific implementation (e.g., GTK/Rust/X11).

Limitations:

  • ✗ Context window limits causing truncation in large documentation/academic tables.
  • ✗ Failure to recognize mtime-based filtering incompatibility with immutable session files.
  • ✗ Initial blindness to external ecosystem pricing architectures requiring explicit provider data.
  • ✗ Overestimation of citation impact/data readiness without verifying environment-specific metadata.
  • ✗ Hallucination of GUI wrapper commands and silent failure in async signature detection.
  • ✗ Difficulty in autonomously correcting cross-environment absolute paths and parallel orchestration timing.

Next Week Outlook

Priorities for next week include completing the Pi0.5 Multi-GPU Policy Evaluation framework by resolving remaining VLA server deadlocks, advancing the MIHD Manuscript preparation (Figures 2-5), and accelerating Life-Copilot feature expansion (Screen Time Tracker/Quick Thought Capture). Additionally, initiate formal batch-training using the newly validated 8-demo Error Recovery dataset while continuing to monitor multi-GPU cluster stability on Tianhe.

Token Usage Statistics

AI Usage · 2026-W14 Claude Code + Codex
Total cost
$473.84
Total tokens
707M
Output tokens
4M
Cache read
94.3%
Cost split Claude Code $380 · Codex $94
Token character Cache reads 94.3% · Active 5.7%

Most token volume came from cache reads; Claude Code drove nearly all cost.

Peak Day: 2026-04-04 — $215.45 / 320.9M tokens

Daily Average: $67.69