July 8, 2026

Agentic Frameworks, Tooling, Skills

CanvasAgent, https://huggingface.co/papers — Visual tool orchestration framework that chains image generation and editing primitives into deterministic agentic loops; replaces ad-hoc PIL/ComfyUI routing with a unified skill system for aerospace schematic iteration and rover hardware mockup generation. [Source: https://huggingface.co/papers]

SkillOpt-Lite, https://huggingface.co/papers — Agent self-evolution skill layer that automates policy refinement via single-line vibe prompts; enables local agents to iteratively adapt tool-calling schemas and routing rules without external RL loops or manual reward tuning. [Source: https://huggingface.co/papers]

345 Claude Code Skills & Agent Plugins, https://github.com/trending/python?since=daily — Consolidated repository of 30+ agents, 70+ custom commands, and 330+ skills; provides a drop-in plugin layer for Claude Code/Cursor that automates cross-repo context graphing, compliance checks, and workflow scaffolding without custom MCP server development. [Source: https://github.com/trending/python?since=daily]

Notable Research

Hierarchical Sparse Attention, https://huggingface.co/papers — Tencent Hunyuan’s method for infinite context modeling; shifts local inference from KV-cache eviction to hierarchical sparsity, preserving long-horizon telemetry and document recall on 32GB VRAM without recomputation overhead. [Source: https://huggingface.co/papers]

DSpark, https://huggingface.co/papers — DeepSeek’s confidence-scheduled speculative decoding with semi-autoregressive generation; reduces token latency and compute overhead for agentic tool-calling loops while maintaining policy consistency and routing stability. [Source: https://huggingface.co/papers]

TurnOPD, https://huggingface.co/papers — Turn-aware on-policy distillation for long-horizon agents; replaces fixed-step RL training with dynamic turn-budget allocation, cutting training compute for autonomous mission planning without accuracy degradation. [Source: https://huggingface.co/papers]

Frontier Lab Updates

Anthropic Claude Sonnet 5 / Opus 4.8 Tool-Schema Drift, https://simonwillison.net/ — Newer Anthropic models now invent extra fields in nested edit arrays, breaking compatibility with third-party coding harnesses and custom MCP servers that expect strict schema matching; requires downstream tool-calling wrappers to implement flexible schema fallbacks or schema relaxation. [Source: https://simonwillison.net/]

Google Gemini 3.1 Flash Lite Image, https://simonwillison.net/ — Optimized for velocity and scale as a lightweight, high-throughput image generation endpoint; suitable for rapid aerospace component visualization and rover telemetry preview without full model deployment or heavy GPU allocation. [Source: https://simonwillison.net/]

Models to Download & Try

Qwen/Qwen-AgentWorld-35B-A3B, https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B — 35B MoE (3B active parameters); ~12–14GB GGUF footprint leaves >16GB VRAM for KV context; purpose-built for agentic workflow orchestration and tool routing, directly extending your Qwen 3.6:35b base for multi-agent state management and complex task decomposition. [Source: https://huggingface.co/models?sort=trending]

poolside/Laguna-XS-2.1, https://huggingface.co/poolside/Laguna-XS-2.1 — 33B text generation model; ~18–20GB Q4_K_M GGUF fits comfortably in 32GB with ~10GB context headroom; optimized for complex instruction-following and research pipeline orchestration, offering a higher reasoning ceiling for long-document synthesis and agent memory formatting. [Source: https://huggingface.co/models?sort=trending]

baidu/Unlimited-OCR, https://huggingface.co/baidu/Unlimited-OCR — 3B vision/OCR specialist; ~1.8GB GGUF leaves >28GB VRAM for heavy context/VLM routing; plugs directly into your vision-scraper pipeline for high-fidelity aerospace document digitization and rover schematic parsing without external API dependencies. [Source: https://huggingface.co/models?sort=trending]

Skipped as Already Covered

• tencent/Hy3 (295B MoE) — exceeds 32GB VRAM limits; covered 7/7.
• zai-org/GLM-5.2 (753B) — cloud-scale; covered 7/6.
• deepseek-ai/DeepSeek-V4-Pro-DSpark (889B) — cloud-scale; covered 7/6.
• Claude Sonnet 5 tokenizer/pricing shift — covered 7/5/7/7.
• Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF & unsloth/Qwen3.6-27B-MTP-GGUF — covered 7/4/7/5.
• empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF — covered 7/4/7/5/7/6.