A hook that halts a Claude Code session when the model serving it changes mid-session β for example when Fable 5 falls back to Opus 4.8 because credits ran out or a safety classifier flagged a request.
Without this, a session can silently continue for tens of minutes on a model you did not choose. In the case that prompted this, a session ran 309 messages on Fable 5, switched at the 310th, and continued for 91 more messages over 30 minutes before anyone noticed.
| # Agent Toolkit: Comprehensive Tool Inventory | |
| **Status:** Curated Reference Document (v9 - added RE category) | |
| **Date:** 2026-02-04 | |
| **Purpose:** Catalog of agent-friendly CLI tools optimized for AI agent use | |
| **Total Tools:** ~275 (after removing 255 unsuitable tools, added Category 36: Binary Analysis & RE) | |
| --- | |
| ## Table of Contents |
| # Spec: tmux Agent Panes | |
| > Fork Claude agents into observable tmux panes | |
| ## Overview | |
| This skill enables Claude to spawn parallel agents, each working in their own tmux pane. The user can observe all agents working simultaneously in a single terminal window. | |
| ``` | |
| βββββββββββββββββββββββ¬ββββββββββββββββββββββ¬ββββββββββββββββββββββ |
| # Claude Code Skills Reference | |
| **Version**: 2.5 | |
| **Claude Code Version**: 2.1.7 (fully tested) | |
| **Date**: 2026-01-15 | |
| **Methodology**: Systematic testing of 167 skill configurations + diagnostic introspection | |
| --- | |
| ## Executive Summary |
| # Analysis of "Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity" | |
| ## Response 1 (Probability: 0.23) | |
| ### 1. Core Claim Contradicting Common Assumptions (Section 3) | |
| The paper argues mode collapse is fundamentally a **data-level problem** rather than an algorithmic one. Existing work attributed mode collapse to inadequate reward models or majority-favoring optimization. The authors prove typicality bias (Ξ± = 0.57Β±0.07, p<10^-14 in HELPSTEER dataset) exists in preference data itself, meaning "even with a perfect reward model and optimization process, inherent bias within preference datasets may still drive mode collapse." | |
| This matters because it implies you can't fix mode collapse by improving RLHF algorithms alone - the preference collection process itself needs reconsideration. | |
| ### 2. Magnitude Finding (Section 5, Figure 4) |
| # π¨ Complete Visual UI Development Guide for Claude Code | |
| ## π The Game-Changing Discovery | |
| **Claude Code can SEE screenshots!** This completely transforms UI development from blind coding to visual design with real-time feedback. | |
| ### The Transform | |
| - **Old Way**: Write code β Hope it looks good β Fix bugs when reported | |
| - **New Way**: Build β **SEE** β Judge β Refine β Repeat until beautiful |