Localhost dashboard for Claude's HTML output pages with live reload
A Reddit user shared a small localhost home page that aggregates all the HTML pages generated by Claude AI. The tool addresses the problem of HTML outputs ending up scattered across the filesystem by providing a card-based dashboard that shows all pages in one place.
Key features
- Card display — Each HTML page appears as a card on the localhost homepage.
- Live reload — Cards refresh automatically when the underlying file changes.
- Update indicators — Cards that have been updated are visually marked.
- Quick preview pane — Hover or click to preview the HTML content inline.
- Symlink registration — AI agents can register their own HTML outputs by dropping a symlink into the watched directory.
The project is open source on GitHub: Himel55/localhost-pages.
📖 Read the full source: r/ClaudeAI
👀 See Also
OpenClaw Model Performance Review: Codex 5.3 Leads, GLM Models Disappoint
A developer tested multiple AI models with OpenClaw, finding Codex 5.3 performs best with 9/10 rating, while GLM 4.7 and GLM 5 scored 5/10 due to high token usage, slow responses, and inconsistent output.
Engram Memory SDK: Graph-Based Memory for AI Agents with Local Models
Engram Memory SDK is an open-source graph memory system for AI agents that works with local models via LiteLLM. It requires only one LLM call for ingestion, then uses vector search and graph traversal for recall with zero ongoing LLM costs.
Parallel Agent Orchestrator for Claude Code Using Git Worktrees
A developer built a parallel orchestrator that uses git worktrees to create isolated environments for Claude Code agents, solving the problem of shared working directories causing broken apps and messy git status.
Tendr Skill Adds CLI-Based Long-Term Memory with Hierarchy to Reduce Token Usage
A new OpenClaw skill separates reasoning from execution for long-term memory operations, using a CLI tool to handle structural changes deterministically. It supports wikilinks and explicit semantic hierarchy across files to reduce token consumption and prevent error accumulation.