Token Enhancer reduces webpage token usage for AI agents
A developer analyzed their AI agent logs and discovered that web fetches include full raw HTML in context, consuming significant tokens. Most of this content consists of navigation bars, scripts, ads, and other non-essential elements.
Token reduction benchmarks
After implementing HTML stripping before content reaches context:
- Yahoo Finance: 704K tokens down to 2.6K tokens
- Wikipedia: 154K tokens down to 19K tokens
- Hacker News: 8.6K tokens down to 859 tokens
Tool implementation
The developer uses Token Enhancer, which works as an MCP server that OpenClaw automatically picks up. The tool is available at: https://github.com/Boof-Pack/token-enhancer
For developers whose AI agents regularly fetch external data, checking logs for raw HTML token consumption could reveal significant cost savings that might otherwise go unnoticed.
📖 Read the full source: r/openclaw
👀 See Also
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Routerly is a free, open-source, self-hosted LLM gateway that provides runtime model selection based on routing policies like cheapest, fastest, or most capable, along with project-level budget limits with per-token tracking. It's OpenAI-compatible for drop-in use with tools like Cursor, LangChain, and Open WebUI.
ReasonDB: Open-Source Document Database Using LLM-Guided Tree Navigation Instead of Vector Search
ReasonDB is an open-source document database that preserves document structure as a hierarchy and uses LLM-guided tree traversal for retrieval instead of vector search. It uses BM25 for initial search, tree-grep for structure filtering, and beam-search traversal where the LLM visits ~25 nodes out of millions.
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