Hermes Agent FAQ — Setup, Tool Use & Debugging Questions

Hermes needs to hold its system prompt, active skill definitions, memory files, and the full conversation history in context simultaneously. Models with smaller windows get truncated mid-session and lose track of earlier tool calls or memory entries — this causes the agent to repeat steps, forget instructions, or fail silently. The 64K minimum is enforced at startup and Hermes will reject models that don't meet it. For local inference, Llama 3.1 8B and Qwen 2.5 14B both support 128K context and work reliably. Source: Hermes Agent troubleshooting guide

Hermes's web and browser tools are only enabled when the configured model passes its internal capability checks — checks that many local models fail even if they chat normally. The fix: first verify your local model works for plain conversation, then test a single tool call in isolation before enabling all skills. If cloud models work but your local model doesn't, the problem is almost always capability detection, not the tool itself. Check the Hermes MCP tools guide for provider-specific workarounds. Source: Hermes troubleshooting docs

Debug in strict layers: (1) install and basic CLI, (2) model and provider connection, (3) tool calls, (4) terminal/gateway backend, (5) advanced integrations like Telegram, cron, or Discord. Most failures look mysterious because two layers were changed simultaneously. Start with hermes chat in the CLI and confirm you get one clean response before adding skills, Docker, or gateway config. If plain chat fails, everything else will too — fix the base layer first. Source: Hermes Agent troubleshooting