SCOREAgents & automation
Hermes Agent Request Scope Resolution

This project introduces an optional skill for the Hermes Agent that improves request understanding by implementing a three-stage confidence-gated ladder to resolve ambiguity, reducing token usage and time spent guessing.
TakeSystem One decision — a typed-decision model (JEV via OpenRouter) classifies the request and assigns a confidence score. 2.
I just opened PR #118604 against the Hermes Agent repo — a Request Scope Resolution optional skill.
The problem: You say "fix the deployment" — Hermes doesn't know which deployment, which fix, or what priority. It guesses. Guessing costs tokens and time.
The fix: A three-stage confidence-gated ladder:
1. System One decision — a typed-decision model (JEV via OpenRouter) classifies the request and assigns a confidence score.
2. Memory search — if confidence is 0.6-0.85, it searches configured memory surfaces (MeMex, HermesVault {Obsidian}, MCP servers) for prior context before proceeding.
3. Ask the user — only if confidence stays below 0.6, and then with one or two bounded clarifying questions. No open-ended prompts.
Ships as an optional skill with a stdlib-only Python script, 12 tests, and docs.
github.com/JPeetz/agent-skills + PR #118604 at NousResearch/hermes-agent
@NousResearch @Teknium
#HermesAgent #OpenSource
