Tool
TraceCC — CLI-Native Long-Term Memory for Hermes
CLI-native long-term memory layer for AI agents. Gives Hermes persistent memory over its own session history with minimal overhead.
Quick answer
TraceCC is a CLI-native long-term memory layer that gives an agent persistent recall over its own session history with minimal overhead. For Hermes users it is an alternative or supplement to the built-in memory, aimed at keeping context across sessions without heavy infrastructure.
TraceCC is a lightweight, CLI-first take on agent memory: persistent recall over session history with minimal overhead, for people who want continuity without a database to run.
Features
- ✓CLI-native
- ✓Long-term memory
- ✓Session history tracking
- ✓Minimal overhead
Why this tool matters
Long-term memory is what separates a useful agent from a stateless chatbot. TraceCC focuses on persisting an agent's own session history so context survives restarts — the continuity Hermes users care about most.
Its selling point is low overhead. Heavier memory systems add tokens and moving parts; a minimal, CLI-native layer keeps the cost and complexity down, which matters because memory and skill indexes already account for a large share of per-call tokens.
Hermes ships its own memory under ~/.hermes, so TraceCC is best understood as an alternative philosophy — lean and history-focused — rather than a required add-on. Evaluate it against the built-in system for your workload before swapping.
For users who found general-purpose memory frameworks fiddly to wire into an agent's automatic save/recall flow, a purpose-built, CLI-native layer is an attractive middle ground between no memory and a full vector stack.
Best use cases
FAQ
Hermes ships memory under ~/.hermes; TraceCC is an alternative, history-focused philosophy with minimal overhead. Evaluate it against the built-in system for your workload rather than assuming it's required.
Memory and skill indexes already make up a large share of per-call tokens. A lean memory layer keeps that overhead — and your bill — down compared with heavier systems.
Yes — a CLI-native layer is a middle ground between no memory and a full vector stack, aimed at the automatic save/recall flow that general frameworks make awkward.