Launching today
Etch
Trace, replay, and verify every AI agent decision.
5 followers
Trace, replay, and verify every AI agent decision.
5 followers
Every AI agent decision (prompts, tool calls, edits, multi-agent handoffs) recorded into a tamper-evident, verifiable history. Debug why the agent did what it did without grepping text logs. When customers or auditors ask what your agent did on Tuesday, prove it in one link. Sits underneath whichever agent stack or context graph you already use. Works with Claude Code, Cursor, Codex, Continue, and any tool that emits webhook events.
The tamper-evident history part is really nice, especially for audit handoffs. One thing that would help a lot: let me pin a custom note or human decision onto a specific span in the timeline. Right now I can see what the agent did, but if I intervened mid-run or overrode a tool call, I want that context attached right next to it instead of buried in a separate log.
@gltenrd2p thanks for this. Appreciate the specific ask.
The underlying "world-model-mcp(https://github.com/SaravananJaichandar/world-model-mcp)" decisions table already carries source_tool and confirmer provenance fields, so the data model supports it. What's missing is a first-class primitive for pinning a human note or override rationale directly to a span in the timeline, signed into the same Merkle chain as the agent events. Right now those would land in the general events log, exactly the pattern you called out.
I'm going to prioritise this. A pin_annotation MCP tool that attaches author, rationale, and timestamp to an event range, signed the same way agent events are, feels like a clean addition.
One question back: would you need reviewers to filter human interventions from agent actions as a separate view, or is a single unified timeline with author metadata enough? Would shape whether annotation is a distinct event type or a field on the existing schema.