A protocol for auditing what happens when a human overrules an agent

Brightbeam AI's CHAP 0.2 gives agent-review workflows a structured record for the moment a human edits or rejects an agent's draft. Each override becomes a hash-chained envelope carrying a diff, a rationale, and a set of controlled-vocabulary tags, so an audit.read call can replay the full decision chain months later instead of someone reconstructing it from chat logs and ticket comments. The protocol's most useful idea is a two-way split: a refining override means the human agreed with the agent's decision but rewrote how it was expressed, while a substituting override means the human reached a different decision entirely. Brightbeam frames these as different failure modes needing different fixes: a high refining rate points at retrieval problems, a high substituting rate points at an ambiguous policy. The repository ships a TypeScript reference implementation (@chap/coordinator on npm), a CLI, an override-analytics tool, and a conformance harness with 21 test vectors that check the hash-chaining and signing behavior the spec promises. CHAP is built to sit next to MCP and A2A rather than replace them.

Why it matters: Teams running agents on review-heavy work now have a concrete shape to put override data in, instead of losing it to Slack threads and ticket comments, and the refining-versus-substituting split gives them a real diagnostic rather than a guess about whether a bad outcome traces to retrieval or to policy. The protocol is a young public draft with one reference implementation and no adoption track record yet, so treat it as a shape worth watching, not a standard to build on today.