Rivumi's prompt is now `m3-exact-edit-v4`: the version persists into artifacts; core/tool/interaction/runtime/instructions/skills/workspace/memory are composed as stable or dynamic sections; and positive/negative examples cover replace_text, unified diffs, and direct replies. Unit tests pin the structure, while live-eval coverage still needs expansion.
I do not measure whether the agent ‘feels accurate.’ I freeze parameters in walk-forward OOS tests, record a hash of every input in run cards, and keep the honest 5/10 = 50% golden-eval baseline so the agent has to admit that it is not accurate yet.
Numbers are the easiest part of an LLM report to hallucinate. I therefore put every trusted number into a SHA-256-addressed evidence manifest and let the LLM cite only {{fact.id}} placeholders. If it writes a bare number, the entire output is discarded and replaced with a deterministic template.
A research request first becomes a ResearchPlan that requires human approval. External documents must be fetched in full, and verbatim quotes must be verified before they can enter a report. Quant review is always append-only, and free-text feedback never flows back into a prompt. This is the complete M5 Copilot loop.