Evidence and the snapshot

Before you start

Two things get fixed, at two moments: the success criteria when you approve the experiment, and the evidence when you complete the tracker. Fixing them is what makes the result trustworthy later.

Steps

1. Criteria are fixed on approval

   Once the experiment is approved, the success criteria can't move. The result can only be read against the criteria you set before you saw any data.

2. Evidence is saved as a snapshot

   Complete tracker saves the rows as a fixed snapshot and completes the experiment. The Learning, its insights and the decision all point at that snapshot, so anyone can check exactly what you were looking at.

3. You call the result

   SwiftCNS drafts observations from the snapshot. Then you say whether the result Met the criteria, did Not met, or is Unclear. If the evidence is thin, say so: Unclear, followed by Test again, is an honest record.

What you get

In the running example, 15 rows were saved. The success criteria were 3 of 15 paying within 7 days; 4 did. SwiftCNS also noted that one more or one fewer payment would flip the result, and that a late payer (day 10) fell outside the window. The team called it Met and said in the Learning that the margin was small.

A Not met result is a result too. It tells you where not to spend the next quarter.

Done when

• You can point to the approved criteria and the snapshot behind any decision.

Common mistakes

• Wanting to edit rows after completing. Run a follow-up experiment instead; the old snapshot stays.
• Calling Not met a failure. The failure is spending the quarter without knowing.

For agents: MCP tools and gotchas

• complete_experiment saves the snapshot; its id appears as snapshotDocumentId on get_data_tracker and get_learning.
• list_evidence_assessments returns history from the retired sufficiency step only.
• An upload or attachment alone never approves or publishes evidence.

Next

MCP server reference.