explain

name	explain
description	Explain a credit decision for an applicant and draft a grounded adverse-action notice. Usage /explain <applicant>

/explain

Run the attribute → check → write loop and save a report.

1. Attribute (attributor agent): python -m tools.attribute "<applicant>" > reports/_attribution.json Read it; note the decision, probability, and the most negative features.
2. Check (checker agent): python -m tools.check --attribution reports/_attribution.json If ok is false, stop and re-run step 1 — a non-additive attribution is not faithful and may not be used.
3. Decide the format:
   • If decision == "approve", write a short approval note; no adverse-action reasons.
   • If decision == "deny", write an adverse-action notice (adverse-action-writer agent): the principal reasons are the features with the most negative phi, at most four, each cited by its adverse_action_reason. Never cite a protected attribute.
4. Save to reports/<applicant>.md:
   • the decision and predicted probability (from the tool),
   • the principal reasons, each tied to its feature key and phi,
   • the additivity gap from step 2,
   • a one-line statement that every reason came from the attribution tool.

Every factor in the notice must come from reports/_attribution.json. No outside reasons, no protected attributes, no numbers the tool did not produce.

Try these to start:

• /explain alice ← denied; recent delinquencies dominate.
• /explain carol ← denied; high credit utilization dominates.
• /explain bob ← approved; no adverse-action reasons.