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Explain a credit decision for an applicant and draft a grounded adverse-action notice. Usage /explain <applicant>
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
| name | explain |
| description | Explain a credit decision for an applicant and draft a grounded adverse-action notice. Usage /explain <applicant> |
Run the attribute → check → write loop and save a report.
python -m tools.attribute "<applicant>" > reports/_attribution.json
Read it; note the decision, probability, and the most negative features.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.decision == "approve", write a short approval note; no adverse-action reasons.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.reports/<applicant>.md:
phi,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.Value a public company's equity end-to-end (FCFE at CAPM cost of equity) with an IB deal team — multi-year EDGAR data, scenario forecasting, Monte-Carlo DCF, dual-source comps, a verification gate, and an investment-committee sign-off. Run `/valuation <cik|ticker>`.
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