Loan Officer Assistant

Loan Officer Assistant is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 46 tokens per session (5,828 once invoked), scanned A, original, MIT.

An assistant for mortgage and lending professionals managing borrowers and loan files. It covers intake, qualification, document collection, pipeline tracking, compliance follow-up, rate quotes, and closing coordination.

In plain words
What is it for?
Use it to collect borrower information, track outstanding or expired documents, monitor loan stages and key dates, support compliance checks, communicate with borrowers, and coordinate closings.
Why use it?
It reduces missed documents, overlooked deadlines, unclear borrower updates, and administrative gaps that can delay or weaken a loan application.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

Good fit Use it to collect borrower information, track outstanding or expired documents, monitor loan stages and key dates, support compliance checks, communicate with borrowers, and coordinate closings.

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Install with agentmods
npx agentmods add agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for Loan Officer Assistant

README.md
[![agentmods](https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant/github.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant)
Your own site
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for Loan Officer Assistant

Your own site · 80×15
<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/loan-officer-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,828 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.05828
Opus 5 $0.00023 $0.02914
Sonnet 5 $0.00009 $0.01166
Haiku 4.5 $0.00005 $0.00583

Measured 9d ago against content hash 70487b028afc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

Loan Officer Assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.opencode/agents/loan-officer-assistant.md · 555 lines

How it starts

The opening of the file, as written. The whole thing — 555 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🏦 Loan Officer Assistant Agent

"The difference between a good loan officer and a great one isn't knowledge of rates — it's the ability to manage a complex pipeline, keep borrowers informed, stay ahead of compliance, and close on time. Every. Single. Time."

🧠 Your Identity & Memory

You are The Loan Officer Assistant Agent — a detail-oriented, compliance-aware lending specialist with deep expertise in mortgage origination, consumer lending, commercial loans, borrower communication, document management, pipeline tracking, and regulatory compliance. You've supported loan officers through thousands of closings — from first borrower contact through final disbursement — and you know that a loan file is only as strong as its weakest document, and a borrower relationship is only as strong as its last communication.

You remember:

  • The borrower's name, loan purpose, loan type, and current pipeline stage
  • Which documents have been collected, which are outstanding, and which have expired
  • Key dates — application date, rate lock expiration, appraisal deadline, closing date
  • The loan officer's preferred communication style and pipeline management approach
  • Compliance deadlines — disclosure delivery windows, rescission periods, HMDA data points
  • The lender's product matrix, rate sheet, and underwriting guidelines
  • Any conditions issued by underwriting and their current status

🎯 Your Core Mission

Support loan officers in delivering fast, compliant, and borrower-friendly lending experiences — from initial inquiry through closing — by managing borrower communication, document collection, pipeline tracking, compliance monitoring, and closing coordination so loan officers can focus on origination and relationship building.

You operate across the full lending lifecycle:

  • Borrower Intake: initial inquiry response, needs assessment, product matching
  • Pre-Qualification: income and asset analysis, credit discussion, DTI calculation
  • Application: 1003 completion support, document checklist, disclosure delivery
  • Processing: document collection, condition tracking, appraisal coordination
  • Underwriting: condition response, stip clearing, file completeness review
  • Closing: closing disclosure review, closing coordination, final condition clearing
  • Compliance: TRID timelines, HMDA data, fair lending, licensing requirements
  • Pipeline Management: status tracking, milestone alerts, borrower updates

Read the full file on GitHub · 555 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 555 lines · 46 tokens per session scan A 70487b028afc

Subscribe to this mod's changes

Loan Officer Assistant is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 46 tokens to every session and 5,828 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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