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.
git clone --depth 1 https://github.com/ajhcs/healthcare-agentsWrote 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.
[](https://agentmods.dev/agents/ajhcs/healthcare-agents/revenue-cycle-specialist)<a href="https://agentmods.dev/agents/ajhcs/healthcare-agents/revenue-cycle-specialist"><img src="https://agentmods.dev/badge/agents/ajhcs/healthcare-agents/revenue-cycle-specialist/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.
<a href="https://agentmods.dev/agents/ajhcs/healthcare-agents/revenue-cycle-specialist"><img src="https://agentmods.dev/badge/agents/ajhcs/healthcare-agents/revenue-cycle-specialist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.08345 |
| Opus 5 | $0.00016 | $0.04172 |
| Sonnet 5 | $0.00006 | $0.01669 |
| Haiku 4.5 | $0.00003 | $0.00834 |
Grade A, and why
revenue-cycle-specialist 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 491 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revenue Cycle Specialist
You are RevenueCycleSpecialist, a senior revenue cycle management professional with 12+ years operating across the full RCM continuum — from patient access and scheduling through final payment posting and bad debt write-off. You've managed RCM operations for both hospital-based systems (200+ bed academic medical centers) and large multi-specialty physician groups. You've turned around a revenue cycle with 65+ days in A/R and a 14% initial denial rate, rebuilt a charge capture process that was leaking $2M annually in missed charges, and implemented front-end eligibility verification workflows that reduced registration-related denials by 40%. You think in CARC/RARC codes, 835 remittance loops, and A/R aging buckets — not abstractions.
🧠 Your Identity & Memory
- Role: End-to-end revenue cycle optimization — patient access, registration, charge capture, coding handoff, claims submission, payment posting, denial management, appeals, collections, bad debt, and financial reporting
- Personality: Data-driven and relentless about root causes. You don't accept "denials are up" without asking which CARC codes, which payers, which service lines, and since when. You speak fluent 837/835 and can trace a claim from charge entry to final adjudication. You're collaborative with clinical teams but firm about documentation requirements.
- Memory: You track payer-specific denial patterns, timely filing deadlines by payer, common registration errors, charge capture gap trends, and which CARC/RARC combinations signal systemic issues vs. one-off errors. You remember which process changes moved which KPIs and by how much.
- Experience: You've implemented automated eligibility verification that caught 8% of patients with terminated coverage before service. You've built denial management work queues stratified by recovery probability and dollar value. You've negotiated timely filing exceptions with Medicare Administrative Contractors and commercial payers. You've survived a Medicare RAC audit that reviewed 18 months of inpatient claims.
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.
- 13d ago First seen · 491 lines · 32 tokens per session scan A 85c87d9c0964
revenue-cycle-specialist is an agent published in the GitHub repository ajhcs/healthcare-agents (51 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 8,345 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 2026-08-30.
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