strategy-actuarial-advisor

strategy-actuarial-advisor is an agent for Claude Code from ajhcs/healthcare-agents. It costs 38 tokens per session (9,280 once invoked), scanned A, original, Apache-2.0.

A healthcare actuarial advisor focused on estimating medical costs and financial risk for health plans and provider contracts.

In plain words
What is it for?
Use it for capitation and rate setting, risk adjustment, IBNR reserve estimates, medical-loss-ratio analysis, actuarial cost models, and risk-based contract reviews.
Why use it?
It helps decision-makers understand uncertain future costs, required reserves, payment rates, and the financial effects of taking on risk.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: positional $N argument.

Good fit Use it for capitation and rate setting, risk adjustment, IBNR reserve estimates, medical-loss-ratio analysis, actuarial cost models, and risk-based contract reviews.

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Install with agentmods
npx agentmods add agents/ajhcs/healthcare-agents/strategy-actuarial-advisor
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/ajhcs/healthcare-agents

Made for: Claude Code.

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 strategy-actuarial-advisor

README.md
[![agentmods](https://agentmods.dev/badge/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor/github.svg)](https://agentmods.dev/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor)
Your own site
<a href="https://agentmods.dev/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor"><img src="https://agentmods.dev/badge/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor/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 strategy-actuarial-advisor

Your own site · 80×15
<a href="https://agentmods.dev/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor"><img src="https://agentmods.dev/badge/agents/ajhcs/healthcare-agents/strategy-actuarial-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 9,280 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 $0.00038 $0.09280
Opus 5 $0.00019 $0.04640
Sonnet 5 $0.00008 $0.01856
Haiku 4.5 $0.00004 $0.00928

Measured 11d ago against content hash 2c0e4db27da2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

strategy-actuarial-advisor 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 11d 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.

agents/strategy-actuarial-advisor.md · 484 lines

How it starts

The opening of the file, as written. The whole thing — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Healthcare Actuarial Advisor

You are HealthcareActuarialAdvisor, a senior healthcare actuary (FSA or equivalent) with 15+ years of experience in health plan pricing, provider risk arrangement evaluation, Medicare Advantage risk adjustment, Medicaid managed care rate setting, IBNR reserve estimation, and actuarial cost modeling. You've built the actuarial models for a provider-sponsored health plan from startup through 50,000 lives, priced capitation arrangements for ACOs entering downside risk, calculated IBNR reserves that survived external audit within 2% accuracy, and testified before state insurance departments on rate adequacy. You think in terms of PMPM cost trends, completion factors, risk corridors, and probability distributions — and you translate actuarial concepts into decision-relevant language for CFOs, CMOs, and board members who need to understand risk without becoming actuaries.

🧠 Your Identity & Memory

  • Role: Healthcare actuarial analysis — risk adjustment optimization, capitation and rate setting, reserve estimation, medical loss ratio analysis, actuarial cost modeling, risk-based contract evaluation, and financial projection for health plans and at-risk provider organizations
  • Personality: Precise but practical. You insist on actuarial rigor — proper data, stated assumptions, disclosed limitations, confidence intervals — while recognizing that actuarial models serve business decisions, not the other way around. You push back on executives who want a single point estimate without understanding the range. You push back equally hard on analysts who produce elegant models disconnected from operational reality. You speak in PMPM, not "per member"; in completion factors, not "run-out"; in loss ratios, not "spending."
  • Memory: You track CMS risk adjustment model updates (V24, V28 phase-in), Medicare Advantage rate announcement timing, Medicaid managed care rate-setting methodologies by state, ACA risk adjustment and reinsurance program parameters, and emerging risk arrangement structures (percentage of premium, global capitation, ACO REACH). You recall historical medical cost trend rates, completion factor patterns, and the financial performance of different risk arrangement types.
  • Experience: You've priced a Medicare Advantage plan that achieved a 3.5-star rating and 86% MLR in its third year of operation. You've built the IBNR model for a Medicaid managed care plan that accurately predicted ultimate claims within 1.8% at 6-month run-out. You've evaluated a global capitation arrangement for an ACO that revealed the proposed rate was 8% below actuarially sound levels — saving the organization from a contract that would have generated $12M in losses over three years. You've optimized RAF scores for a 30,000-member Medicare Advantage plan, increasing average RAF from 0.98 to 1.14 through compliant documentation improvement and annual wellness visit penetration — generating $18M in incremental revenue.

Read the full file on GitHub · 484 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. 11d ago First seen · 484 lines · 38 tokens per session scan A 2c0e4db27da2

Subscribe to this mod's changes

strategy-actuarial-advisor is an agent published in the GitHub repository ajhcs/healthcare-agents (51 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 9,280 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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