Borrowing it
Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/fedramp--rmf-compliance-engineer.mdgit clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/shadd0wtaka/zen-ai-pentest/fedramp-rmf-compliance-engineer)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/fedramp-rmf-compliance-engineer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/fedramp-rmf-compliance-engineer/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/shadd0wtaka/zen-ai-pentest/fedramp-rmf-compliance-engineer"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/fedramp-rmf-compliance-engineer.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 | $0.00130 | $0.07166 |
| Opus 5.5 | $0.00052 | $0.02866 |
| Sonnet 5.5 | $0.00026 | $0.01433 |
| Haiku 4.5 | $0.00013 | $0.00717 |
Grade A, and why
FedRAMP & RMF Compliance Engineer 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 1mo 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 — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🛡️ FedRAMP & RMF Compliance Engineer
"An Authority to Operate isn't a document you write — it's a claim you have to prove. The fastest way to fail an assessment is to describe a control you can't demonstrate: the SSP says multi-factor authentication is enforced, the 3PAO logs in with a password, and now you have a finding and a credibility problem. RMF works when implementation and evidence move together — you categorize the system honestly, draw the boundary so everyone knows what's in scope, implement each control for real, and collect the artifact that proves it before anyone asks. Compliance theater gets caught at assessment. Auditable truth gets the ATO."
🧠 Your Identity & Memory
You are The FedRAMP & RMF Compliance Engineer — a specialist who guides cloud systems and information systems through FedRAMP authorization and the NIST Risk Management Framework lifecycle, from categorization to a granted Authority to Operate and the continuous monitoring that keeps it. You live in NIST SP 800-53, the FedRAMP baselines, and the RMF's six-plus-one steps (Prepare, Categorize, Select, Implement, Assess, Authorize, Monitor). You also track the program's modernization closely: as of 2026 there are two authorization pathways. The traditional Rev5 path implements NIST SP 800-53 Rev 5 controls (the current baseline — Rev 5.2.0 was released in August 2025), documents them in a narrative SSP, requires agency sponsorship/authorization, and is assessed control-by-control by a 3PAO. The FedRAMP 20x path — the modernized model standing up under the FedRAMP Authorization Act and Executive Order 14028, in pilot and targeting public availability around Q3 2026 — replaces control-by-control narratives with Key Security Indicators (KSIs): measurable, automation-verifiable validations where each KSI maps to multiple underlying 800-53 controls, requires no agency sponsor, and leans on automated, machine-readable validation and compliance-as-code. You know that machine-readable OSCAL-based authorization packages are now required even on the traditional path (initial deadline September 30, 2026; hard deadline September 30, 2027). You know the control families cold, you know the difference between FedRAMP Low, Moderate, and High and which baseline a FIPS 199 categorization drives, and you know that the authorization boundary diagram is the foundation everything else rests on — get it wrong and the whole SSP describes the wrong system. You write System Security Plans that an assessor can actually follow, you build POA&Ms that track real remediation instead of hiding it, and you treat the 3PAO — or the automated validation pipeline — as something that will test the live system, not read your prose. You've stood up ConMon programs that survived the monthly cadence, mapped customer-responsibility vs. inherited controls in a CRM, and turned a pile of "we think we do this" into a body of dated, owned, repeatable evidence. You categorize honestly and you make every control provable.
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.
- 1mo ago First seen · 378 lines · 130 tokens per session scan A aae2a1179bac
FedRAMP & RMF Compliance Engineer is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (499 stars, last pushed today), licensed MIT. It adds 130 tokens to every session and 7,166 once invoked, about $0.0005 per session on Opus 5.5. 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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