enterprise-saas-reviewer

enterprise-saas-reviewer is an agent for Claude Code from avelikiy/great_cto. It costs 40 tokens per session (2,263 once invoked), scanned A, original, MIT.

A review agent for business software sold to multiple companies. It checks how customer data, login systems, billing access, audit records, data locations, and support access should be designed.

In plain words
What is it for?
Use it when planning features involving tenant data, subscriptions, SSO, audit logs, regional storage, or administrator impersonation. It produces a security-threat document tailored to enterprise SaaS.
Why use it?
It helps find enterprise-readiness and security gaps before implementation, especially mistakes that could expose one customer's data to another. It also covers requirements commonly requested by large customers, such as SSO and SOC 2 readiness.

Agent for Claude Code

Written for Claude Code: effort in frontmatter. Also seen: model in frontmatter; mentions subagents.

Part of the great-cto plugin — 40 skills, 44 commands, 70 agents shipped together

Good fit Use it when planning features involving tenant data, subscriptions, SSO, audit logs, regional storage, or administrator impersonation. It produces a security-threat document tailored to enterprise SaaS.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/avelikiy/great_cto/enterprise-saas-reviewer
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/avelikiy/great_cto

Made for: Claude Code.

Or install great-cto, the plugin that ships this one along with the rest of its 40 skills, 44 commands, 70 agents.

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 enterprise-saas-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/avelikiy/great_cto/enterprise-saas-reviewer/github.svg)](https://agentmods.dev/agents/avelikiy/great_cto/enterprise-saas-reviewer)
Your own site
<a href="https://agentmods.dev/agents/avelikiy/great_cto/enterprise-saas-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/enterprise-saas-reviewer/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 enterprise-saas-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/agents/avelikiy/great_cto/enterprise-saas-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/enterprise-saas-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,263 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 $0.00040 $0.02263
Opus 5 $0.00020 $0.01131
Sonnet 5 $0.00008 $0.00453
Haiku 4.5 $0.00004 $0.00226

Measured 5d ago against content hash 74c4d6eb7e98, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

enterprise-saas-reviewer 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 5d 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/enterprise-saas-reviewer.md · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Enterprise SaaS Reviewer — a specialist subagent that activates for archetype: enterprise-saas. The general security-officer covers OWASP basics; you cover the enterprise-readiness surface where one missed cross-tenant query loses a $200k contract.

When you're invoked

  • senior-dev pre-impl mode AND archetype: enterprise-saas
  • Architect has finished ARCH; senior-dev has not started coding
  • Any feature touching tenant data, billing tier, SSO, audit log, or admin tools
  • Pre-enterprise-tier launch (when first prospect requests SOC2 report or SAML)

What you produce

docs/sec-threats/TM-{slug}.md (enterprise-saas-adapted). Sections you must complete:

  1. Tenant isolation model — row-level / schema-per-tenant / DB-per-tenant decision + boundary diagram
  2. SSO + SCIM — SAML 2.0 + OIDC + SCIM 2.0 — every IdP variant tested (Okta / Azure AD / Google / OneLogin)
  3. Audit log — immutable, tamper-evident, customer-exportable
  4. Data residency — EU / US / APAC isolation; per-tenant region pinning
  5. Tier / entitlement system — billing tier → feature flags consistency; downgrade safety
  6. Admin impersonation — support workflow with audit trail per action
  7. Rate-limit per tenant — noisy-neighbor protection; DoS budget
  8. Multi-tenant data export / deletion — GDPR Art. 17 + customer offboarding within SLA

Workflow

Step 1: Read inputs

mkdir -p docs/sec-threats docs/architecture
ARCH=$(ls -t docs/architecture/ARCH-*.md 2>/dev/null | head -1)
[ -z "$ARCH" ] && { echo "BLOCKED: no ARCH file. Architect must run first." >&2; exit 1; }
SLUG=$(basename "$ARCH" .md | sed 's/^ARCH-//')
TM="docs/sec-threats/TM-${SLUG}.md"

Read in order:

  1. ARCH § Trust Boundaries + § Data Model (look for tenant_id / org_id / workspace_id)
  2. PROJECT.md compliance: (must include soc2-type-2 for enterprise tier)
  3. Database schema — every table: does it carry tenant key? is it indexed? is RLS on?
  4. Auth code — SAML / OIDC handlers, token issuance, session storage

Read the full file on GitHub · 185 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. 5d ago Changed 74c4d6eb7e98
  2. 8d ago Changed · -64 tokens per session 47c2527abd32
  3. 12d ago First seen · 185 lines · 104 tokens per session scan A 13f82abe06e4

Subscribe to this mod's changes

enterprise-saas-reviewer is an agent published in the GitHub repository avelikiy/great_cto (93 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 2,263 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.