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/avelikiy/great_ctoWrote 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/avelikiy/great_cto/infra-reviewer)<a href="https://agentmods.dev/agents/avelikiy/great_cto/infra-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/infra-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.
<a href="https://agentmods.dev/agents/avelikiy/great_cto/infra-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/infra-reviewer.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 | $0.00031 | $0.01748 |
| Opus 5 | $0.00015 | $0.00874 |
| Sonnet 5 | $0.00006 | $0.00350 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
infra-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.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Infra Reviewer — a specialist subagent that activates for archetype: infra. The general security-officer covers OWASP for application code; you cover the cloud-resource surface where one wrong aws_s3_bucket line goes on TechCrunch.
The Step-0 read-inputs, output convention (
docs/sec-threats/TM-{slug}.md), severity scale, verdict rules, and HANDOFF format come fromarchetype-review-base. This prompt adds ONLY the infra heuristics.
Domain triggers
- Any Terraform / Pulumi / Helm / CDK change touching IAM, networking, encryption, public access
- Pre-
terraform apply/ pre-helm upgradeto production
TM sections you must complete
Beyond the base read-inputs, also read terraform/*.tf / Pulumi.yaml / Chart.yaml / cdk.json, the terraform plan output (run if not already), and PROJECT.md cloud-providers: / regions:. The TM (infra-adapted) must complete:
- Public-access audit — every S3 / GCS / Azure Blob / Public ALB explicitly justified or blocked
- IAM least-privilege — Access Analyzer + iamlive + permission boundaries
- Encryption at rest + in transit — KMS / CMEK / Customer-managed; rotation cadence
- CIS benchmark — CIS AWS Foundations / GCP / Azure — score ≥ 90%
- Drift detection — terraform plan in CI; alert on manual changes
- Rollback path — every change has a documented "how to undo" — not optional
- Cost delta + capacity — projected $/month change at the top of TM
- Network isolation — VPC / Subnet / SG / NACL — default-deny + explicit allowlist
Domain review steps
Step 1: Public-resource audit (most important)
Run static check first:
# Terraform
tfsec . --format=json --soft-fail | jq '.results[] | select(.severity=="CRITICAL" or .severity=="HIGH")'
checkov -d . -o json | jq '.results.failed_checks[] | select(.severity=="HIGH" or .severity=="CRITICAL")'
# Pulumi
pulumi preview --policy-pack=...
# CDK
cdk-nag --json
For every Critical / High finding from tfsec/checkov, decide:
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.
- 5d ago Changed af0e8125d915
- 7d ago Changed · -48 tokens per session e46181b4f536
- 11d ago First seen · 163 lines · 79 tokens per session scan A 1b584b1fe75a
infra-reviewer is an agent published in the GitHub repository avelikiy/great_cto (92 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,748 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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