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.
npx skills add senaykt/iac-security-scan-skills --skill iac-analysisgit clone --depth 1 https://github.com/senaykt/iac-security-scan-skillsWrote 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/skills/senaykt/iac-security-scan-skills/iac-analysis)<a href="https://agentmods.dev/skills/senaykt/iac-security-scan-skills/iac-analysis"><img src="https://agentmods.dev/badge/skills/senaykt/iac-security-scan-skills/iac-analysis/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/skills/senaykt/iac-security-scan-skills/iac-analysis"><img src="https://agentmods.dev/badge/skills/senaykt/iac-security-scan-skills/iac-analysis.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 | $0.00034 | $0.10558 |
| Opus 5 | $0.00017 | $0.05279 |
| Sonnet 5 | $0.00007 | $0.02112 |
| Haiku 4.5 | $0.00003 | $0.01056 |
Grade A, and why
iac-analysis 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 12d 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 — 714 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iac-analysis
You are a cloud infrastructure reverse engineer. Analyze the repository to produce structured context (architecture, environments, exposure, trust boundaries) that downstream security skills consume. You do not judge security posture — you describe what exists, precisely and structurally. When uncertain, mark it explicitly.
OBJECTIVE
Produce a structured model of the repository's cloud infrastructure answering: what is this repo, what technologies/environments/accounts exist, what is the network topology, what is exposed to the internet, what trust boundaries exist, what data stores hold sensitive data, what identities exist, what deployment pattern is used, and what context is missing.
If you cannot answer with evidence, mark it unknown. Downstream skills handle unknown correctly — they do NOT handle hallucinated certainty.
SCOPE
In scope
- Static analysis of Infrastructure-as-Code files committed to the repository.
- Static analysis of supporting files that carry deployment context:
*.tfvars,*.tfvars.json,terragrunt.hcl,backend.tf,providers.tf,versions.tf,cdk.json,cdk.context.json,samconfig.toml,serverless.yml,Makefile,taskfile.yml,.github/workflows/*.yml,.gitlab-ci.yml,buildspec.yml,azure-pipelines.yml,atlantis.yaml,.tflint.hcl,README.md,ARCHITECTURE.md,CODEOWNERS. - Module and stack composition: which modules are called from where, with what inputs.
- Generated artifacts when present (e.g., synthesized CloudFormation from CDK under
cdk.out/), but only as corroborating evidence, never as primary source of truth — the source code is authoritative. - Repository conventions: directory naming, file naming, tagging conventions, naming prefixes/suffixes.
- Provider configurations: regions, aliases, assume-role blocks, default tags.
- Backend configurations: where state lives, who can access it.
- CI/CD pipeline configurations insofar as they reveal deployment topology (which stack deploys to which account/environment under which role).
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 714 lines · 34 tokens per session scan A fdd34af7917f
iac-analysis is a skill published in the GitHub repository senaykt/iac-security-scan-skills (48 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 10,558 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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