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 cnfeat/top-pm-skills --skill infra-as-code-reviewgit clone --depth 1 https://github.com/cnfeat/top-pm-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/cnfeat/top-pm-skills/infra-as-code-review)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/infra-as-code-review"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/infra-as-code-review/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/cnfeat/top-pm-skills/infra-as-code-review"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/infra-as-code-review.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 | $0.00079 | $0.03163 |
| Opus 5.5 | $0.00032 | $0.01265 |
| Sonnet 5.5 | $0.00016 | $0.00633 |
| Haiku 4.5 | $0.00008 | $0.00316 |
Grade A, and why
infra-as-code-review 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infrastructure-as-Code Review
Produce a structured infrastructure-as-code review that applies security, reliability, and operational quality standards to a specific body of IaC code. The output serves two purposes: an actionable review report for the code at hand (with findings by severity and specific remediation steps), and a reusable checklist the team can apply to every future IaC change. If the user provides actual code, analyze it and populate the findings table with real issues. If no code is provided, produce the checklist and a template findings report.
Required Inputs
Ask for these if not already provided:
- IaC tool — Terraform, CloudFormation, Pulumi, Ansible, or CDK
- Cloud provider — AWS, GCP, Azure, or multi-cloud
- What the code provisions — a brief description (e.g., "VPC, EKS cluster, and RDS instance for the payments service")
- Security policies or naming standards in use — any existing org standards to check against; if none, use sensible defaults
- The IaC code itself — paste or describe it; if not provided, produce the checklist template only and note findings require code
Output Format
IaC Review Report: [What Is Being Provisioned]
Reviewer: [Name / Claude] IaC Tool: [Terraform / CloudFormation / Pulumi / Ansible / CDK] Cloud Provider: [AWS / GCP / Azure] Code Location: [Repo path or PR link] Review Date: [Date] Overall Risk: [Critical / High / Medium / Low]
Executive Summary
| Severity | Finding Count | Resolved in This Review | Carry-Over Risk |
|---|---|---|---|
| Critical | [n] | [n] | [Yes/No — explain] |
| High | [n] | [n] | [Yes/No — explain] |
| Medium | [n] | [n] | [Yes/No — explain] |
| Low | [n] | [n] | [Yes/No — explain] |
| Total | [n] | [n] |
Recommendation: [Approve / Approve with Required Changes / Block — one sentence rationale]
Findings
Critical Findings
CRIT-01: [Finding Title]
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 · 301 lines · 79 tokens per session scan A d46046e1d353
infra-as-code-review is a skill published in the GitHub repository cnfeat/top-pm-skills (55 stars, last pushed 4mo ago), licensed MIT. It adds 79 tokens to every session and 3,163 once invoked, about $0.0003 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.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…