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 infraspecdev/tesseract --skill repo-reviewgit clone --depth 1 https://github.com/infraspecdev/tesseractWrote 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/infraspecdev/tesseract/repo-review)<a href="https://agentmods.dev/skills/infraspecdev/tesseract/repo-review"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/repo-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/infraspecdev/tesseract/repo-review"><img src="https://agentmods.dev/badge/skills/infraspecdev/tesseract/repo-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 | $0.00029 | $0.00943 |
| Opus 5 | $0.00015 | $0.00472 |
| Sonnet 5 | $0.00006 | $0.00189 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
atmos-repo-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 7d 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.
This is a copy
100% identical to atmos-repo-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Atmos Repository Review
Overview
Structured review of Atmos infrastructure repositories with file-based analysis and implementation planning.
Core principle: Analysis and plans are ALWAYS persisted to files, even on re-reviews. Never skip writing files.
When to Use
- Reviewing an Atmos components or stacks repository
- Evaluating Terraform/OpenTofu infrastructure organization
- Assessing IaC repository for Atmos best practices
- Onboarding to understand existing Atmos setup
- Re-grading after improvements (creates fresh analysis.md and plan.md)
When NOT to Use
- Reviewing a single Terraform module that is not part of an Atmos repo
- General Terraform code review without Atmos structure concerns
- Reviewing Helm charts, Kubernetes manifests, or non-IaC code
- Quick one-off questions about Atmos configuration syntax
- The user explicitly asks for a non-structured review or casual feedback
Workflow
Explore -> Questions (skip if known) -> Evaluate -> Write analysis.md -> Write plan.md
-> Ask User: [proceed | stop | edit plan] -> Review Plan -> Execute Step by Step
Critical Rules
- ALWAYS write analysis.md — Even on re-reviews, create fresh analysis
- ALWAYS write plan.md — Even if no P0 issues, document P1/P2 improvements
- ALWAYS ask user before executing — Never auto-proceed to execution
- Show the user what was written — Summarize key findings after writing files
Workflow Steps
1. Explore Repository
Use Glob, Read, and file exploration to understand structure. Check for: atmos.yaml, stacks/, components/terraform/, catalog/, CI/CD config, version constraints, provider/backend files, pre-commit hooks, terraform-docs setup, release tooling, and per-component versioning strategy.
Identify repo type: components-only, stacks-only, or monorepo.
2. Ask Clarifying Questions
On first review, ask 10-15 questions covering architecture, scale, operations, development, and governance. Skip on re-review if context is known. See templates.md for question categories.
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.
- 7d ago First seen · 87 lines · 29 tokens per session scan A 1d20d606dc21
atmos-repo-review is a skill published in the GitHub repository infraspecdev/tesseract (5 stars, last pushed 2mo ago), licensed MIT. It adds 29 tokens to every session and 943 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to atmos-repo-review, differing in 0 lines, and is treated as a copy.
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