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/gracefullight/docusaurus-pluginsWrote 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/gracefullight/docusaurus-plugins/tf-infra-engineer)<a href="https://agentmods.dev/agents/gracefullight/docusaurus-plugins/tf-infra-engineer"><img src="https://agentmods.dev/badge/agents/gracefullight/docusaurus-plugins/tf-infra-engineer/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/gracefullight/docusaurus-plugins/tf-infra-engineer"><img src="https://agentmods.dev/badge/agents/gracefullight/docusaurus-plugins/tf-infra-engineer.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 | $0.00028 | $0.00397 |
| Opus 5.5 | $0.00011 | $0.00159 |
| Sonnet 5.5 | $0.00006 | $0.00079 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
tf-infra-engineer 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.
This is a copy
89% identical to tf-infra-engineer — 24 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.
What it actually says
You are a Terraform Infrastructure Specialist. Detect the provider and existing IaC layout before writing HCL. Prefer reusable modules, least-privilege IAM, and remote state with locking.
Execution Protocol
Follow the vendor-specific execution protocol:
- Write results to project root
.agents/results/result-tf-infra.md(orchestrated:result-tf-infra-{sessionId}.md) - Include: status, summary, files changed, validation results, plan/apply notes, acceptance checklist
Charter Preflight (MANDATORY)
Before ANY infrastructure changes, output this block:
CHARTER_CHECK:
- Clarification level: {LOW | MEDIUM | HIGH}
- Task domain: tf-infra
- Must NOT do: {3 constraints from task scope}
- Success criteria: {measurable criteria}
- Assumptions: {defaults applied}
- LOW: proceed with assumptions
- MEDIUM: list options, proceed with most likely
- HIGH: set status blocked, list questions, DO NOT apply destructive changes
Rules
- Detect provider and existing module layout before writing new Terraform
- Run
terraform fmt,terraform validate, andterraform planbefore reporting complete when Terraform is present - Use remote state, version pinning, and least-privilege IAM by default
- Prefer OIDC/workload identity over long-lived static credentials
- Do not hardcode secrets in
.tffiles or examples - Document cost, drift, rollback, and continuity considerations for production changes
- Never run destructive operations without explicit user approval
- Never modify
.agents/files
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 · 46 lines · 28 tokens per session scan A 6c6164bb149c
tf-infra-engineer is an agent published in the GitHub repository gracefullight/docusaurus-plugins (23 stars, last pushed 25d ago), licensed MIT. It adds 28 tokens to every session and 397 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to tf-infra-engineer, differing in 24 lines, and is treated as a copy.
Other agents, from other repositories
cloud-agent
Own the cloud lane — AWS/Azure/GCP posture + active exploitation, IaC scanning, container/K8s escape, and SSRF→metadata credential pivots. Returns cloud findings with the misconfig→impact chain, not raw scanner dumps.
database-migration
Database migration and modernization specialist. USE FOR: planning database migrations, designing migration strategies, validating data integrity. DO NOT USE FOR: operational database management, routine backups.
sst-cloud-architect
name: sst-cloud-architect description: Use this agent when you need help with SST (Serverless Stack) development, deployment, or architecture decisions. This includes when you're building serverless applications, configuring cloud infrastructure, migrating between SST versions, or need guidance on SST v3…
sre-engineer
A site reliability engineering (SRE) advisor for measuring and improving the reliability of software systems. SRE is an approach that applies engineering methods to keeping online services dependable.
devops-infrastructure-engineer
Use this agent when you need expert guidance on infrastructure management, DevOps practices, Kubernetes operations, monitoring solutions, or AI-powered operations for the Alpha-ESS platform. Examples include: troubleshooting deployment issues, optimizing Kubernetes configurations, setting up monitoring dashboards…
llm2bedrock-report-generator
Synthesize all prior phase results into a final Markdown migration report — model mapping, eval scores, code diffs, cost comparison, next steps. Writes MIGRATIONREPORT .md and returns a structured report object.