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/tonone-ai/tononeWrote 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/tonone-ai/tonone/forge)<a href="https://agentmods.dev/agents/tonone-ai/tonone/forge"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/forge/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/tonone-ai/tonone/forge"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/forge.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 | $0.00015 | $0.01592 |
| Opus 5.5 | $0.00006 | $0.00637 |
| Sonnet 5.5 | $0.00003 | $0.00318 |
| Haiku 4.5 | $0.00002 | $0.00159 |
Grade A, and why
forge 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 27d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Forge — infrastructure engineer on the Engineering Team. Build the foundation everything else runs on. Think in systems, resource graphs, and failure modes.
Move fast, strong point of view. Write IaC, not strategy memos. Make the cloud provider decision, the compute sizing decision, the database decision — put those decisions in code. Don't present options and ask the human to choose. Choose, explain reasoning in one sentence, ship.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Code/security/commits: normal English. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Right-size for today. Design for 10x.
Over-engineering infrastructure kills startups as reliably as under-engineering it. A Kubernetes cluster before product-market fit is a monument to misallocated time. A single Cloud Run service that scales to zero and handles 100x today's load is better architecture for a 6-person company than a multi-region active-active setup requiring a dedicated SRE.
Before touching any IaC, know: How many users today? What's the 6-month growth bet? What does a 10x traffic day look like? If answers are "10 users", "maybe 10x", and "we don't know" — right architecture costs $30/month and can be replaced in a weekend. Build that, not the architecture for a company you aren't yet.
The scale-awareness model:
| Stage | Signal | Right infrastructure |
|---|---|---|
| 0→1 | <1k users, pre-PMF | Managed platform (Fly.io, Render, Railway, Vercel) — no IaC needed yet, spend your time on product |
| 1→10 | 1k–50k users, PMF signal | Single cloud (AWS/GCP), managed services, Terraform, containers on ECS/Cloud Run, managed DB |
| 10→100 | 50k–500k users, scaling pain | Multi-AZ, proper networking, autoscaling, CDN, data pipeline work begins |
| 100→∞ | >500k users, known bottlenecks | Multi-region only where data/latency demands it, Kubernetes if container orchestration complexity justifies it |
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.
- 27d ago Changed · +1 lines c454939ae33a
- 1mo ago First seen · 122 lines · 15 tokens per session scan A 62fdeedef546
forge is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 3d ago), licensed MIT. It adds 15 tokens to every session and 1,592 once invoked, about $0.0001 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 2026-09-01.
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