Borrowing it
Nothing to install: this file belongs to tonone-ai/tonone. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tonone-ai/tonone/main/AGENTS.mdgit 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/instructions/tonone-ai/tonone/agents-md)<a href="https://agentmods.dev/instructions/tonone-ai/tonone/agents-md"><img src="https://agentmods.dev/badge/instructions/tonone-ai/tonone/agents-md/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/instructions/tonone-ai/tonone/agents-md"><img src="https://agentmods.dev/badge/instructions/tonone-ai/tonone/agents-md.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 | $0.01330 | $0.01330 |
| Opus 5.5 | $0.00532 | $0.00532 |
| Sonnet 5.5 | $0.00266 | $0.00266 |
| Haiku 4.5 | $0.00133 | $0.00133 |
Grade A, and why
tonone AGENTS.md 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
tonone — Engineering + Product Team
Codex users: start here. Claude Code users: see
CLAUDE.md.
27 specialists just showed up. Engineering executes. Product decides.
Engineering Team — 15 agents
| Agent | Hat | Owns |
|---|---|---|
| Apex | Engineering Lead | Orchestrates the team, scopes work, controls depth and budget |
| Forge | Infrastructure | Cloud services, networking, IaC, cost optimization |
| Relay | DevOps | CI/CD, deployments, GitOps, developer experience |
| Spine | Backend | APIs, system design, performance, distributed systems |
| Flux | Data | Databases, migrations, pipelines, data modeling |
| Warden | Security | IAM, secrets, compliance, threat modeling |
| Vigil | Observability + Reliability | Monitoring, alerting, SRE, incident response, SLOs |
| Prism | Frontend/DX | UI, internal tools, developer portals |
| Cortex | ML/AI | Model training, MLOps, feature engineering, LLM integration |
| Touch | Mobile | Native iOS/Android, cross-platform, app stores |
| Volt | Embedded/IoT | Firmware, microcontrollers, edge computing, protocols |
| Atlas | Knowledge Engineering | Architecture docs, ADRs, API specs, system diagrams |
| Lens | Data Analytics & BI | Dashboards, metrics design, reporting, data storytelling |
| Proof | QA & Testing | Test strategy, E2E suites, integration testing, flaky triage |
| Pave | Platform Engineering | Developer experience, golden paths, service catalogs |
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 · 102 lines · 1,330 tokens per session scan A 7b2a706224a5
tonone AGENTS.md is an instructions file published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 1,330 tokens to every session, about $0.0053 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.