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 agentmods add instructions/taniwhaai/arai/agents-mdgit clone --depth 1 https://github.com/taniwhaai/araiWrote 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/taniwhaai/arai/agents-md)<a href="https://agentmods.dev/instructions/taniwhaai/arai/agents-md"><img src="https://agentmods.dev/badge/instructions/taniwhaai/arai/agents-md.svg" alt="Measured on agentmods" 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 | $0.01340 | $0.01340 |
| Opus 5 | $0.00670 | $0.00670 |
| Sonnet 5 | $0.00268 | $0.00268 |
| Haiku 4.5 | $0.00134 | $0.00134 |
Grade A, and why
arai 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 6d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Arai
This file contains rules that AI coding agents must follow when working in this repository.
These rules exist because mistakes here are expensive (corrupting Taniwha build state, breaking compartmentalization invariants, etc.).
Core Discipline (Non-Negotiable)
- Always enter plan mode for any non-trivial task (3+ steps, architectural decisions, or anything that would benefit from user review before coding). Use the
enter_plan_modetool. - Never edit source files while in plan mode except for the plan file itself.
- Exit plan mode with
exit_plan_modeand present the plan for explicit user approval before making implementation changes. - Respect the current plan file as the single source of truth during any planning or implementation phase. Do not improvise outside it.
Taniwha / Subagent Rules
- When using the Taniwha compartmentalized build system (
.claude/skills/), always follow the documented process:- Use the orchestrator/dispatcher pattern for complex work.
- Dispatch the correct role subagents (design-doc, contract-derivation, leaf-implementation, composition, verifier).
- Never bypass phases (especially verification).
- Never manually mutate files under
.taniwha/kupu/except through the approved mechanisms (Kupu MCP tools when available, or the exact bash fallback scripts in.claude/skills/_shared/scripts/util/). - Always prefer Kupu MCP tools when available. When they are not, use the canonical bash scripts (
new_ulid.sh,now.sh,event_path.sh).
Work Style
- Plan first. Write plans to
tasks/todo.md(or the active session plan file) with checkable items before deep implementation. - Verify before claiming done. Run tests, benchmarks, and manual verification. Do not mark tasks complete until they actually work.
- Minimal impact. Only touch what is necessary. Challenge yourself: "Is there a more elegant way with less surface area?"
- After any correction from the user, update
tasks/lessons.mdwith the pattern and rules to prevent recurrence.
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.
- 6d ago First seen · 72 lines · 1,340 tokens per session scan A 88db971919e8
arai AGENTS.md is an instructions file published in the GitHub repository taniwhaai/arai (7 stars, last pushed 23d ago), licensed Apache-2.0. It adds 1,340 tokens to every session, about $0.0067 per session on Opus 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 2026-08-31.
Other instructions, from other repositories
plan-forge architecture-principles.instructions.md
Core architecture principles — Architecture-First Approach, Separation of Concerns, TDD, Best Practices over Quick Wins. READ BEFORE any code changes.
plan-forge copilot-instructions.md
Copilot instructions for srnichols/plan-forge, covering instructions for copilot, architecture principles, core principles (non-negotiable), cost estimates and talking to forge-master.
plan-forge auth.instructions.md
.NET authentication & authorization — JWT/OIDC, policy-based auth, multi-tenant isolation, API keys, testing.
plan-forge blazor-fluent-ui.instructions.md
Blazor Server + Microsoft Fluent UI patterns — component layering, state, lifecycle, accessibility. Auto-loads when editing .razor / .razor.cs files.
plan-forge aci-design.instructions.md
Agent-Computer Interface (ACI) rules — how every forge MCP tool must shape its inputs and outputs so the calling agent can use it reliably. Auto-loads when editing tool definitions or capabilities.
plan-forge landing-zone.instructions.md
Azure Landing Zone baselines — identity, network, policy, management, security, tagging, subscription organization.