Borrowing it
Nothing to install: this file belongs to hakoniwalab/hakoniwa-business-pack. 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/hakoniwalab/hakoniwa-business-pack/main/AGENTS.mdgit clone --depth 1 https://github.com/hakoniwalab/hakoniwa-business-packWrote 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/hakoniwalab/hakoniwa-business-pack/agents-md)<a href="https://agentmods.dev/instructions/hakoniwalab/hakoniwa-business-pack/agents-md"><img src="https://agentmods.dev/badge/instructions/hakoniwalab/hakoniwa-business-pack/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/hakoniwalab/hakoniwa-business-pack/agents-md"><img src="https://agentmods.dev/badge/instructions/hakoniwalab/hakoniwa-business-pack/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 | $0.01848 | $0.01848 |
| Opus 5 | $0.00924 | $0.00924 |
| Sonnet 5 | $0.00370 | $0.00370 |
| Haiku 4.5 | $0.00185 | $0.00185 |
Grade A, and why
hakoniwa-business-pack 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 10d 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 — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hakoniwa Business Pack Agent Router
This repository is structured system knowledge for translating user requirements into defensible Hakoniwa system compositions and for improving that knowledge from real usage.
Do not treat this repository as a normal source-code project first.
AGENTS.md is the stable entry point for AI agents. It routes the agent to one of two primary roles:
- User / Solution Agent: understand a user goal and produce a defensible Hakoniwa Recipe, with execution or validation only when requested.
- Maintainer / Learning Agent: turn reusable demand signals, implementation discoveries, runtime evidence, and corrections into durable Business Pack knowledge and executable guardrails.
Choose The Active Role
User / Solution Agent
Read AGENTS-USER.md when the task is primarily about using Hakoniwa to satisfy a user need.
Typical triggers:
- "Can Hakoniwa do X?"
- "How should I build X with Hakoniwa?"
- selecting components for a requirement
- designing or updating a Recipe
- evaluating feasibility or validation status
- creating or running a simulation-only Demo
- implementing an already-defined Recipe
The normal flow is:
User Requirement
-> Search / interpret existing Use Cases
-> Required Capabilities
-> Catalog Components
-> Recipe
-> Feasibility / Validation / Agency Boundary
-> Optional Execution
-> Preserve unmet or reusable demand as Use Case knowledge
Before evaluating feasibility from Catalog components alone, search usecases/ for an existing reusable problem or desired outcome that matches the user's intent. Reuse or refine that Use Case when appropriate.
If no matching Use Case exists, derive a provisional Use Case from the user's goal. A request that is currently not_feasible, partially_feasible, or unknown is still valuable demand knowledge: preserve the unmet need as a Use Case Fragment or canonical Use Case candidate instead of discarding it after feasibility analysis.
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.
- 10d ago First seen · 211 lines · 1,848 tokens per session scan A e86b033269ed
hakoniwa-business-pack AGENTS.md is an instructions file published in the GitHub repository hakoniwalab/hakoniwa-business-pack (5 stars, last pushed today), licensed MIT. It adds 1,848 tokens to every session, about $0.0092 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.
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