Best practice: HADS format for system prompts that work across all 300+ models

[catcam]

OpenRouter's core value is model-agnostic access — users switch between GPT-4, Claude, Llama, Mistral without changing their app. But documentation and system prompts often break when switching because smaller models handle verbose docs differently than larger ones.

HADS (Human-AI Document Standard) solves this: https://github.com/catcam/hads

A lightweight Markdown tagging convention that works from GPT-4 down to Llama 3 8B:

## API Authentication

**[SPEC]**
- Method: Bearer token
- Header: `Authorization: Bearer <token>`
- Expiry: 3600s

**[NOTE]**
Switched from cookie auth in v2. Legacy docs mentioning cookies are outdated.

**[BUG] Token silently rejected after password change**
Symptom: 401 identical to expired token
Cause: All tokens invalidated on password change
Fix: Re-authenticate after any account operation

The AI manifest at the top tells any model what to read and skip — explicit instruction beats structural inference, especially for 7B models.

Why relevant to OpenRouter users:

• System prompts written in HADS work consistently across model tiers
• Context docs in HADS format reduce hallucination when switching to smaller/cheaper models
• Zero overhead — pure Markdown, no tooling

Would this be worth a mention in the docs or examples as a best practice for portable system prompts?