🧭 Agent Guidance Block
The agent_guidance block provides optional, non-enforceable hints to agents consuming a .llmfeed.json feed.
Unlike agent-behavior specifications (which may define normative requirements), this block is intended to help agents:
✅ interpret author intent
✅ adapt interaction style
✅ adjust reasoning depth or behaviour
✅ surface explanations to the user
🎯 Purpose
Feeds may include agent guidance to:
- Suggest interaction constraints.
- Provide ethically or contextually important signals.
- Offer hints for UX / presentation.
- Recommend caution in handling sensitive content.
🛠️ Example
"agent_guidance": {
"max_inference_depth": 3,
"interaction_tone": "formal",
"consent_hint": "Ask the user before accessing sensitive information",
"risk_tolerance": "low",
"preferred_explanation_style": "bullet-points",
"custom_notes": "This feed relates to user financial data. Be cautious and transparent."
}
📚 Fields
| Field | Purpose |
|---|---|
max_inference_depth | Suggests limiting depth of reasoning/inference |
interaction_tone | Preferred tone (e.g. formal, friendly) |
consent_hint | Suggests when to seek human consent |
risk_tolerance | Recommended risk posture (low, medium, high) |
preferred_explanation_style | UX hint (e.g. bullet-points, summary, narrative) |
custom_notes | Free-text notes for agent developers |
🚦 Usage
Agents SHOULD treat agent_guidance as non-binding.
However, if the feed is properly signed and certified by a trusted authority, agents MAY:
✅ Increase the confidence level given to the guidance.
✅ Prioritize alignment with the suggested behaviours.
✅ Surface to the user that these are trusted recommendations.
If present, agent_guidance MAY influence:
- Prompt framing
- UX presentation
- Decision thresholds
- Interaction flow
It SHOULD be surfaced (if applicable) to the user or agent operator.
📡 Summary
The agent_guidance block complements more enforceable blocks (trust, agent-behavior) by offering soft, contextual hints.
When the feed is signed and certified, these hints gain additional trust weight and can help shape more intent-aligned agent behaviour.
Its adoption helps create a more intent-aware, human-aligned Agentic Web.