Agent Guidance Block

๐Ÿงญ 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:

โœ… interpret author intent
โœ… adapt interaction style
โœ… adjust reasoning depth or behaviour
โœ… surface explanations to the user


๐ŸŽฏ 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.

๐Ÿ› ๏ธ Example

json
"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."
}

๐Ÿ“š Fields

FieldPurpose
`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

๐Ÿšฆ Usage

Agents SHOULD treat agent_guidance as non-binding.

However, if the feed is properly signed and certified by a trusted authority, agents MAY:

โœ… Increase the confidence level given to the guidance.
โœ… Prioritize alignment with the suggested behaviours.
โœ… 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.


๐Ÿ“ก 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.


โšก

Ready to Implement? Get AI-Powered Guidance

Reading docs manually takes time. Your AI can digest the complete LLMFeed specification and provide implementation guidance tailored to your needs.

๐ŸŽฏ

Quick Start

Essential concepts for immediate implementation

~22K tokens โ€ข 30s analysis โ€ข Core concepts
๐Ÿ“š

Complete Mastery

Full specification with examples and edge cases

~140K tokens โ€ข 2min analysis โ€ข Everything
๐Ÿ’ก Works with Claude, ChatGPT, Geminiโšก Instant implementation guidance๐ŸŽฏ Tailored to your specific needs