Guide Version 1.6.0
Published
Last Modified
Status Stable

This specification is published and recommended for implementation. Backwards-compatible additions may occur in MINOR versions; breaking changes only in MAJOR versions, with deprecation notice. See specification conventions for status definitions.

Interoperability Guide

Conflict resolution and precedence rules for AI Discovery Files

When multiple AI Discovery Files contain conflicting information, this guide defines which file takes precedence. These rules ensure consistent interpretation and help implementers maintain file coherence.

§1 Core Principles

Three principles guide conflict resolution for AI Discovery Files:

  1. Structured data takes precedence over unstructured. JSON files are authoritative over their text equivalents because they can be parsed unambiguously.
  2. Specific files take precedence over general files. A file dedicated to a single purpose (e.g., brand.txt for naming) is authoritative for that purpose.
  3. Access control takes precedence over usage permissions. If a file cannot be accessed, any permissions declared for it are moot.
Design Goal

Conflicts SHOULD be rare. If you find yourself frequently resolving conflicts, your files likely contain redundant or contradictory information that SHOULD be reconciled at the source.

§2 File Hierarchy

The 10 AI Discovery Files are organised into functional tiers. Within each tier, files serve complementary rather than competing purposes.

Tier 1: Access Control

These files control whether AI systems can access content at all.

robots.txt > robots-ai.txt

Tier 2: Structured Identity

These files are authoritative for factual identity data.

identity.json > ai.json

Tier 3: Human-Readable Context

These files provide context in human-readable formats.

llms.txt > ai.txt > llm.txt > llms.html

Tier 4: Supporting Files

These files provide supplementary information.

brand.txt > faq-ai.txt > developer-ai.txt

§3 Precedence Matrix

When information conflicts between files, use this matrix to determine which source is authoritative:

Information Type 1st (Highest) 2nd 3rd External
Business Name identity.json llms.txt brand.txt Schema.org
Alternate Names identity.json brand.txt llms.txt Schema.org
AI Permissions ai.json ai.txt
Crawler Access robots.txt robots-ai.txt
Service Descriptions llms.txt faq-ai.txt identity.json Schema.org
Contact Information identity.json llms.txt ai.json Schema.org
Naming Conventions brand.txt identity.json
Reading This Table

For "Business Name": if identity.json exists, its name property is authoritative. If not, fall back to the H1 heading in llms.txt, then to brand.txt official names.

§4 Common Conflict Scenarios

Scenario 1: Name Mismatch

When

identity.json: "name": "Acme Corporation Ltd"
llms.txt H1: # Acme Corp
brand.txt: official-names: Acme Corporation

Resolution: identity.json name is canonical. Update llms.txt H1 to match, OR add "Acme Corp" to identity.json alternateNames array if it's a valid trading name.

Scenario 2: Permission Conflict

When

ai.txt: May summarise content
ai.json: { "summarisation": "prohibited" }

Resolution: ai.json is authoritative for machine parsing. Update ai.txt to match. Both files SHOULD contain equivalent information.

Scenario 3: Access vs Usage Conflict

When

robots.txt: Disallow: /insights/
ai.txt: May summarise content from /insights/

Resolution: robots.txt controls access. If content is blocked, AI cannot reach it—the ai.txt permission is moot. Either update robots.txt to allow access, or remove the permission from ai.txt.

Scenario 4: llm.txt vs llms.txt

When

/llm.txt exists with different content than /llms.txt

Resolution: llms.txt is canonical. The llm.txt file SHOULD be a 301 redirect to llms.txt, not a separate file with different content.

Scenario 5: FAQ Answer Contradicts Service Description

When

llms.txt: "We provide web development services"
faq-ai.txt: Q: Do you build websites? A: No, we focus on consulting only.

Resolution: llms.txt is authoritative for service scope. Update the FAQ answer to align with the services section, or update llms.txt if the FAQ reflects the actual truth.

§5 External Standards

AI Discovery Files MUST align with external standards already on your website.

robots.txt

robots.txt is an external standard that always takes precedence for access control. AI Discovery Files cannot override it.

Schema.org Structured Data

When your website already has Schema.org Organization markup, it SHOULD align with identity.json:

Recommendation

Generate your Schema.org Organization markup from the same source data as identity.json to ensure consistency.

HTTP Headers

Some sites use HTTP headers (e.g., X-Robots-Tag) for crawler control:

§6 Consistency Checklist

Before publishing AI Discovery Files, verify consistency:

Version History

1.6.0

Phase 6 standardisation release. Added /specifications/roadmap/ (theme-pegged forward plan with Active/Next/Future/On hold status flags), /specifications/extensions/ (rules for experimental x- prefixed files and the promotion path), and /specifications/i18n-a11y/ (multi-language publication, locale-tagged identity fields, RTL handling, accessibility of llms.html). Added the Discovery: directive to the robots-ai.txt specification (publishers MAY advertise AI Discovery Files on the same host). Added a formal media-type stance to the HTTP behaviour page (existing IANA types, no bespoke registrations). Expanded the file integrity and signing section on the security and privacy page with four candidate mechanisms, cross-cutting concerns, and interim publisher / consumer guidance. The Discovery: directive is the only normative addition to publisher behaviour; all other additions are forward-looking documentation.

1.5.0

Phase 5 standardisation release. Added /specifications/related-standards/ (positioning vs llmstxt.org, IETF AI Preferences, robots.txt, Schema.org, BCP 14, JSON Schema 2020-12, SemVer) and /specifications/implementations/ (public record of conformant implementations, IETF-style). Added an explicit llmstxt.org backward-compatibility statement to the llms.txt specification. Added a formal multi-domain and subdomain scoping rule to both the llms.txt and identity.json specifications (host-scoped files, cross-host identity asserted via sameAs). No normative requirements changed for existing publishers; the new scoping rules formalise behaviour the specification already implied.

1.4.0

Phase 4 standardisation release. Added /specifications/processing-model/ (seven-stage algorithm for conformant consumers), /specifications/consumer-guidance/ (what AI systems should do with AI Discovery Files), /specifications/test-vectors/ (canonical test suite framing), and reference-implementation framing on the AI Visibility Checker. No normative requirements changed.

1.3.0

Phase 3 standardisation release. Added /specifications/versioning/ (Semantic Versioning 2.0.0 commitments, deprecation timeline, lifecycle), /specifications/governance/ (proposal lifecycle, editorial process, working principles), /specifications/security-privacy/ (trust model, content-injection patterns, GDPR considerations, integrity primitives roadmap), and /specifications/http-behaviour/ (status codes, redirects, soft-404 detection, caching, rate limits). No normative requirements changed.

1.2.0

Phase 2 standardisation release. Added formal conformance specification (Essential / Recommended / Complete classes). Published machine-readable registry at /specifications/registry.json, spec meta-schema, and validator-output schema. Introduced versioned JSON Schema URLs (/v1/) alongside unversioned 'latest' aliases. Added optional BCP 47 language declaration field across all applicable AI Discovery Files. No normative requirements changed.

1.1.0

Phase 1 standardisation release. Added 'Status of This Document' block (Stable). Normalised normative requirement keywords to uppercase per RFC 2119 and RFC 8174. Added References section linking to /specifications/conventions/ and /licensing/. No normative requirements changed.

1.0.1

Added AI Visibility Directory registration guidance. Minor documentation update.

1.0.0

Initial publication. Establishes precedence hierarchy and conflict resolution rules for all 10 AI Discovery Files.

References

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Register in the AI Visibility Directory

Once your AI Discovery Files are published, register your website in the AI Visibility Directory — the verified registry of websites implementing AI Discovery Files. Registration validates your implementation and lists your site for AI systems and industry peers to discover.

Basic Listing

Card entry in the directory with automated file validation. Open to any site with a valid llms.txt file. No cost.

Full Listing Recommended

Dedicated profile page on the directory with dofollow backlinks to your website — a genuine SEO authority signal from a topically relevant, verified source. Includes an attribution badge and enhanced visibility.