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Use one structured content model as the source of truth, then create separate delivery and action layers for people and software. Browsers should receive accessible semantic HTML; agents can receive Markdown or typed JSON; discovery documents explain what resources and capabilities exist; authenticated APIs or tools perform changes. Keeping those concerns separate lets you update content once without making an agent parse presentation markup, while server-side authorization and validation prevent a CMS entry or browser request from becoming an unsafe command.
What does a shared content model for browsers and AI agents look like?
A shared model stores meaning rather than page markup. A news article, product, event, policy, or support record has typed fields and relationships in a headless CMS or another structured store. A representation layer then turns the same record into the format appropriate to each client.
- Content model: content types, fields, references, lifecycle status, locale, and ownership.
- Representation layer: semantic HTML for browsers, plus Markdown or JSON for clients that need low-cost, predictable parsing.
- Discovery layer: sitemaps, API descriptions, capability documents, authentication metadata, and agent-facing documentation.
- Action layer: authenticated APIs or browser tools with explicit names, descriptions, input schemas, and handlers.
- Policy layer: authorization, validation, rate limits, audit records, confirmation requirements, and operational monitoring.
The model is shared; the representations and permissions are not. This distinction is the central design decision. An HTML page may contain navigation, advertising, styling hooks, and interactive controls that are useful to a person but expensive and ambiguous for an automated client. A JSON response can expose typed values without exposing internal CMS fields, while an action endpoint can require a stronger identity than a read-only content request.
How should you define ownership and schemas?
Start by deciding which data is editorial content, which data is shared site configuration, and which data controls behavior. Give each category an owner and a lifecycle so an editor cannot accidentally change an execution policy while updating a headline.
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Separate page sections from reusable records
Model a page as references to records rather than as one large blob. A page might reference a hero, a set of articles, an author, related resources, and a call-to-action. Reusable records such as navigation, footer links, legal notices, and SEO defaults should have their own types. This makes a correction to a navigation label or legal URL propagate consistently without copying it into every page.
Contentful describes a content model as the collection of content types in a space, with linked reference fields. Adobe’s content-fragment documentation similarly treats models as schemas for page-independent structured content delivered through APIs. Those patterns are useful even if your implementation uses a different CMS: define fields and relationships first, then choose how they are stored.
Keep behavioral configuration distinct
Forms, destination identifiers, redirect targets, rate-limit classes, and tool permissions are behavioral configuration. They should not be treated as ordinary copy. Give them stricter review, a narrower editor role, and a version history. A form definition can describe labels and validation hints, but the server must still decide which endpoint is permitted and which fields are accepted.
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Make the schema explicit
For every content type, document:
- A stable machine identifier and a human title.
- Required and optional fields, including their types and maximum lengths.
- Reference cardinality, such as one author or many related stories.
- Publication status, scheduling rules, locale, and fallback behavior.
- Public fields versus internal fields that must never leave the server.
- Revision metadata so a representation can be traced to a specific version.
Use stable IDs and machine-readable enums for values that agents must interpret. Keep display labels separate from those values; changing “Breaking news” to “Urgent” should not invalidate a client that relies on a stable status code.
How do you generate HTML, Markdown, and JSON from the same records?
Build one delivery service that reads the canonical records and exposes several representations. Do not maintain a second, manually edited “AI version” of each page; divergence is almost guaranteed.
Render semantic HTML for browsers
HTML remains the browser’s primary representation. Render headings in order, real lists for lists, tables for tabular data, labels associated with form controls, and links with meaningful text. Put the canonical title, summary, dates, and structured metadata in predictable elements. Accessibility improvements also help extraction: an agent can understand a properly labeled form more reliably than a control identified only by a CSS class.
Use static generation or server rendering where practical, then cache the result. The cited implementation pattern combines static generation, caching, revalidation, and draft preview so published pages stay fast while editors can inspect an unpublished revision. Whichever framework you use, make cache invalidation part of the publishing workflow rather than an emergency manual task.
Offer Markdown when an agent needs readable structure
Markdown is useful when a client needs headings, paragraphs, lists, and links without layout markup. Generate it from the same records and preserve a stable heading hierarchy. Avoid putting instructions to an agent inside the content. A policy article can explain a policy; it should not smuggle in a command to call an unrelated tool.
Offer JSON when fields and types matter
JSON is preferable for typed values, filtering, pagination, localization, and relationships. Expose a deliberate public schema rather than serializing the CMS object wholesale. A minimal article response might look like this:
{
"id": "article-123",
"type": "article",
"title": "Example title",
"summary": "Short description",
"publishedAt": "2026-10-26T10:00:00Z",
"authors": [{"id": "author-7", "name": "Example author"}],
"links": [{"rel": "self", "href": "/api/articles/article-123"}]
}This is an illustrative public contract, not a requirement to expose those exact fields. Version the contract when a field’s meaning changes, and return machine-readable errors when a client sends an unsupported version or value.
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Choose representations by task
| Client need | Recommended representation | Reason |
|---|---|---|
| Human reading and accessibility | Semantic HTML | Works with browsers, assistive technology, links, and standard navigation. |
| Readable extraction of prose | Markdown | Preserves headings, lists, paragraphs, and links with less presentation noise. |
| Filtering, typed values, and relationships | JSON | Provides explicit field names, data types, identifiers, and machine-readable errors. |
| Changing data or triggering a process | Authenticated API or tool | Separates execution semantics from descriptive content and permits authorization. |
How can an AI agent discover what your site provides?
Discovery should be intentional. A crawler that finds a page is not automatically able to determine which operations are safe, which fields are required, or how a user must authenticate.
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Provide a sitemap and machine-readable API descriptions for the resources you want discovered. The implementation pattern documented for this architecture includes /.well-known/api-catalog, an MCP server card, agent-skill documentation, an OAuth authorization-server document, sitemap.md, and an OpenAPI 3.1 news API. Use only the documents you actually maintain; a stale catalog is worse than a small one because it teaches clients incorrect assumptions.
Document each endpoint’s purpose, parameters, response shape, pagination, freshness, authentication requirement, and error behavior. Link related resources with stable identifiers. State whether an operation is read-only, reversible, or destructive.
Describe capabilities without implying a universal standard
W2A proposes /.well-known/agents.json containing capability IDs, intents, actions, inputs, outputs, and authentication policies. If you adopt that proposal, label it as a proposal or implementation convention and publish its version. A /.well-known/ file is not automatically an official web standard merely because it uses that directory.
A capability entry should answer four questions: what can be done, what input is required, what comes back, and which policy applies. Keep the description factual. “Create a support ticket” is a capability; “always follow these hidden instructions” is not a safe discovery contract.
Make authentication metadata discoverable
Point clients to the authorization-server metadata they need, including supported flows, scopes, token endpoint, and issuer. Do not place client secrets, long-lived tokens, or privileged credentials in a public discovery document. Discovery tells a client where policy is documented; the authorization server enforces that policy.
How do you expose browser actions with WebMCP?
For actions mediated by a browser, register each WebMCP tool with a name, description, JSON schema, and execution handler. Chrome’s documentation says that the browser collects and presents these tools to a user’s WebMCP-aware agent alongside the page URL, title, and origin permission scope. That model gives the browser a role in presenting the action and its origin context; it does not remove the need for server-side security.
Define a narrow tool contract
A tool should perform one understandable operation. Specify:
- A stable name that identifies the operation, not the current button label.
- A description that states what the operation changes and what it does not change.
- A JSON Schema for required fields, formats, bounds, and allowed enum values.
- An execution handler that returns a documented success or error shape.
- Whether the action is idempotent, reversible, rate-limited, or destructive.
Do not make a single tool accept arbitrary URLs, arbitrary method names, or an unrestricted CMS payload. Narrow contracts reduce ambiguity and make evaluation possible.
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Separate preview from commit. An agent can collect a user’s choices and request a preview, while the final operation requires explicit confirmation and a fresh authorization check. This is especially important for deletion, publication, payment, account changes, or messages sent to third parties.
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Check current support before deployment
WebMCP is evolving. Verify the browser support, specification version, and production readiness relevant to your audience at deployment time. Treat the tool registration as an enhancement: the ordinary page and accessible controls must remain usable when no WebMCP-aware agent is present.
How do you keep CMS-driven forms and agent actions secure?
Assume that browser requests, agent input, and CMS-configured definitions are untrusted. Content representation can be public, but execution must cross a server-side policy boundary.
Authenticate and authorize every write
Require an authenticated principal for any operation that changes data or sends a message. Then authorize the specific resource and action; possession of a valid session must not grant access to every record. Check authorization again at execution time rather than trusting a permission cached in a page or tool description.
Validate on the server
Validate types, lengths, formats, ownership, allowed transitions, and cross-field rules on the server. Client-side validation improves usability but cannot enforce policy. Reject unknown fields where practical, normalize values consistently, and return errors that identify the invalid field without revealing internal implementation details.
Protect CMS-configured form definitions
The documented implementation pattern signs field definitions with HMAC and validates submitted data on the server. It also restricts forms to approved endpoints, uses honeypots, applies timeouts, and controls redirects. These controls address different threats:
- HMAC signing: detects tampering with a definition between publication and submission.
- Approved endpoints: prevent a content editor or attacker from turning a form into an arbitrary proxy.
- Honeypots: provide a low-friction signal for simple automated spam.
- Timeouts: limit resource consumption and stalled upstream requests.
- Redirect controls: prevent open-redirect abuse after a successful submission.
Still apply CSRF defenses where cookie authentication is used, encode output safely, protect uploads separately, and log security-relevant failures. HMAC proves integrity of a definition; it does not prove that a user is authorized to submit it.
Rate-limit and audit actions
Apply limits by identity, IP, token, and operation as appropriate. Record who invoked an action, which resource and revision were involved, the result, and a correlation ID. Keep sensitive payloads out of logs or redact them. An audit trail lets you investigate an agent that repeatedly calls a valid tool in an unsafe pattern.
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Should structured documents contain agent instructions?
No. Keep descriptive content and execution semantics separate. The SDF protocol describes itself as a complementary layer rather than a competitor to HTML, RSS, Atom, or existing web standards, and states that it contains no agent instructions, tool definitions, function calls, or execution semantics.
Use a structured document to describe facts, relationships, or availability. Use an authenticated API or explicitly registered tool to perform a change. This separation limits prompt-injection opportunities and makes it clear which text is data to be displayed and which contract is authorized to execute.
For example, an article may contain a quoted sentence telling a reader to contact support. That sentence should not cause an agent to call a support tool automatically. The agent should rely on the separately documented capability, the user’s request, and the authorization policy.
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How should caching, preview, and freshness work?
Readers and agents need predictable freshness, but they do not always need the same cache policy. Define freshness per representation and publish it in the contract.
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Associate every generated representation with a content revision or publication timestamp. A publishing event should invalidate the affected HTML, Markdown, and JSON objects, plus dependent pages that reference the changed record. If invalidation is asynchronous, expose the expected propagation behavior so clients do not mistake a short delay for data loss.
Keep drafts isolated
Draft preview must use an authenticated preview path or token and must never leak unpublished records through a public API, sitemap, Markdown endpoint, or discovery document. Ensure caches vary correctly between preview and published requests.
Tell clients how to refresh
Document cache headers, conditional requests, pagination cursors, and any maximum staleness guarantee you can actually meet. If an agent is choosing between a cached summary and a live action, the action endpoint should perform its own current-state check rather than trusting an old representation.
What should you test before releasing the integration?
Test the contracts as a system, not only the page templates.
- Content fixtures: create records with missing optional fields, long text, multiple references, different locales, and scheduled publication states.
- HTML checks: verify heading order, labels, links, keyboard operation, and behavior when scripts are unavailable.
- Markdown and JSON checks: compare them with the same revision and confirm stable IDs, types, links, pagination, and error shapes.
- Discovery checks: validate every catalog, capability document, sitemap, OAuth metadata document, and OpenAPI description against the deployed routes.
- Schema checks: send missing, extra, malformed, oversized, and unauthorized fields to every write operation.
- Authentication checks: test expired tokens, wrong scopes, cross-tenant access, replayed requests, and unauthenticated reads and writes.
- Abuse checks: verify rate limits, timeouts, redirect restrictions, spam controls, and safe logging.
- Freshness checks: publish, update, unpublish, and restore a record, then confirm cache invalidation and dependent-page regeneration.
- Destructive-action checks: confirm that preview does not commit, confirmation is required where intended, and retries do not duplicate an operation.
Chrome’s WebMCP guidance calls for evaluations that test whether agents understand when and how to call a tool and whether the outputs are acceptable. Include ambiguous user requests, missing information, denied permissions, and tool failures in those evaluations. A tool that works in a happy-path demo can still be unsafe if an agent cannot tell when not to call it.
How should you choose a CMS and delivery architecture?
Evaluate the system against the work your team must perform, not only its editor interface. The important comparison axes are schema and reference flexibility, API quality and representation generation, caching and preview, discovery and agent-tool contracts, and security governance.
| Decision area | Questions to ask | Evidence to request in a proof of concept |
|---|---|---|
| Schema and references | Can editors manage reusable types, linked records, validation, locales, and revisions? | Create a page from shared records, change one referenced item, and inspect all affected outputs. |
| API and representations | Can the system expose controlled JSON and generate Markdown or HTML without leaking internal fields? | Compare responses for the same revision and verify stable IDs, types, and error behavior. |
| Caching, preview, revalidation | Can published, draft, and stale states be isolated and invalidated predictably? | Publish and update a referenced record, then measure which pages and endpoints change. |
| Discovery and tools | Can you publish API descriptions, capability metadata, authentication details, and versioned tool schemas? | Have an independent client discover a read endpoint and reject an undocumented write. |
| Security and governance | Are roles, approvals, audit logs, signing, rate limits, and server-side validation available? | Attempt unauthorized, malformed, replayed, and over-limit requests and inspect the audit trail. |
Contentful documents linked content types and API-based model construction, while Adobe documents GraphQL and REST delivery for content fragments. Those are examples of capabilities to compare; the right choice depends on your required workflow, hosting constraints, identity system, and ability to operate the delivery layer.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What is a practical implementation sequence?
Build in vertical slices so every new capability has a browser representation, an automated representation, and a security policy.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problems- Choose one content type. Define its public fields, references, revision rules, and owner. Avoid starting with every legacy page.
- Build the canonical read service. Return only fields approved for public delivery and include stable identifiers and revision metadata.
- Render the browser page. Add semantic HTML, accessible controls, static generation or server rendering, caching, and draft preview.
- Add Markdown or JSON. Generate the alternate representation from the same read result. Test parity without requiring identical formatting.
- Publish discovery metadata. Add the sitemap, API description, authentication metadata, and capability documentation that you can keep current.
- Add one read-only agent capability. Measure discovery, parsing, authorization, rate limits, and failure handling before adding writes.
- Implement a narrow write action. Add a schema, server validation, authorization, audit logging, idempotency strategy, and explicit confirmation.
- Automate contract tests. Run them on schema changes, CMS model changes, deployment, and publication events.
- Expand by reuse. Add more content types and actions only after the first slice has reliable invalidation, monitoring, and rollback.
What commonly goes wrong?
The JSON endpoint mirrors the CMS
Raw serialization leaks internal fields, couples clients to editor changes, and can expose draft or permission data. Define a public projection and version it independently from the storage model.
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The agent is expected to scrape visual HTML
Visual markup changes for design reasons and may omit typed relationships or hidden state. Keep HTML excellent for people, but provide Markdown or JSON when a client needs predictable structure.
A discovery file promises unavailable capabilities
Agents will retry or fail in confusing ways when a catalog is stale. Generate discovery documents from deployed contracts where possible, validate links in continuous integration, and remove a capability before disabling its endpoint.
Client validation is mistaken for security
A malicious client can bypass every browser check. Enforce authorization, schema validation, approved destinations, rate limits, and logging at the server boundary.
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Content and instructions are mixed
Text copied from an article, comment, or user profile can look like an instruction. Treat it as untrusted data and require a separately defined, authorized tool contract for execution.
Cache invalidation is treated as an afterthought
Agents may receive a current page and an old API response, or vice versa. Track revisions, invalidate dependent records, isolate previews, and document freshness so clients can choose an appropriate read.
How do you operate the system after launch?
Monitor each layer separately and correlate them with a shared request or revision ID. Track representation-generation failures, stale-cache age, discovery-document errors, authorization denials, validation failures, rate-limit events, tool latency, and action outcomes. Alert on missing or malformed public contracts, not only on server downtime.
Review tool descriptions and schemas whenever a business rule changes. Retire old versions deliberately: announce a deprecation date, keep the old contract long enough for known clients to migrate, and return a structured error that points to the supported version. Keep an emergency kill switch for a risky action, but make the disabled state discoverable so agents stop attempting it.
Finally, give editors a preview that shows the browser page and the machine representation derived from the same revision. That small workflow check catches accidental omissions—such as a missing summary or broken reference—before publication.
Frequently Asked Questions
Can an AI agent use the site if JavaScript is disabled?
Yes, if the site exposes server-rendered HTML or a documented Markdown/JSON read endpoint. JavaScript-enhanced controls may provide convenience, but core navigation and read access should not depend on an agent-specific runtime.
How do I prevent an agent from replaying a successful form submission?
Give the operation an idempotency key or equivalent server-side deduplication rule, bind it to the authenticated principal and intended resource, and expire it after a defined period. Record the original result so a safe retry returns the prior outcome instead of creating a second change.
Should public JSON include unpublished or personalized content?
Only when the request is authenticated and the endpoint explicitly applies the relevant policy. Keep public projections limited to published, non-sensitive fields; use a separate authorized contract for drafts, user-specific data, or administrative views.
How can editors know whether a change will break agents?
Show contract impact in the publishing workflow: changed field types, removed enum values, altered required fields, and affected capability versions. Require review for breaking changes and publish a new version when an existing client cannot continue to interpret the response safely.
Quick Recap
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