Badger
Static outputs Manifest JSON llms.txt
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Infrastructure for the agent-driven web

Make your site work natively for humans and agents.

Badger helps websites be understood, trusted, and acted on in agent-mediated journeys, from research and comparison to transaction.

Better legibility for research agents. Better structure for shopping results. Better paths to action for agent-mediated commerce.

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Interactive explainer

See the same surface through three readers.

Human visitors read the story. Agents read the structure. Commerce systems read the path to action. The switch below makes that difference explicit without changing the underlying page.

Choose a browsing mode

Traditional flow

People browse with visual context.

The visitor scans layout, copy, and brand cues to decide whether to keep reading, compare, or leave.

Human experience

A person lands on the page, reads the story, and decides what the site is trying to sell.

Agent interpretation

An external system may only see loose text unless the site also exposes structure, sources, and machine-readable meaning.

Site requirement

Use editorial layout, but do not rely on layout alone to convey critical facts.

Visual hierarchy carries meaningCopy can stay ambiguous for longerThe next action is often implied by design

Delegated discovery

Agents reduce ambiguity before a human ever visits.

The system compares offers, policy, and relevance across sites before the customer sees a shortlist.

Human experience

The customer still owns the decision, but now the first filter is an assistant that has to understand the site accurately.

Agent interpretation

The agent needs canonical facts, explicit policy, and a stable path to explain why the site is relevant.

Site requirement

Publish the facts the agent needs: identity, policy, freshness, and a clear source of truth.

Structured facts outrank styleFreshness and provenance matterComparison-ready attributes determine visibility

Commercial handoff

The next valid action should be explicit.

When the agent is ready, the site should expose a bounded route for quote, contact, reserve, or buy.

Human experience

The person still needs a trustworthy summary, but the path to act can be shorter and more structured.

Agent interpretation

The system should know which action is valid, what it can submit, and what returns or confirmations to expect.

Site requirement

Expose explicit actions instead of forcing the agent to infer intent from a visual interface.

Action contracts are boundedCommercial intent should be declaredThe handoff must remain safe and predictable

Static outputs

Machine-readable entry points published alongside the human narrative.

Manifest JSONPricing JSONActions JSON LLM Overview

Outcome model

One platform, four practical outcomes.

Outcome

Be understood

Expose canonical facts, explicit identifiers, and source hierarchy so agents can represent the business accurately.

Outcome

Be surfaced

Improve how your offers appear in research flows, shopping results, and agent-generated recommendations.

Outcome

Be trusted

Make freshness, provenance, and policy boundaries obvious so systems know what is authoritative.

Outcome

Be acted on

Support clean transitions from comparison to quote, reserve, subscribe, or buy.

The shift

The web is becoming agent-mediated.

The shift

Customers increasingly arrive through agents, not just browsers.

Search is changing. Shopping is changing. Discovery is changing. A growing share of customer journeys now begins with an agent that researches options, compares products, summarizes tradeoffs, and may eventually complete a transaction.

The risk

If agents cannot understand you, customers may never see you.

In agent-led discovery, invisibility looks like silent exclusion. When product constraints, shipping logic, returns terms, or merchant trust signals are unclear, the agent skips the offer and the customer never knows it existed.

The change

From marketing paper to durable business meaning.

Badger turns scattered product knowledge, inconsistent fields, and hard-to-parse policies into a machine-native interface. That makes your business easier to understand, easier to compare, and easier to transact with.

Static-first outputs

One registry, many static surfaces.

Static pages, machine contracts, and generated surfaces can all be built from one canonical registry, so the public site stays coherent as it grows.

Agent Readiness

Benchmarked for delegated interaction.

Score the surface by whether an external system can retrieve facts, interpret policy, and move toward a valid next action without relying on visual guesswork.

88

Navigation

Ability for agents to traverse the site hierarchy without visual cues.

42

Action

Availability of standardized calls-to-action for autonomous execution.

12

Transaction

Machine-to-machine transaction readiness remains the most brittle layer.

Capability registry

Generated category surfaces.

These are the reusable public surfaces that keep the story specific: capability pages, adapter pages, and use cases all derive from the same source of truth.

Capability

Agent Interface

A structured interface layer that helps agents retrieve canonical facts, understand policy, and take valid next actions.

/capabilities/agent-interface

Capability

Commerce Readiness

Bridge agent-led research to structured commercial action, from merchant identity and policy clarity to transaction readiness.

/capabilities/commerce-readiness