WebAI/Reference library
WEBAI KNOWLEDGE ATLAS · EDITORIAL PREVIEW

Reference library▤

Official texts, standards, research papers and first-party documentation.

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A library of original references. Each card describes a particular document, while shared evaluation advice lives in one methodology guide organized by source family. Inclusion does not mean WebAI endorses every conclusion.

Source reading and verification guideOne shared method, adapted to each document type View methods

Choose the family matching the document you want to examine. These rules are not repeated on individual cards: they apply to all references of the same type.

Standards

A specification defines terms, conformance and sometimes reference tests. It helps distinguish proposals, drafts and adopted standards.

  1. Identify the publishing body and exact status.
  2. Read normative sections and document date.
  3. Compare features against actual implementation support.
  4. Record incompatibilities and deployment limitations.

Caution : A W3C project title does not automatically make a document a W3C Recommendation.

Agents

Agent protocols and projects define discovery, messaging, tools and tasks but do not automatically grant action permissions.

  1. Locate a dated version and required fields.
  2. Separate capability descriptions from permissions.
  3. Test exchanges on fictional data.
  4. Review errors and final outcomes.

Caution : Publishing a schema does not prove every library implements it.

Trust

Trust methods document signatures, policies, risks or verification workflows. Interpret results within their stated scope.

  1. Identify the exact claim being checked.
  2. Verify source and technical scope.
  3. Cross-check assertions against independent evidence.
  4. Record unknowns and contradictions.

Caution : A signature or score does not automatically establish factual truth.

Regulation

Regulatory texts establish duties within a defined scope. Exceptions, dates and versions shape their interpretation.

  1. Read original definitions and articles.
  2. Identify jurisdiction, actor and use case.
  3. Check application dates and exceptions.
  4. Seek legal review for real decisions.

Caution : Educational summaries are not personalized legal advice.

Discovery

These sources describe search, crawling and publisher interactions with search products. Rules vary by service.

  1. Distinguish search, ranking, crawling and training.
  2. Check official guidance for each crawler.
  3. Observe actual indexing and cited links.
  4. Do not generalize vendor marketing claims.

Caution : No single optimization guarantees a model citation.

Web creation

Web development documents help design structured, accessible pages usable beyond AI interfaces.

  1. Identify the feature’s user purpose.
  2. Read APIs, examples and browser constraints.
  3. Test a fallback without a model or external service.
  4. Measure accessibility and performance.

Caution : Documentation examples are not a replacement for device testing.

Models

Model sources describe architectures, datasets and evaluations. Editorial status and licensing require independent review.

  1. Identify authors, revisions and intended tasks.
  2. Read model cards and license terms.
  3. Compare evaluations and declared limitations.
  4. Test representative domain examples.

Caution : An author-written model card is not independent certification.

Search & RAG

Research publications propose concepts, results and methods. To understand their scope, inspect methods, datasets and reproducibility.

  1. Identify manuscript or reviewed publication.
  2. Read question, method and sample.
  3. Inspect metrics, failures and limitations.
  4. Look for replications, revisions and critiques.

Caution : A submitted preprint has not necessarily undergone peer review.

On-device AI

These documents concern models running in the browser or on-device. They explain availability, memory needs, acceleration and privacy.

  1. Check browser version and hardware.
  2. Inspect model size and licensing.
  3. Measure latency, memory and failures.
  4. Provide an accessible fallback.

Caution : The term local guarantees neither sufficient performance nor complete privacy.

Immersive

Immersive standards cover spatial representation, hardware, interaction and sensor permissions. Read them together with Web accessibility guidance.

  1. Identify supported devices and browsers.
  2. Distinguish 3D, VR and AR.
  3. Test comfort, performance and navigation.
  4. Provide an accessible 2D mode.

Caution : A 3D scene is not automatically VR and does not guarantee historical fidelity.

01Standards

W3C Web & AI Interest Group

Forum on the intersection of Web standards and AI.

Source websitewww.w3.org
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07Agents

Model Context Protocol

Specification and documentation for MCP.

Source websitemodelcontextprotocol.io
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08Agents

Agent2Agent Protocol

Specification for agent-to-agent messages and tasks.

Source websitea2a-protocol.org
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09Agents

W3C WebMCP

Community proposal for exposing tools to Web agents.

Source websitewebmachinelearning.github.io
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10Trust

C2PA Specifications

Technical specifications for media provenance.

Source websitespec.c2pa.org
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12Regulation

European AI Act

Official portal for the EU AI Act.

Source websitedigital-strategy.ec.europa.eu
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14Discovery

Google Search Central

Official Google indexing and search documentation.

Source websitedevelopers.google.com
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15Discovery

Bing Webmaster Guidelines

Microsoft documentation for site discoverability.

Source websitewww.bing.com
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16Discovery

Pagefind Multilingual

Multilingual static search documentation.

Source websitepagefind.app
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17Web creation

Astro Content Collections

Structured content collections in Astro.

Source websitedocs.astro.build
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18Web creation

MDN Web Docs

Reference documentation for core Web technologies.

Source websitedeveloper.mozilla.org
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21Search & RAG

Transformers paper

Foundational paper on Transformer architecture.

Source websitearxiv.org
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24Search & RAG

VisualWebArena paper

Evaluation of agents using visually grounded interfaces.

Source websitearxiv.org
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25Search & RAG

OSWorld paper

Evaluation environment for computer-using agents.

Source websitearxiv.org
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26Search & RAG

GEO paper

Paper on optimization for generative search engines.

Source websitearxiv.org
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28Immersive

WebXR Device API

Specification for immersive experiences on the Web.

Source websitewww.w3.org
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29Standards

IETF Datatracker

IETF working group documents and internet drafts.

Source websitedatatracker.ietf.org
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31Search & RAG

Crossref REST API

Research metadata and identifier API.

Source websiteapi.crossref.org
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32Web creation

GitHub Docs

Version control, security and automation documentation.

Source websitedocs.github.com
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33Agents

MCP 2026 specification

July 2026 specification: capabilities and security.

Source websitegithub.com
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34Agents

A2A Agent Card specification

Agent discovery and capability descriptions.

Source websitea2a-protocol.org
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35Standards

WebMCP Community Draft

Community draft, not a W3C Recommendation.

Source websitewebmachinelearning.github.io
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36Discovery

Google AI Search guidance

Official guidance for generative search results.

Source websitedevelopers.google.com
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37Discovery

Google AI optimization guide

Clarification on llms.txt and special AI markup.

Source websitedevelopers.google.com
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38Discovery

Google crawlers and Extended

Crawler controls and tokens with distinct purposes.

Source websitedevelopers.google.com
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39Discovery

OpenAI crawler docs

OAI-SearchBot, GPTBot and crawl preferences.

Source websitedevelopers.openai.com
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40Standards

Chrome built-in AI APIs

Built-in browser AI APIs and availability limits.

Source websitedeveloper.chrome.com
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41Standards

WebNN introduction

Accelerated neural computation in browsers.

Source websitewebmachinelearning.github.io
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43Trust

OWASP prompt injection

Instruction injection from untrusted content.

Source websitegenai.owasp.org
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44Trust

NIST Generative AI RMF

Voluntary generative AI risk management framework.

Source websitewww.nist.gov
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45Regulation

EU AI Act consolidated

Consolidated legal text and Article 50.

Source websiteeur-lex.europa.eu
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47Search & RAG

RAG foundation paper

Foundational paper by Lewis et al. (2020).

Source websitearxiv.org
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50Search & RAG

ReAct — Reasoning and Acting (2022)

Study of combining reasoning traces and actions involving sources or environments. Useful for explaining tool-using agents without establishing general robustness.

Source websitearxiv.org
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51Search & RAG

Toolformer — Language Models Using Tools (2023)

NeurIPS work on learning to call external tools from language models. Experiments focus on selected APIs and tasks.

Source websitepapers.neurips.cc
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52Search & RAG

Lost in the Middle — Long Context (2024)

Published TACL study showing that position of relevant information in long contexts can affect model use. Important for RAG design and testing retrieved passages.

Source websiteaclanthology.org
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53Search & RAG

WebArena — Realistic Web Agents (2023)

Self-hostable research environment with realistic Web tasks for evaluating agents’ ability to complete actions. Findings depend on benchmark sites and scenarios.

Source websitewebarena.dev
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54Search & RAG

VisualWebArena — Visual Web Tasks (2024)

Web benchmark where visual perception complements text interpretation, supporting evaluation of agents navigating human-facing interfaces.

Source websitearxiv.org
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55Search & RAG

OSWorld — Computer Use Benchmark (2024)

Benchmark of computer tasks spanning applications and system states, illustrating the difficulty of reliably completing real operations.

Source websitearxiv.org
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56Search & RAG

RAGAS — RAG Evaluation (2023)

Research on evaluating RAG systems along dimensions including passage retrieval and generated-answer faithfulness. Automated metrics require validation.

Source websitearxiv.org
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57Search & RAG

GEO — Generative Engine Optimization (2023)

Study of strategies and visibility metrics in generative search engines. Results apply to experimental settings, not guaranteed universal rankings.

Source websitearxiv.org
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58Search & RAG

SWE-bench — Software Agents (2024)

ICLR benchmark of code repair tasks derived from real repository issues, using executable checks rather than prose evaluation alone.

Source websiteproceedings.iclr.cc
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59Search & RAG

AgentDojo — Prompt Injection Evaluation

Research environment for assessing prompt injections and defenses in tool-using agents. It separates simulated attacks from observed incidents.

Source websiteagentdojo.spylab.ai
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