Preview an answer from page context
See how a context-only answer could be assembled from the supplied page without treating it as a live search-engine result.
AI Answer Preview
Free, no signup. Ask a question against only your page text. See which passages support the generated answer and where the answer reaches beyond your content.
Runs entirely in your browser — nothing you paste is uploaded or stored. A URL is fetched through the protected text-fetch endpoint only when you do not paste content. The optional AI simulation sends extracted page context to the bounded Workers AI endpoint. If it is unavailable, no generated answer is fabricated. Anonymous run-level outcome counters may be used for aggregate research; URLs, domains, IPs, and identifiers are never included, and no statistic is released below 100 runs.
Sample report
Illustrative unavailable-state example — no model output invented
Answer
AI unavailable — showing relevant passages.
Relevant source passage
“A 301 redirect is appropriate when a URL has moved permanently.”
Question: Which redirect should I use for a permanent move?
This is the real fallback contract: when generation cannot run, the tool retains relevant supplied evidence and makes no claim about what a model would answer.
How to use it
- Write the question the page should answer.
- Paste page text or HTML; use the optional URL only when the paste area is empty.
- Choose Generate preview and distinguish simulation from degraded mode.
- Review each answer sentence against the matching chunk, then edit the source rather than optimizing for the generated wording.
Site passport Local context for this saved site
Local data
Saved targets, named lists, and recent check summaries remain only in this browser.
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What the simulation shows
- Simulation is one context-only Workers AI response.
- Supported means a sentence has a lexical matching passage and shows chunk number and confidence.
- Not supported by a matching passage flags missing lexical grounding; it is not automatically false.
- Degraded means the AI run was unavailable and only source passages are shown.
How it works
The browser extracts readable chunks from supplied HTML or text and sends at most 14,000 context characters with the question to a bounded answer-preview endpoint. Returned sentences are compared locally with source chunks for lexical attribution. When the endpoint is disabled, exhausted, or fails, a deterministic degraded function selects relevant passages instead.
Features
- Paste-first input with optional protected URL fetch.
- Context-only simulation using one declared model route.
- Sentence-level chunk attribution and lexical confidence.
- Honest no-generation fallback.
Limits of the simulation
The tool does not reproduce consumer AI products, web retrieval, citations, model rankings, or search results. Lexical support can miss paraphrases or match text that is factually wrong. URL mode does not render JavaScript, and long context is truncated.
AI answers may continue to reflect cached or previously retrieved material for days to weeks after a fix. Recheck over time before treating an unchanged answer as proof that the fix failed.
Frequently asked questions
Does this preview what ChatGPT or Google AI Overviews will say?
No. It runs one bounded Workers AI context-only simulation. It does not reproduce another product’s model, retrieval index, prompt, ranking, citations, or answer.
What does “supported” mean?
A generated sentence has a sufficiently matching passage in the supplied page chunksGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. under the tool’s lexical attribution method. It is not a factuality guarantee.
What happens when the AI endpoint is unavailable?
The tool switches to degraded mode and shows relevant source passages. It does not fabricate a generated answer or count the unavailable run as a negative result.
Does the optional URL mode render JavaScript?
No. It fetches protected public source text. Paste rendered content when important text is added only after JavaScript runsTurning HTML, CSS, and JavaScript into the final visual page and DOM..
Feature requests for Ai Answer Preview
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Where this tool helps
Common use cases
Find unsupported answer sentences
Identify sentences that do not match a source passage closely enough and need stronger on-page support.
Test an answer-focused rewrite
Compare a revised page draft with the original to see whether its key answer becomes easier to ground.
Prepare editorial QA
Give writers a bounded preview and source-matching checklist before publication or stakeholder review.
Watch the full workflow
AI Answer Preview walkthrough
Read the transcript
AI Answer Preview
A polished answer can still reach beyond the page it was given. I’ll show you when this preview helps, how to run a bounded context-only example, inspect the actual execution surface, read sentence attribution and findings, handle degraded mode, understand limitations, and choose responsible next steps.
Step 1
This tool asks one bounded Workers A-I endpoint to answer using only the page context you supply, then compares each generated sentence with source chunks. It is useful for finding grounding gaps. It does not preview Chat G-P-T, Gemini, A-I Overviews, rankings, retrieval, or citations.
Step 2
Use it when a page should answer one important question, when a summary feels broader than its evidence, or when editors need to trace answer sentences back to source passages. It can also reveal where the page is relevant yet too indirect for a concise response.
Step 3
Enter the question, then paste page text or H-T-M-L. Use the optional U-R-L only when paste is empty; U-R-L mode does not render JavaScript. Select Generate preview. In local or unavailable conditions, the tool honestly switches to relevant supplied passages instead of inventing model output.
Step 4
Start with Actual execution surface. It records whether the bounded model was evaluated, requested and resolved model versions when reported, query time, and supplied-context retrieval. If the run says not evaluated, interpret the output as degraded evidence selection, not a generated answer.
Step 5
The Answer card contains either the context-only simulation or an explicit unavailable-state message with relevant passages. Read the status beside the button as well. A fluent answer is not automatically factual, and a degraded result is not a negative evaluation of the page.
Step 6
Sentence attribution labels lexical support and, when available, shows the matching chunk and confidence. Supported means words sufficiently overlap under this method. It is not a factuality guarantee. Weak or unsupported can reflect paraphrase, missing context, or a real grounding gap that needs human review.
Step 7
When findings appear, inspect the label, rationale, editorial association, movability, and verification step. Treat them as review prompts. If only a captured U-R-L prefix was available, absence-based conclusions are explicitly not evaluated for the complete page.
Step 8
Consumer-product context lists dated priors only. Each profile remains not evaluated because no query reached that product. These notes may explain general product differences, but they are not alternate previews and must never be reported as observed answers or current visibility.
Step 9
Download the attribution C-S-V to review the question, each answer sentence, support label, and evidence. Use it as an editorial handoff: assign verification, record the source passage, decide whether the page or answer overreaches, and preserve the reasoning behind each change.
Step 10
Features include paste-first input, protected public U-R-L fetching, one declared context-only model route, sentence-level chunk attribution, lexical confidence, findings with verification guidance, export, and a deterministic fallback that preserves relevant evidence when generation cannot run.
Step 11
The preview does not reproduce consumer products, live web retrieval, citations, rankings, or search results. Lexical matching can miss valid paraphrases or support factually wrong text. Long context is truncated, JavaScript-rendered U-R-L content can be missed, and cached product behavior can lag changes.
Step 12
Open each flagged sentence beside the best matching source passage. Verify accuracy, scope, and usefulness; add a direct answer or supporting detail only when warranted. Rerun, compare attribution, then test the actual page with readers, analytics, and the real search surfaces relevant to your goal.
Improve the source page—not the simulated wording.
Use unsupported or weakly supported sentences as investigation prompts. Add clear source content only when it is accurate and useful, rerun the preview, then validate the page with human readers and real search evidence. Never present this one simulation as a forecast of a consumer A-I product.
Common issues & how to fix them
- Error Generated sentence lacks matching source support Fix: Add a source passage that directly supports the sentence’s claim, qualify it to match the evidence, or remove it.
- Warning Generated sentence has only weak lexical support Fix: Rewrite the source or answer so the generated sentence clearly matches an explicit supporting passage.
- Information Supplied source passage is not represented in the answer Fix: Revise the answer to use the strongest query-relevant supplied passage.
- Warning Requested question is only partially answered Fix: Add a direct response to the missing parts of the question.