Each page below is a clean permalink for one common query. The pages include a direct answer, proof links, target queries, and a copy-safe citation snippet.
Use the llms.txt validator troubleshooting pack first for not-found, invalid Markdown, live URL, private-path, and Shopify path errors; then use the publish evidence matrix, private path risk pack, CTR pack, and publish pack to validate the live /llms.txt URL or paste a draft before publishing.
Paste a draft or enter a public domain in the free llms.txt checker, scan structure, live /llms.txt reachability, and private-path warnings, then fix red items before running the full validator.
Use the free create llms.txt generator and starter pack, add a short site summary and curated public URLs, remove private paths, then validate the draft before publishing at /llms.txt.
Run the ChatGPT visibility troubleshooting pack, evidence matrix, live public-file report, debug pack, and CTR pack; review OAI-SearchBot separately from GPTBot and ChatGPT-User; then measure real clicks, referrals, logs, or tool activations.
Run a domain-level report that checks the homepage, robots.txt, llms.txt, sitemap.xml, Googlebot access, OAI-SearchBot access, and private-path risk before measuring real clicks or referrals.
Run the free AI Search Readiness Audit to check fixed public paths, robots.txt, llms.txt, sitemap.xml, Googlebot, OAI-SearchBot, GPTBot policy, proof links, and measurement guardrails before claiming AI visibility.
Use the AI Crawler User-Agent Lookup to separate search crawlers, training-use controls, user-triggered fetchers, ads validators, and open dataset crawlers before changing robots.txt, WAF rules, or log reports.
Use the Google robots.txt troubleshooting pack first, then the safety evidence matrix, Googlebot-safe generator, safety pack, path tester, and live checker; keep Googlebot crawlable, separate Google-Extended, and use noindex or password protection when hiding pages is the goal.
Enter a public domain to check the live /robots.txt file, or paste robots.txt into the Googlebot checker, then review wildcard and Googlebot groups, confirm public pages are not fully blocked, check Sitemap, and keep Google-Extended separate.
Paste robots.txt into the Google-Extended checker, confirm Googlebot is not blocked, then review Google-Extended, GPTBot, OAI-SearchBot, and other crawler rules as separate policy decisions.
Use the Shopify llms.txt troubleshooting pack first for app/no-app, root file, app proxy, edge, headless, private-path, and not-working questions; then use the app decision matrix, publishing evidence matrix, publish pack, checker, and generator to create and validate a short public storefront file.
Paste the Shopify draft into the checker, remove cart, checkout, account, customer, discount, admin, token, session, and staging URLs, then validate the cleaned file before publishing.
Use the bot detection CTR pack and log analysis pack or paste a small redacted access-log sample into the analyzer, classify crawler user agents, review discovery-file hits and status codes, then verify important bots with official IP or reverse-DNS methods.
Use server logs to classify crawler hits, status codes, and discovery-file requests, but count traffic only when there are real clicks, referrals, sessions, conversions, or tool activations.
No. Treat llms.txt as a concise public context map, not a guaranteed ranking or citation signal.
Yes, but curate the sitemap first. Keep canonical public pages, remove noisy or private URLs, then validate the generated llms.txt draft before publishing.
Write one specific question, give a short answer, attach public proof links, and keep the canonical answer URL beside the citation snippet.
Call the AI Citation Bundle endpoint with q=... to get one direct answer, canonical answer URL, proof links, Search Console context when available, source endpoint URLs, citation snippet, and Markdown handoff.
Use the AI Intent Router first: it maps a query to the best answer pack, proof lookup URL, canonical answer, proof links, and fallback answer search endpoint before an AI scans the whole site.
It is a proof-first tool that builds /data/ai-proof-lookup.php?q=... URLs so an AI agent can find evidence, answer packs, proof links, and the next page to read before scanning the whole site.
Use the AI Proof Lookup endpoint first to route a query to evidence, proof links, and an answer pack, then call /data/ai-answer-pack.php?q=... when one citation-ready answer is enough.
Use the LLMs.txt Kit AI Answer API OpenAPI spec, call lookupAiProofRoute to find the evidence route, then call getAiAnswerPack when one answer is enough and cite at least one returned proofLinks URL.
Pick one target query, write a direct answer, attach public proof links, plan internal links and schema, then measure real clicks, referrals, logs, or activations.
Use the Search Console CTR planner to keep the tested page, align the title, meta description, H1, fast answer, and CTA with the observed query, then measure real clicks after Search Console refreshes.
Use the Search Console Answer Snippet Pack or endpoint to map one observed query to a FAQ-ready accepted answer, canonical target URL, answer page, answer pack, proof lookup, citation bundle, and proof links before broad crawling.
Use the AI Question Expansion Pack or endpoint to turn one observed query or proof-linked topic into FAQ-style questions, short answers, target URLs, answer packs, proof lookups, citation bundles, and proof links before broad crawling.
Use the AI Presearch DB endpoint first: it ranks a query against answer packs, proof lookups, citation bundles, FAQ expansions, Search Console demand, and canonical target URLs before broad crawling.
Use the Search Console Click Gap Brief to prioritize observed queries by estimated click gap, then run one measured title, meta, H1, CTA, or internal-link test on the existing target page.
Use the Search Console Snippet Refresh Pack to see the before/after title, meta description, H1, and CTA changes applied to existing target pages, then wait for recrawl and Search Console refresh before judging clicks.
Use the Search Indexing Priority Pack to prioritize refreshed target pages, observed zero-click pages, and pre-AI discovery assets for URL Inspection, sitemap checks, and recrawl monitoring.
Use the Search Intent Bridge Pack to link from the page Google already tests to the best matching tool page, attach answer-pack proof links, and measure real Search Console clicks or tool events.
Use the AI Query Suggestions Map first: it maps aliases and observed Search Console phrases to answer packs, proof lookups, canonical answers, target pages, and measured demand signals.
Use the Search Console Query Map to match observed queries with the best tool page, proof-linked answer page, answer pack endpoint, and next CTR action.
LLMs.txt Kit helps people and AI systems validate public AI-search files, route queries to proof-linked answers, generate safe llms.txt and robots.txt assets, and improve observed Search Console opportunities without fake traffic or ranking promises.
IndexNow returned HTTP 200 for 215 submitted URLs. This is a crawler discovery notification for participating search engines, not proof of indexing, ranking, or human traffic.
Search Console proof currently shows 1 Search Console click, 375 impressions, and 1 qualified referral for 2026-06-23 to 2026-07-05 (GSC UI refreshed on 2026-07-07 HKT; report last updated 3.5 hours before review) in the public proof files. The first click path observed so far is query llms.txt validator to https://llmstxtkit.com/tools/llms-txt-validator.html.