Generate Codex launchers for repo sweeps without rebuilding the shell script each time.
Use this when you want a reusable runner for prompts-gpt.com hardening passes. Pick the maintained sweep family, set the default model and iteration count, target one functionality or the whole app, and download a launcher that stays aligned with the repo scripts.
Free Tool
Generate a Codex sweep launcher that matches your run.
Downloads as codex-feature-launcher.sh.
Broadest option. Starts with a whole-codebase review, then implements targeted fixes, features, security, performance, and final validation.
The launcher exports this as the default `CODEX_MODEL`.
Each iteration runs the selected sweep runner once end to end.
Used by the maintained sweep runner when that preset supports parallel passes.
Defaults the launcher to `USE_BACKGROUND_AGENTS=yes|no`.
Review the whole repo across product, prompts, AI visibility, admin, SDK, performance, and SEO.
Only used when the target feature is set to `custom`.
Defaults to `workspace-write`. Override only if your Codex setup needs a different mode.
The launcher auto-detects repo root first. This path is only a fallback when launched elsewhere.
Script preview
codex-feature-launcher.shFeature-target sweep uses .scripts/run-codex-feature-target-sweep.sh.
The downloaded launcher stays thin on purpose, so improvements to the maintained repo runner automatically flow into future runs.
This is built for repeatable repo sweeps, not one-off shell snippets.
The generator keeps the launch script thin and points it at the maintained repo runners. That means model defaults, iterations, targeting, and run mode can be customized without letting the shell template drift away from the real sweep logic.
Configurable runners
Choose from the maintained AI visibility, feature-target, full-product, prompts, or client SDK sweep families.
Downloadable launcher
Export a ready-to-run shell script instead of rebuilding the same environment variables every time.
Feature targeting
Point the broader sweep at one functionality or run across the full product when the pass needs wider coverage.
Open Prompt Studio
Draft reusable prompt workflows after the code sweep surfaces missing UX or prompt quality work.
Run the visibility checker
Test a public domain or prompt path before deciding which sweep target needs the next hardening pass.
Read the docs
Review how projects, monitors, prompts, and reports connect before creating larger automation runs.
When to use feature-target mode
Use the feature-target preset when one functionality needs a broader codebase review, a prioritized to-do list, and staged implementation passes instead of a fixed five-flow sweep.
What gets downloaded
The file is a shell launcher. It discovers the repo root when possible, exports your selected defaults, then hands off to the maintained runner inside `.scripts`.
Show the same product truth to crawlers, AI systems, and evaluators.
Competitive AI visibility products expose public discovery files, evidence-led docs, and a transparent self-check path. prompts-gpt.com should do the same so the market sees the current AI visibility platform, not older prompt-library snapshots or a rerun URL without context.
Use the live checker for diagnostics. Use the published markdown or JSON self-audit exports when you need a stable public proof artifact. The JSON export also includes the Prompts-GPT.com project preset and monitor blueprint used for the ongoing internal follow-up path.
llms.txt
Machine-readable source map for the current product truth.
robots.txt
Crawler access policy for public and private routes.
sitemap.xml
Canonical public URL inventory for discovery and recrawl.
Self-audit export
Stable markdown proof artifact for the prompts-gpt.com self-evaluation.
Self-audit JSON
Machine-readable self-audit payload with credibility notes and project guidance.
Self-audit report
Public methodology, export guidance, and current discovery gaps.
Live checker rerun
Fresh diagnostic surface for answer snapshots, citations, and recommendations.
Make each share surface explicit about stability, format, and audience.
The self-test showed that public discovery surfaces are only credible when buyers can tell which link is stable proof, which one is a live rerun, which files are AI-readable discovery aids, and which path requires sign-in for recurring monitoring.
Self-audit markdown export
markdownStable proofStable public proof artifact for external sharing, procurement review, and citations.
Audience: buyer
Open Self-audit markdown export: /reports/prompts-gpt-com-self-audit.mdSelf-audit JSON export
jsonStable proofMachine-readable self-audit payload with credibility notes, export context, and project guidance.
Audience: ai-system
Open Self-audit JSON export: /reports/prompts-gpt-com-self-audit.jsonSelf-audit article
htmlStable proofMethodology, current limits, and product-claim boundaries for public evaluation.
Audience: buyer
Open Self-audit article: /articles/prompts-gpt-com-ai-visibility-self-auditFree checker rerun URL
htmlLive diagnosticFresh answer snapshot, source list, and recommendations for live inspection.
Audience: operator
Open Free checker rerun URL: /free-tools/ai-brand-visibility-checker?site=prompts-gpt.com&submitted=1Official llms.txt
txtAI-readableCanonical AI-readable source map for the current public product story.
Audience: ai-system
Open Official llms.txt: /llms.txtrobots.txt
txtAI-readableCrawler access policy for public versus private routes.
Audience: crawler
Open robots.txt: /robots.txtsitemap.xml
xmlAI-readableCanonical public URL inventory for discovery and recrawl.
Audience: crawler
Open sitemap.xml: /sitemap.xmlPrompts-GPT.com project preset
htmlProject handoffAuthenticated handoff path from one public self-check into recurring monitoring.
Audience: operator
Open Prompts-GPT.com project preset: /free-tools/ai-brand-visibility-checker?auth=sign-up&next=%2Fdashboard%2Fprojects%2Fnew%3Fbrand%3DPrompts-GPT.com%26site%3Dhttps%253A%252F%252Fprompts-gpt.com%26category%3DAI%2Bsearch%2Bvisibility%2Bplatform%26source%3Dfree-checkerMake the public proof boundary explicit for every credibility check.
The self-audit should not force evaluators to infer which parts are inspectable now, which are only directional, which require a saved monitor, and which require sign-in. The matrix below makes that boundary machine-readable and visible on the page.
Answer snapshots
Inspectable nowA credible AI visibility product should show the actual answer snippet instead of summarizing results as a score only.
Inspect by
Run the checker on prompts-gpt.com, read the answer snippet and full-answer evidence, then preserve that run with the checker markdown or JSON download.
Share policy
Use checker-run markdown or JSON when sharing one diagnostic run. Use the self-audit export and article for durable product-level proof.
Citations and source evidence
Inspectable nowBuyers need to see whether owned pages, third-party reviews, or comparison pages are actually supporting the answer.
Inspect by
Inspect detected source URLs, provider-verified flags, top industry sources, and source labels in the live checker result or the checker-run exports.
Share policy
Treat citation lists from one checker run as directional evidence. Use the self-audit export to explain what the product can prove publicly today.
Recommendations
Inspectable nowDiscovery tooling is only useful when the answer evidence turns into concrete next actions instead of a generic score.
Inspect by
Review the checker recommendations below the answer snapshot and compare them with the documented workflow in the public docs.
Share policy
Recommendations from one run are acceptable to share as tactical diagnostics, but not as recurring trend proof.
Opportunity backlog
Inspectable nowOperators need a clear backlog that connects missing mentions or weak citations to pages, briefs, FAQs, or source fixes.
Inspect by
Inspect the opportunity cards and exported opportunity payload from the live checker run for prompts-gpt.com.
Share policy
Use checker-run exports for run-specific opportunities. Use the self-audit export to explain the proof boundary between one run and recurring monitoring.
Scoring and confidence
Directional onlySingle-run scores are easy to overclaim. Public proof should state that a preview score is directional until repeated prompt tracking exists.
Inspect by
Compare the preview score against the benchmark prompt pack and the scoring limitation notes before treating it as a durable benchmark.
Share policy
Do not use a single rerun score as a long-term performance claim. Use repeated monitoring for trend or share-of-voice claims.
Crawler-to-citation logic
Monitor onlyConnecting crawler events to later citations is valuable, but the free checker should not imply that capability without a saved monitor.
Inspect by
Review the public feature and docs pages for the workflow description, then confirm the actual crawler-to-citation evidence only inside a saved monitor.
Share policy
Keep crawler-to-citation claims at the workflow and methodology level in public materials. Do not present them as checker output.
Project guidance and recurring setup
Requires authA public self-check should hand off cleanly into a real recurring project when the platform's own prompt set is worth monitoring.
Inspect by
Use the built-in Prompts-GPT.com project preset and baseline monitor prompts after sign-in, then rerun the benchmark prompt pack as a saved project.
Share policy
Public proof can link to the authenticated handoff path, but project creation and recurring monitor evidence remain account-bound.
A credible self-test needs more than one branded rerun prompt.
The branded checker prompt is useful for a first-pass diagnostic, but recurring self-evaluation should also test category, competitor, recommendation, local, and buying-intent prompts. Those benchmark prompts are exported with the self-audit so the proof path stays reproducible.
Analyze AI visibility for prompts-gpt.com. Is the brand understood, mentioned, cited, and positioned accurately in AI answers?
diagnosticUseful as a first-pass branded diagnostic, but still biased because the prompt names the brand directly.
best AI search visibility platforms for marketing teams
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
tools for monitoring brand visibility in ChatGPT and Perplexity
categoryExpands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.
prompts-gpt.com alternatives for AI visibility monitoring
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
prompts-gpt.com vs PromptWatch for answer engine optimization
competitorChecks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.
which AI visibility tools should an SEO agency compare
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
recommend software for tracking AI answer citations and brand mentions
recommendationTests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.
AI search visibility tools for teams in the United States
localVerifies whether region-specific discovery claims hold outside the core branded story.
AI visibility software pricing and features for a growing brand
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
which AI brand monitoring platform should I buy
buying_intentChecks whether pricing and feature pages support commercial AI answers with enough proof.
Public AI visibility products are judged on proof, not only feature copy.
Competitor research consistently raises the same bar: exportable evidence, shareable reporting, public methodology, and a clean handoff into recurring monitoring. This kit exists so prompts-gpt.com reads like an AI Search visibility platform rather than a generic dashboard with AI-themed marketing.
Stable public proof export
supported publiclyBuyers need a shareable artifact that does not mutate when answer providers change.
Machine-readable evidence export
supported publiclyAI systems, evaluators, and internal tools need a structured payload instead of screenshot-only proof.
Live diagnostic rerun
supported with limitsOperators need a fresh answer snapshot to inspect citations, entities, and recommendations on demand.
Public methodology and claim boundaries
supported publiclyTrust depends on explaining what scoring, citations, and crawler context can prove versus what requires saved monitoring.
Recurring reporting handoff
monitor onlyA credible platform must convert a public diagnostic into a saved project when visibility work becomes ongoing.
PDF and CSV export with citation detail
supported with limitsStakeholders expect downloadable brand reports and citation spreadsheets with full and summary modes.
Scheduled report delivery
supported with limitsRecurring automated email reports eliminate manual export steps for teams that report AI visibility to leadership.
Shareable online dashboards
monitor onlyAgencies and teams need live dashboard links that stakeholders can access without account setup.
BI connector (Looker Studio)
monitor onlyData teams need live structured feeds into existing dashboards and reporting pipelines.
Content briefs from AI insights
supported with limitsVisibility data should produce concrete content recommendations, not just metrics.
Prompt gap and competitor gap analysis
supported with limitsBuyers need to identify exactly which prompts competitors own and where the brand is absent.
Geo distribution tracking
supported with limitsGlobal brands need to understand which countries and regions provide their highest AI visibility.
Public proof expectations were checked against live category examples.
This self-audit did not invent a reporting standard. The research pass checked how adjacent AI visibility products explain citations, documentation, and exports in public before setting the proof policy for prompts-gpt.com.
Semrush AI Visibility Toolkit
Recurring reporting, prompt research, and shareable AI visibility dashboardsReviewed 2026-05-16Semrush publicly documents prompt research, visibility overview, brand performance reporting, PDF exports, CSV exports, and shareable online dashboards inside the AI Visibility Toolkit.
Why it matters: Buyers now expect AI visibility tools to move from one-off scans into recurring reporting and stakeholder-ready sharing.
Semrush KB - Getting Started with the AI Visibility ToolkitPeec AI
AI search analytics, source influence metrics, and BI-friendly reportingReviewed 2026-05-16Peec documents visibility, position, sentiment, source-used metrics, a documentation llms.txt index, and a Looker Studio connector for reporting.
Why it matters: Clear metric definitions, machine-readable docs, and reporting connectors make public product claims easier to trust.
Peec AI Docs - Welcome and Looker Studio connectorProfound
Answer-engine tracking plus actions and query fanout analysisReviewed 2026-05-16Profound publicly documents visibility tracking across major answer engines, query fanouts, actions, and customer workflows tied to AI search outcomes.
Why it matters: Public product stories in this category increasingly connect measurement to concrete action workflows instead of isolated scoring.
Profound - Introducing Actions and Query FanoutsScrunch
Citation drill-down and source-level influence reviewReviewed 2026-05-16Scrunch publicly documents citation grouping by domain or URL, platform filtering, and citation-level influence analysis in its help center.
Why it matters: Answer evidence without source drill-down is weak; buyers want to inspect which domains influence mentions and citations.
Scrunch Help Center - Understanding the Citations Tab in ScrunchOtterlyAI
Export-oriented reporting and GEO audit artifactsReviewed 2026-05-16Otterly publicly documents CSV exports for prompts and citations, a GEO Audit PDF export, a Looker Studio connector, and explicit boundaries for what is not exportable yet.
Why it matters: Claim boundaries matter in this category; precise public export disclosures are more trustworthy than broad unsupported promises.
Otterly Help - Can I export my data and reports?Ahrefs Brand Radar
Search-backed prompt database with free AI visibility checker and cited domain analysisReviewed 2026-05-16Ahrefs publicly provides a free no-signup AI visibility checker with mentions by platform, top 5 topics, top 5 cited domains, and top 5 cited pages. Brand Radar tracks 400M+ monthly search-backed prompts derived from real search behavior across ChatGPT, Gemini, Perplexity, Copilot, AI Overviews, AI Mode, and Grok.
Why it matters: A free checker with no signup creates a strong top-of-funnel acquisition loop. Search-backed prompts from real user behavior are more trustworthy than synthetic question sets. Cited domain and cited page analysis gives actionable source intelligence.
Ahrefs - Free AI Visibility Checker and Brand RadarPublic proof should include what is still weak.
A credible AI visibility platform should publish risks discovered during self-testing, not only positive feature claims. These risks are mirrored in the self-audit markdown and JSON exports for external review.
Legacy prompt-library snippets still outrank AI visibility positioning for some queries
highEvidence: Public search results still surface the /prompts listing with a legacy 'Best AI Prompts Library' snippet while the homepage describes prompts-gpt.com as an AI visibility platform.
Impact: Evaluators can misclassify prompts-gpt.com as a generic prompt library instead of an AI Search Visibility platform.
Action: Keep /, /features, /pricing, /resources, /docs, /articles, and self-audit exports internally consistent; keep canonical AI visibility positioning in llms.txt and avoid reintroducing prompt-library-first metadata.
Live rerun links are easy to treat as permanent proof
mediumEvidence: The free checker URL is public and shareable, but the output can change as providers, citations, and model behavior shift.
Impact: External stakeholders may treat mutable diagnostics as stable evidence and misread score changes as regressions.
Action: Use markdown/JSON exports and the self-audit article as the default proof artifacts in public sharing and documentation.