Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
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Check whether a website's robots.txt allows the AI crawlers that decide visibility in ChatGPT Search, Perplexity, Claude, Gemini, and Microsoft Copilot. Use when someone asks whether AI bots are blocked, whether to allow or block GPTBot, why a site never appears in AI answers, or wants a robots.txt review for AI crawlers. Reads only robots.txt, then returns a per-agent allow/block table, the exact rule responsible for each verdict, and the precise lines to change. Distinguishes training crawlers from the search crawlers that actually control citations.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
One wrong line in robots.txt removes a site from AI answers completely, and no
amount of content work can compensate. This check takes under a minute and
should run before any other AI-visibility work.
Read https://<domain>/robots.txt and nothing else. Do not crawl the site, do
not attempt to access disallowed paths, and do not bypass any access control.
This is a read of one public file.
Fetch https://<domain>/robots.txt.
For each agent below, apply standard robots.txt matching: the most specific
User-agent group that names the agent wins, and * applies only when no group
names it. Within the winning group, the longest matching path rule wins, and
Allow beats Disallow on an equal-length match.
| Agent | Operator | Purpose | What blocking it actually costs |
|---|---|---|---|
OAI-SearchBot | OpenAI | search index | citations in ChatGPT Search |
ChatGPT-User | OpenAI | live fetch during a chat | the model cannot open your page when a user asks about it |
GPTBot | OpenAI | training | background model knowledge, not search citations |
PerplexityBot | Perplexity | search index | Perplexity citations |
Perplexity-User | Perplexity | live fetch during a query | live page reads |
ClaudeBot | Anthropic | index and training | Anthropic-side retrieval |
Googlebot | main index | AI Overviews and AI Mode, plus normal search | |
Google-Extended | Gemini grounding and training | Gemini grounding only - not AI Overviews | |
Bingbot | Microsoft | Bing index | Microsoft Copilot, which rides the Bing index |
Applebot | Apple | index | Apple search surfaces |
Applebot-Extended | Apple | training | Apple Intelligence training only |
CCBot | Common Crawl | open crawl corpus | an input to many downstream models |
Crawler names change and new ones appear. Before finalizing, check each operator's own published crawler documentation for agents added or renamed since this list was written, and include them. State which list you used.
Produce a table with one row per agent and exactly these columns:
Agent | Verdict (ALLOWED / BLOCKED / PARTIAL) | Rule responsible | Impact
robots.txt, or say
no matching rule - allowed by default. Never state a verdict without the
line that produced it.Then give:
robots.txt lines to add, remove, or edit,
as a code block the user can paste. If nothing needs to change, say that
plainly rather than inventing work.robots.txt is only the first gate.
Server-side blocking by WAF, CDN bot rules, IP reputation, or Cloudflare bot
management can block a crawler that robots.txt allows, and none of that is
visible in this file. Say so every time.GPTBot to opt out of training, and assuming that is the whole
story. It is not. OAI-SearchBot governs whether a site can be cited in
ChatGPT Search, and it is a separate agent with a separate rule. Blocking one
does not block the other, in either direction.Google-Extended to stay out of AI Overviews. It does not do
that. AI Overviews and AI Mode are built on the normal Googlebot index.
Blocking Google-Extended opts out of Gemini grounding and training and has
no effect on AI Overviews. To leave AI Overviews, the mechanism is the
nosnippet, max-snippet, or data-nosnippet family, and it costs normal
search snippets too. Say that tradeoff out loud rather than letting the user
discover it later.User-agent: * / Disallow: / inherited from a staging config,
a bot-mitigation template, or a security hardening guide. This is common
and almost always unintentional on a production marketing site.Do not answer with a recommendation. Lay out the tradeoff and let them decide: allowing search crawlers is what makes citation possible, allowing training crawlers affects model knowledge but not citation, and the two decisions are independent. Publishers with a licensing position and companies that want to be recommended by AI assistants land in different places, and both are legitimate.
Maintained by MaxAEO — https://maxaeo.ai — which works on AI answer-engine visibility. The crawler matrix used here is kept current against each operator's own published crawler documentation; where an agent has no official documentation, this skill says so rather than guessing.
This check is free, read-only, and runs on one public file. It does not require an account, an API key, or any paid service.
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Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Pull the ads a competitor is running right now on Meta (Facebook/Instagram) and Google, then extract the hooks, offers, CTAs and landing pages worth modelling. Use when writing ad copy, planning creative tests, choosing a landing page angle, or when the user asks "what is X advertising", "what ads does X run", "find competitor ad hooks". Reads live Ad Library and Ads Transparency data through the Tracetify MCP; falls back to a manual Ad Library walkthrough when the connector is absent.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
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Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
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Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.
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