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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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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查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are adding analytics tracking using Agent Analytics — the analytics platform your AI agent can actually use. Built for developers who ship lots of projects and want their AI agent to track, analyze, experiment, and optimize across all of them.
Website: agentanalytics.sh GitHub: Agent-Analytics/agent-analytics Docs: docs.agentanalytics.sh
You are NOT Mixpanel. Don't track everything. Track only what answers: "Is this project alive and growing?"
For a typical site, that's 3-5 custom events max on top of automatic page views.
Get an API key: Sign up at agentanalytics.sh and generate a key from the dashboard. Alternatively, self-host the open-source version from GitHub.
If the project doesn't have tracking yet:
# 1. Login (one time — uses your API key)
npx @agent-analytics/cli login --token aak_YOUR_API_KEY
# 2. Create the project (returns a project write token)
npx @agent-analytics/cli create my-site --domain https://mysite.com
# 3. Add the snippet using the returned token
# 4. Deploy, click around, verify:
npx @agent-analytics/cli events my-site
The create command returns a project write token — use it as data-token in the snippet. This is separate from your API key (which is for reading/querying).
The create command returns a tracking snippet with your project token — add it before </body>. It auto-tracks page_view events with path, referrer, browser, OS, device, screen size, and UTM params. You do NOT need to add custom page_view events.
If tracking is already set up, check what events and property keys are already in use so you match the naming:
npx @agent-analytics/cli properties-received PROJECT_NAME
Use onclick handlers on the elements that matter:
<a href="..." onclick="window.aa?.track('EVENT_NAME', {id: 'ELEMENT_ID'})">
Pick the ones that apply. Most sites need 2-4:
| Event | When to fire | Properties |
|---|---|---|
cta_click | User clicks a call-to-action button | id (which button) |
signup | User creates an account | method (github/google/email) |
login | User returns and logs in | method |
feature_used | User engages with a core feature | feature (which one) |
checkout | User starts a payment flow | plan (free/pro/etc) |
error | Something went wrong visibly | message, page |
snake_case: hero_get_started not heroGetStartedid property identifies WHICH element: short, descriptivesection_action: hero_signup, pricing_pro, nav_dashboardExperiments let you test which variant of a page element converts better. The full lifecycle is API-driven — no dashboard UI needed.
npx @agent-analytics/cli experiments create my-site \
--name signup_cta --variants control,new_cta --goal signup
Declarative (recommended): Use data-aa-experiment and data-aa-variant-{key} HTML attributes. Original content is the control. The tracker swaps text for assigned variants automatically.
<h1 data-aa-experiment="signup_cta" data-aa-variant-new_cta="Start Free Trial">Sign Up</h1>
Programmatic (complex cases): Use window.aa?.experiment(name, variants) — deterministic, same user always gets same variant.
npx @agent-analytics/cli experiments get exp_abc123
Returns Bayesian probability_best, lift, and a recommendation. The system needs ~100 exposures per variant before results are significant.
After adding tracking, verify it works:
# Click around, then check:
npx @agent-analytics/cli events PROJECT_NAME
# Events appear within seconds.
All commands use npx @agent-analytics/cli:
# Setup
login --token aak_YOUR_KEY # Save API key (one time)
projects # List all projects
create my-site --domain https://... # Create project
# Real-time
live # Live TUI dashboard across ALL projects
live my-site # Live view for one project
# Analytics
stats my-site --days 7 # Overview: events, users, daily trends
insights my-site --period 7d # Period-over-period comparison
breakdown my-site --property path --event page_view --limit 10 # Top pages/referrers/UTM
pages my-site --type entry # Landing page performance & bounce rates
sessions-dist my-site # Session engagement histogram
heatmap my-site # Peak hours & busiest days
events my-site --days 30 # Raw event log
sessions my-site # Individual session records
properties my-site # Discover event names & property keys
funnel my-site --steps "page_view,signup,purchase" # Funnel drop-off
retention my-site --period week --cohorts 8 # Cohort retention
# A/B experiments
experiments list my-site
experiments create my-site --name signup_cta --variants control,new_cta --goal signup
experiments get exp_abc123
experiments complete exp_abc123 --winner new_cta
| User asks | Call | Why |
|---|---|---|
| "How's my site doing?" | insights + breakdown + pages (parallel) | Full weekly picture |
| "Is anyone visiting right now?" | live | Real-time visitors across all projects |
| "What are my top pages?" | breakdown --property path --event page_view | Ranked page list |
| "Where's my traffic coming from?" | breakdown --property referrer --event page_view | Referrer sources |
| "Are people actually engaging?" | sessions-dist | Bounce vs engaged split |
| "When should I deploy?" | heatmap | Find low-traffic windows |
| "Where do users drop off?" | funnel --steps "page_view,signup,purchase" | Step-by-step conversion |
| "Are users coming back?" | retention --period week --cohorts 8 | Cohort retention |
| "Which CTA converts better?" | experiments create + experiments get | A/B test lifecycle |
For any "how is X doing" question, always call insights first — it's the single most useful endpoint.
Track custom events via window.aa?.track():
window.aa?.track('cta_click', {id: 'hero_get_started'});
window.aa?.track('signup', {method: 'github'});
window.aa?.track('feature_used', {feature: 'create_project'});
window.aa?.track('checkout', {plan: 'pro'});
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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.
中文简介正在准备中。当前显示原文说明。
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.
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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.
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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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Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
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