CrowTerminal
AI command-line assistant service for agent memory tracking, engagement analysis, webhook events, and platform intelligence.
Helps automation builders inspect how an agent's markdown drives engagement, follow client memory changes over time, and listen for webhook events.
Example Use Cases
These are the CrowTerminal actions Snow can use when building apps with you. Connecting an account does not make Snow run these on its own.
Tool to bulk ingest up to 50 analytics data points at once to CrowTerminal. Use when you need to efficiently push large amounts of platform analytics data for content creators across social media platforms. Ideal for batch uploads of retention, engagement, views, and other metrics.
Tool to get detailed status of each CrowTerminal service component. Returns current health status, latency, and summary statistics for all monitored components (database, cache, APIs, webhooks). Use when checking system health or diagnosing service issues.
Tool to retrieve valid data types for ingestion across platforms. Returns available data types for TikTok, Instagram, and YouTube that can be used for data ingestion operations.
Retrieve CrowTerminal service status including overall health, component metrics, and uptime data. Use when you need to check the operational status of CrowTerminal services or monitor system health. No authentication required.
Tool to retrieve historical uptime data for CrowTerminal agents. Use when you need to check system reliability, view uptime percentages for 24h/7d periods, or review recent service incidents.
Tool to ingest platform analytics data from TikTok Studio, Instagram Insights, or YouTube Analytics. Use when you need to push retention curves, demographics, traffic sources, or other engagement metrics for analysis. Supports both video-specific and channel-level data ingestion.
Tool to update an existing webhook configuration in CrowTerminal. Use when you need to modify webhook URL, change event subscriptions, or enable/disable a webhook.
Tool to validate proposed changes against historical data before updating memory. Use when you need to check if proposed changes contradict historical patterns and receive warnings or recommendations.
Tool to analyze engagement correlation for every field in your agent's markdown. Use when you need to understand which agent configuration fields drive engagement and get specific recommendations for improvement. Returns similarity to best/worst performing versions and field-by-field analysis.
Tool to read memory for multiple clients at once (up to 50). Use when you need to efficiently retrieve memory data for multiple creators in a single API call.