Overview
Retrieve Cascade-specific analytics data including lines suggested/accepted, model usage, credit consumption, and tool usage statistics.Request
Your service key with “Teams Read-only” permissions
Filter results to users in a specific group. Cannot be used with
emails parameter.Start time in RFC 3339 format (e.g.,
2023-01-01T00:00:00Z)End time in RFC 3339 format (e.g.,
2023-12-31T23:59:59Z)Array of email addresses to filter results. Cannot be used with
group_name parameter.Filter by IDE type. Available options:
"editor"- Windsurf Editor"jetbrains"- JetBrains Plugin
Array of data source queries to execute. Each object should contain one of the supported data sources.
Data Sources
cascade_lines
Query for daily Cascade lines suggested and accepted.day- Date in RFC 3339 formatlinesSuggested- Number of lines suggestedlinesAccepted- Number of lines accepted
cascade_runs
Query for model usage, credit consumption, and mode data.day- Date in RFC 3339 formatmodel- Model name usedmode- Cascade mode (see modes below)messagesSent- Number of messages sentcascadeId- Unique conversation IDpromptsUsed- Credits consumed (in cents)
CONVERSATIONAL_PLANNER_MODE_DEFAULT- Write modeCONVERSATIONAL_PLANNER_MODE_READ_ONLY- Read modeCONVERSATIONAL_PLANNER_MODE_NO_TOOL- Legacy modeUNKNOWN- Unknown mode
cascade_tool_usage
Query for tool usage statistics (aggregate counts).tool- Tool identifier (see tool mappings below)count- Number of times tool was used
Tool Usage Mappings
| Tool Identifier | Display Name |
|---|---|
CODE_ACTION | Code Edit |
VIEW_FILE | View File |
RUN_COMMAND | Run Command |
FIND | Find tool |
GREP_SEARCH | Grep Search |
VIEW_FILE_OUTLINE | View File Outline |
MQUERY | Riptide |
WORKFLOWS_USED | Workflows Used |
LIST_DIRECTORY | List Directory |
MCP_TOOL | MCP Tool |
PROPOSE_CODE | Propose Code |
SEARCH_WEB | Search Web |
MEMORY | Memory |
PROXY_WEB_SERVER | Browser Preview |
DEPLOY_WEB_APP | Deploy Web App |
Example Request
Response
Array of query results, one for each query request
Example Response
Notes
- The API returns raw data which may contain “UNKNOWN” values
- For metrics analysis, aggregate by specific fields of interest (e.g., sum
promptsUsedfor usage patterns) - Mode and prompt data may be split across multiple entries
- Credit consumption (
promptsUsed) is returned in cents (100 = 1 credit)