Analytics API - Factory Documentation

The Analytics API provides programmatic access to organization-level usage data for Factory. Query Factory Standard Credits consumption, tool invocations, user activity, and productivity metrics across your entire organization.

Quick Start

curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/tokens?startDate=2026-01-14&endDate=2026-01-28"

Authentication

All requests require a Factory API key in the Authorization header:

Authorization: Bearer fk-your-api-key

Generate API keys at app.factory.ai/settings/api-keys.

Permissions

Only users with Manager or Owner roles can access the Analytics API. Members and guests will receive a 403 error.

Base URL

https://api.factory.ai/api/v1/analytics

Response Format

All responses follow a consistent envelope structure:

{
  "data": [ ... ],
  "meta": { ... }
}

Field	Type	Description
`data`	array	Array of result objects (one per day, or per group when using `group_by`)
`meta`	object	Request metadata: `org_id`, `start_date`, `end_date`, and pagination info for `/users`

Endpoints

The Analytics API provides five endpoints, each focused on a specific category of metrics:

Endpoint	Description
`/tokens`	Factory Standard Credits consumption by model and user
`/tools`	Tool invocations and autonomy metrics
`/activity`	Daily, weekly, and monthly active users
`/productivity`	File operations and git activity
`/users`	Per-user metrics with pagination

Understanding `group_by`

Several endpoints support a group_by parameter. Here’s how it works:

Without group_by: Returns one row per day with nested breakdowns (e.g., by_tool, daily_active_users_by_client). Use this when you want all dimensions in a single response.
With group_by: Flattens one of those nested arrays into separate rows. Each row has a group_key field identifying the dimension value. Use this when piping data into tools that expect flat rows (spreadsheets, BI tools, time-series databases).

For example, /activity without group_by returns daily_active_users_by_client as an object. With group_by=client, you get separate rows for terminal-ui, web, and non-interactive-cli - useful for plotting each client type as its own line on a chart.

Factory Standard Credits Usage

Returns daily Factory Standard Credits consumption across your organization.

GET /tokens

Query Parameters

Parameter	Type	Required	Description
`startDate`	string	Yes	Start date in `YYYY-MM-DD` format
`endDate`	string	Yes	End date in `YYYY-MM-DD` format
`group_by`	string	No	Set to `model` to group results by model

Response Fields

Field	Type	Description
`date`	string	Date in `YYYY-MM-DD` format
`billable_tokens`	number	Factory Standard Credits consumed, computed from raw input and raw output tokens with cache discounts
`input_tokens`	number	Raw input tokens sent to model
`output_tokens`	number	Tokens generated by model
`cache_read_tokens`	number	Tokens read from prompt cache
`cache_write_tokens`	number	Tokens written to prompt cache
`by_model`	array	Breakdown per model
`by_user`	array	Breakdown per user

Example

# Factory Standard Credits usage for a date range
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/tokens?startDate=2026-01-14&endDate=2026-01-28"

# Grouped by model
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/tokens?startDate=2026-01-15&endDate=2026-01-15&group_by=model"

Tool Usage

Returns daily tool invocations, MCP usage, skills, slash commands, and autonomy metrics.

GET /tools

Query Parameters

Parameter	Type	Required	Description
`startDate`	string	Yes	Start date in `YYYY-MM-DD` format
`endDate`	string	Yes	End date in `YYYY-MM-DD` format
`group_by`	string	No	Set to `tool_name` to group results by tool

Response

{
  "data": [
    {
      "date": "2026-01-15",
      "tool_calls": 45000,
      "by_tool": [
        { "tool": "Read", "invocations": 12500 },
        { "tool": "Edit", "invocations": 8200 },
        { "tool": "Execute", "invocations": 6100 }
      ],
      "mcp_users_with_mcp": 42,
      "mcp_by_server": [
        { "server": "github", "invocations": 1200 },
        { "server": "notion", "invocations": 850 }
      ],
      "skills_invocations": 320,
      "skills_by_name": [
        { "name": "browser", "count": 180 },
        { "name": "frontend-ui", "count": 95 }
      ],
      "slash_commands_invocations": 1500,
      "slash_commands_by_name": [
        { "name": "review", "count": 420 },
        { "name": "test", "count": 380 }
      ],
      "hooks_invocations": 2800,
      "hooks_by_event": [
        { "event": "PostToolUse", "matcher": "*.ts", "command": "eslint --fix", "count": 1200 }
      ],
      "web_users": 42,
      "autonomy_ratio_avg": 8.5,
      "autonomy_ratio_p50": 6.2,
      "autonomy_ratio_p90": 18.4,
      "tool_calls_per_session_avg": 45.2,
      "user_turns_per_session_avg": 5.3,
      "tool_autonomy_level_ratio": {
        "auto_high": 0.35,
        "auto_medium": 0.42,
        "auto_low": 0.18,
        "manual": 0.05
      }
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15"
  }
}

Response Fields

Field	Type	Description
`date`	string	Date in `YYYY-MM-DD` format
`tool_calls`	number	Total tool invocations
`by_tool`	array	Breakdown by tool name
`mcp_users_with_mcp`	number	Users who used MCP servers
`mcp_by_server`	array	Invocations per MCP server
`skills_invocations`	number	Total skill activations
`skills_by_name`	array	Breakdown by skill
`slash_commands_invocations`	number	Total slash command uses
`slash_commands_by_name`	array	Breakdown by command
`hooks_invocations`	number	Total hook executions
`hooks_by_event`	array	Breakdown by event type
`web_users`	number	Users who used web/workspace interface
`autonomy_ratio_avg`	number	Average tool calls per user turn
`autonomy_ratio_p50`	number	Median autonomy ratio
`autonomy_ratio_p90`	number	90th percentile autonomy ratio
`tool_calls_per_session_avg`	number	Average tool calls per session
`user_turns_per_session_avg`	number	Average user messages per session
`tool_autonomy_level_ratio`	object	Distribution of autonomy levels

Grouped Response

When group_by=tool_name, returns one row per tool per day inside data:

{
  "data": [
    {
      "date": "2026-01-15",
      "group_key": "Read",
      "tool_calls": 12500
    },
    {
      "date": "2026-01-15",
      "group_key": "Edit",
      "tool_calls": 8200
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15"
  }
}

User Activity

Returns daily, weekly, and monthly active users along with session counts.

GET /activity

Query Parameters

Parameter	Type	Required	Description
`startDate`	string	Yes	Start date in `YYYY-MM-DD` format
`endDate`	string	Yes	End date in `YYYY-MM-DD` format
`group_by`	string	No	Set to `client` to group by client type

Response

{
  "data": [
    {
      "date": "2026-01-15",
      "daily_active_users": 128,
      "weekly_active_users": 312,
      "monthly_active_users": 485,
      "daily_active_users_by_client": {
        "terminal-ui": 95,
        "web": 42,
        "non-interactive-cli": 18
      },
      "sessions": 890,
      "messages": 12500,
      "user_messages": 4200
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15"
  }
}

Response Fields

Field	Type	Description
`date`	string	Date in `YYYY-MM-DD` format
`daily_active_users`	number	Unique users on this day
`weekly_active_users`	number	Unique users in trailing 7 days
`monthly_active_users`	number	Unique users in trailing 30 days
`daily_active_users_by_client`	object	DAU breakdown by client type
`sessions`	number	Total sessions started
`messages`	number	Total messages (user + assistant)
`user_messages`	number	Messages from users only

Client Types

Client	Description
`terminal-ui`	Interactive CLI sessions
`web`	Factory App
`non-interactive-cli`	Headless/automated CLI (`droid exec`)

Grouped Response

When group_by=client, returns one row per client type per day inside data:

{
  "data": [
    {
      "date": "2026-01-15",
      "group_key": "terminal-ui",
      "daily_active_users": 95
    },
    {
      "date": "2026-01-15",
      "group_key": "web",
      "daily_active_users": 42
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15"
  }
}

Productivity

Returns daily file operations and git activity.

GET /productivity

Query Parameters

Parameter	Type	Required	Description
`startDate`	string	Yes	Start date in `YYYY-MM-DD` format
`endDate`	string	Yes	End date in `YYYY-MM-DD` format

Response

{
  "data": [
    {
      "date": "2026-01-15",
      "files_created": 245,
      "files_edited": 1820,
      "by_extension": [
        { "extension": ".ts", "count": 890 },
        { "extension": ".tsx", "count": 420 },
        { "extension": ".py", "count": 310 }
      ],
      "by_language": [
        { "language": "TypeScript", "count": 1310 },
        { "language": "Python", "count": 310 }
      ],
      "git_commits": 156,
      "git_prs_created": 42
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15"
  }
}

Response Fields

Field	Type	Description
`date`	string	Date in `YYYY-MM-DD` format
`files_created`	number	New files created by agent
`files_edited`	number	Existing files modified by agent
`by_extension`	array	Operations per file extension
`by_language`	array	Operations per programming language
`git_commits`	number	Commits made via agent
`git_prs_created`	number	Pull requests created via agent

Per-User Metrics

Returns detailed metrics per user with cursor-based pagination.

GET /users

Query Parameters

Parameter	Type	Required	Description
`startDate`	string	Yes	Start date in `YYYY-MM-DD` format
`endDate`	string	Yes	End date in `YYYY-MM-DD` format
`limit`	number	No	Users per page, 1-100 (default: 20)
`cursor`	string	No	User ID for pagination (from `next_cursor`)

Response

{
  "data": [
    {
      "user_id": "user_01HPMQ7NXKHM7Y7PR3TTZY3JZS",
      "user_email": "developer@company.com",
      "date": "2026-01-15",
      "tool_calls": 1250,
      "billable_tokens": 450000,
      "primary_model": "claude-sonnet-4-20250514",
      "primary_model_tier": "standard",
      "files_created": 12,
      "files_edited": 85,
      "git_commits": 8,
      "git_prs_created": 2,
      "mcp_calls": 45,
      "skill_calls": 8,
      "slash_commands": 22,
      "hooks": 120,
      "sessions": 15,
      "messages": 180,
      "user_messages": 62,
      "assistant_messages": 118,
      "autonomy_ratio": 9.2,
      "delegation_level": "auto-high",
      "languages": ["TypeScript", "Python", "Go"]
    }
  ],
  "meta": {
    "org_id": "org_01HPMQ6ABCDE...",
    "start_date": "2026-01-15",
    "end_date": "2026-01-15",
    "has_more": true,
    "next_cursor": "user_01HPMQ8ABCDE7Y7PR3TTZY4KLM"
  }
}

Response Fields

Field	Type	Description
`user_id`	string	Unique user identifier
`user_email`	string \| null	User email
`date`	string	Date in `YYYY-MM-DD` format
`tool_calls`	number	Tool invocations by this user
`billable_tokens`	number	Factory Standard Credits consumed by this user
`primary_model`	string	Most-used model
`primary_model_tier`	string	Model tier (`standard` or `thinking`)
`files_created`	number	Files created
`files_edited`	number	Files edited
`git_commits`	number	Commits made
`git_prs_created`	number	Pull requests created
`mcp_calls`	number	MCP tool invocations
`skill_calls`	number	Skill activations
`slash_commands`	number	Slash command uses
`hooks`	number	Hook executions
`sessions`	number	Sessions started
`messages`	number	Total messages
`user_messages`	number	User messages only
`assistant_messages`	number	Assistant messages
`autonomy_ratio`	number	Tool calls per user turn
`delegation_level`	string	Primary autonomy mode
`languages`	array	Programming languages worked in

Delegation Levels

Level	Description
`auto-high`	Maximum autonomy, minimal confirmations
`auto-medium`	Balanced autonomy with some confirmations
`auto-low`	Limited autonomy, frequent confirmations
`spec`	Specification mode, planning before execution
`manual`	Full manual control, confirm each action

Pagination

Use cursor-based pagination to iterate through users:

# First page
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/users?startDate=2026-01-15&endDate=2026-01-15&limit=50"

# Next page
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/users?startDate=2026-01-15&endDate=2026-01-15&limit=50&cursor=user_01HPMQ8ABCDE7Y7PR3TTZY4KLM"

Important Constraints

Date Requirements

Format: All dates must be YYYY-MM-DD
Timezone: UTC only (no timezone parameter)
Data availability: Data is available through yesterday (UTC). Requesting today’s date returns a 400 error.
Historical data: Available from January 14, 2026

Rate Limits

Rate limits vary by plan. Contact us for specifics or if you need higher limits for dashboard or automation use cases.

Error Handling

The API returns standard HTTP status codes:

Status	Description
`400`	Invalid date format, today’s date requested, or limit out of range
`401`	Missing or invalid API key
`403`	Insufficient permissions (requires Manager or Owner role)
`500`	Internal error

Error Response Format

{
  "title": "Bad Request",
  "detail": "Cannot query today's date - analytics data has a 24-hour lag",
  "status": 400,
  "requestId": "req_01HPMQ9WXYZ..."
}

Data Pipeline

Analytics data flows through the following pipeline:

CLI/Daemon → OTEL Events → BigQuery (raw) → dbt models → API

Source: OpenTelemetry spans from the CLI and daemon
Processing: Daily batch aggregation via dbt
Availability: Data is available the day after it’s generated

Data Quality Notes

A few known data quality considerations:

MCP server names: Some duplicates exist due to case sensitivity (e.g., axiom vs Axiom)
Tool names: Approximately 0.006% of entries contain parsing artifacts
User counts: A user active on multiple clients counts once in DAU but appears in each client breakdown

Use Cases

Cost Monitoring Dashboard

Track usage trends and identify cost drivers:

# Daily usage for the month
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/tokens?startDate=2026-01-14&endDate=2026-01-28"

Adoption Tracking

Monitor DAU/WAU/MAU and identify adoption patterns:

# Activity metrics with client breakdown
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/activity?startDate=2026-01-14&endDate=2026-01-28&group_by=client"

Team Productivity Reports

Measure output and efficiency:

# Productivity metrics
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/productivity?startDate=2026-01-14&endDate=2026-01-28"

Individual Performance

Export per-user metrics for team leads:

# Paginate through all users
curl -H "Authorization: Bearer $FACTORY_API_KEY" \
  "https://api.factory.ai/api/v1/analytics/users?startDate=2026-01-15&endDate=2026-01-15&limit=100"

​Quick Start

​Authentication

​Permissions

​Base URL

​Response Format

​Endpoints

​Understanding group_by

​Factory Standard Credits Usage

​Query Parameters

​Response Fields

​Example

​Tool Usage

​Query Parameters

​Response

​Response Fields

​Grouped Response

​User Activity

​Query Parameters

​Response

​Response Fields

​Client Types

​Grouped Response

​Productivity

​Query Parameters

​Response

​Response Fields

​Per-User Metrics

​Query Parameters

​Response

​Response Fields

​Delegation Levels

​Pagination

​Important Constraints

​Date Requirements

​Rate Limits

​Error Handling

​Error Response Format

​Data Pipeline

​Data Quality Notes

​Use Cases

​Cost Monitoring Dashboard

​Adoption Tracking

​Team Productivity Reports

​Individual Performance

Quick Start

Authentication

Permissions

Base URL

Response Format

Endpoints

Understanding `group_by`

Factory Standard Credits Usage

Query Parameters

Response Fields

Example

Tool Usage

Query Parameters

Response

Response Fields

Grouped Response

User Activity

Query Parameters

Response

Response Fields

Client Types

Grouped Response

Productivity

Query Parameters

Response

Response Fields

Per-User Metrics

Query Parameters

Response

Response Fields

Delegation Levels

Pagination

Important Constraints

Date Requirements

Rate Limits

Error Handling

Error Response Format

Data Pipeline

Data Quality Notes

Use Cases

Cost Monitoring Dashboard

Adoption Tracking

Team Productivity Reports

Individual Performance