Usage Report

Get Messages Usage Report

GET/v1/organizations/usage_report/messages

Get Claude Code Usage Report

GET/v1/organizations/usage_report/claude_code

ModelsExpand Collapse

ClaudeCodeUsageReport = object { data, has_more, next_page }

data: array of object { actor, core_metrics, customer_type, 6 more }

List of Claude Code usage records for the requested date.

actor: object { email_address, type } or object { api_key_name, type }

The user or API key that performed the Claude Code actions.

Accepts one of the following:

UserActor = object { email_address, type }

email_address: string

Email address of the user who performed Claude Code actions.

type: "user_actor"

APIActor = object { api_key_name, type }

api_key_name: string

Name of the API key used to perform Claude Code actions.

type: "api_actor"

core_metrics: object { commits_by_claude_code, lines_of_code, num_sessions, pull_requests_by_claude_code }

Core productivity metrics measuring Claude Code usage and impact.

commits_by_claude_code: number

Number of git commits created through Claude Code's commit functionality.

lines_of_code: object { added, removed }

Statistics on code changes made through Claude Code.

added: number

Total number of lines of code added across all files by Claude Code.

removed: number

Total number of lines of code removed across all files by Claude Code.

num_sessions: number

Number of distinct Claude Code sessions initiated by this actor.

pull_requests_by_claude_code: number

Number of pull requests created through Claude Code's PR functionality.

customer_type: "api" or "subscription"

Type of customer account (api for API customers, subscription for Pro/Team customers).

Accepts one of the following:

"api"

"subscription"

date: string

UTC date for the usage metrics in YYYY-MM-DD format.

model_breakdown: array of object { estimated_cost, model, tokens }

Token usage and cost breakdown by AI model used.

estimated_cost: object { amount, currency }

Estimated cost for using this model

amount: number

Estimated cost amount in minor currency units (e.g., cents for USD).

currency: string

Currency code for the estimated cost (e.g., 'USD').

model: string

Name of the AI model used for Claude Code interactions.

tokens: object { cache_creation, cache_read, input, output }

Token usage breakdown for this model

cache_creation: number

Number of cache creation tokens consumed by this model.

cache_read: number

Number of cache read tokens consumed by this model.

input: number

Number of input tokens consumed by this model.

output: number

Number of output tokens generated by this model.

organization_id: string

ID of the organization that owns the Claude Code usage.

terminal_type: string

Type of terminal or environment where Claude Code was used.

tool_actions: map[object { accepted, rejected } ]

Breakdown of tool action acceptance and rejection rates by tool type.

accepted: number

Number of tool action proposals that the user accepted.

rejected: number

Number of tool action proposals that the user rejected.

subscription_type: optional "enterprise" or "team"

Subscription tier for subscription customers. null for API customers.

Accepts one of the following:

"enterprise"

"team"

has_more: boolean

True if there are more records available beyond the current page.

next_page: string

Opaque cursor token for fetching the next page of results, or null if no more pages are available.

MessagesUsageReport = object { data, has_more, next_page }

data: array of object { ending_at, results, starting_at }

ending_at: string

End of the time bucket (exclusive) in RFC 3339 format.

results: array of object { api_key_id, cache_creation, cache_read_input_tokens, 9 more }

List of usage items for this time bucket. There may be multiple items if one or more group_by[] parameters are specified.

api_key_id: string

ID of the API key used. null if not grouping by API key or for usage in the Anthropic Console.

cache_creation: object { ephemeral_1h_input_tokens, ephemeral_5m_input_tokens }

The number of input tokens for cache creation.

ephemeral_1h_input_tokens: number

The number of input tokens used to create the 1 hour cache entry.

ephemeral_5m_input_tokens: number

The number of input tokens used to create the 5 minute cache entry.

cache_read_input_tokens: number

The number of input tokens read from the cache.

context_window: "0-200k" or "200k-1M"

Context window used. null if not grouping by context window.

Accepts one of the following:

"0-200k"

"200k-1M"

inference_geo: string

Inference geo used matching requests' inference_geo parameter if set, otherwise the workspace's default_inference_geo. For models that do not support specifying inference_geo the value is "not_available". Always null if not grouping by inference geo.

model: string

Model used. null if not grouping by model.

output_tokens: number

The number of output tokens generated.

server_tool_use: object { web_search_requests }

Server-side tool usage metrics.

web_search_requests: number

The number of web search requests made.

service_tier: "standard" or "batch" or "priority" or 3 more

Service tier used. null if not grouping by service tier.

Accepts one of the following:

"standard"

"batch"

"priority"

"priority_on_demand"

"flex"

"flex_discount"

speed: "standard" or "fast"

Speed of the usage (research preview). null if not grouping by speed. Only returned when the fast-mode-2026-02-01 beta header is provided.

Accepts one of the following:

"standard"

"fast"

uncached_input_tokens: number

The number of uncached input tokens processed.

workspace_id: string

ID of the Workspace used. null if not grouping by workspace or for the default workspace.

starting_at: string

Start of the time bucket (inclusive) in RFC 3339 format.

has_more: boolean

Indicates if there are more results.

next_page: string

Token to provide in as page in the subsequent request to retrieve the next page of data.

Usage Report

Get Messages Usage Report

GET/v1/organizations/usage_report/messages

Get Claude Code Usage Report

GET/v1/organizations/usage_report/claude_code

ModelsExpand Collapse

ClaudeCodeUsageReport = object { data, has_more, next_page }

data: array of object { actor, core_metrics, customer_type, 6 more }

List of Claude Code usage records for the requested date.

actor: object { email_address, type } or object { api_key_name, type }

The user or API key that performed the Claude Code actions.

Accepts one of the following:

UserActor = object { email_address, type }

email_address: string

Email address of the user who performed Claude Code actions.

type: "user_actor"

APIActor = object { api_key_name, type }

api_key_name: string

Name of the API key used to perform Claude Code actions.

type: "api_actor"

core_metrics: object { commits_by_claude_code, lines_of_code, num_sessions, pull_requests_by_claude_code }

Core productivity metrics measuring Claude Code usage and impact.

commits_by_claude_code: number

Number of git commits created through Claude Code's commit functionality.

lines_of_code: object { added, removed }

Statistics on code changes made through Claude Code.

added: number

Total number of lines of code added across all files by Claude Code.

removed: number

Total number of lines of code removed across all files by Claude Code.

num_sessions: number

Number of distinct Claude Code sessions initiated by this actor.

pull_requests_by_claude_code: number

Number of pull requests created through Claude Code's PR functionality.

customer_type: "api" or "subscription"

Type of customer account (api for API customers, subscription for Pro/Team customers).

Accepts one of the following:

"api"

"subscription"

date: string

UTC date for the usage metrics in YYYY-MM-DD format.

model_breakdown: array of object { estimated_cost, model, tokens }

Token usage and cost breakdown by AI model used.

estimated_cost: object { amount, currency }

Estimated cost for using this model

amount: number

Estimated cost amount in minor currency units (e.g., cents for USD).

currency: string

Currency code for the estimated cost (e.g., 'USD').

model: string

Name of the AI model used for Claude Code interactions.

tokens: object { cache_creation, cache_read, input, output }

Token usage breakdown for this model

cache_creation: number

Number of cache creation tokens consumed by this model.

cache_read: number

Number of cache read tokens consumed by this model.

input: number

Number of input tokens consumed by this model.

output: number

Number of output tokens generated by this model.

organization_id: string

ID of the organization that owns the Claude Code usage.

terminal_type: string

Type of terminal or environment where Claude Code was used.

tool_actions: map[object { accepted, rejected } ]

Breakdown of tool action acceptance and rejection rates by tool type.

accepted: number

Number of tool action proposals that the user accepted.

rejected: number

Number of tool action proposals that the user rejected.

subscription_type: optional "enterprise" or "team"

Subscription tier for subscription customers. null for API customers.

Accepts one of the following:

"enterprise"

"team"

has_more: boolean

True if there are more records available beyond the current page.

next_page: string

Opaque cursor token for fetching the next page of results, or null if no more pages are available.

MessagesUsageReport = object { data, has_more, next_page }

data: array of object { ending_at, results, starting_at }

ending_at: string

End of the time bucket (exclusive) in RFC 3339 format.

results: array of object { api_key_id, cache_creation, cache_read_input_tokens, 9 more }

List of usage items for this time bucket. There may be multiple items if one or more group_by[] parameters are specified.

api_key_id: string

ID of the API key used. null if not grouping by API key or for usage in the Anthropic Console.

cache_creation: object { ephemeral_1h_input_tokens, ephemeral_5m_input_tokens }

The number of input tokens for cache creation.

ephemeral_1h_input_tokens: number

The number of input tokens used to create the 1 hour cache entry.

ephemeral_5m_input_tokens: number

The number of input tokens used to create the 5 minute cache entry.

cache_read_input_tokens: number

The number of input tokens read from the cache.

context_window: "0-200k" or "200k-1M"

Context window used. null if not grouping by context window.

Accepts one of the following:

"0-200k"

"200k-1M"

inference_geo: string

model: string

Model used. null if not grouping by model.

output_tokens: number

The number of output tokens generated.

server_tool_use: object { web_search_requests }

Server-side tool usage metrics.

web_search_requests: number

The number of web search requests made.

service_tier: "standard" or "batch" or "priority" or 3 more

Service tier used. null if not grouping by service tier.

Accepts one of the following:

"standard"

"batch"

"priority"

"priority_on_demand"

"flex"

"flex_discount"

speed: "standard" or "fast"

Speed of the usage (research preview). null if not grouping by speed. Only returned when the fast-mode-2026-02-01 beta header is provided.

Accepts one of the following:

"standard"

"fast"

uncached_input_tokens: number

The number of uncached input tokens processed.

workspace_id: string

ID of the Workspace used. null if not grouping by workspace or for the default workspace.

starting_at: string

Start of the time bucket (inclusive) in RFC 3339 format.

has_more: boolean

Indicates if there are more results.

next_page: string

Token to provide in as page in the subsequent request to retrieve the next page of data.