Usage

Anona meters every operation in credits and enforces a per-minute rate limit. These endpoints report where you stand.

Token counts on Reason and ask-about-user responses cover the whole internal reasoning pass — several LLM calls of retrieval and synthesis — not just the answer text you receive. A short answer with a few hundred output_tokens is normal, and those totals are what credits are charged on.

Method and path	Auth	Returns
`GET /v1/usage/me`	API key	Current credit balance and rate limit for the calling key’s organization.
`GET /v1/usage`	Dashboard session	Credit usage over a period, with a time series.
`GET /v1/usage/breakdown`	Dashboard session	Per-operation breakdown across record, retrieve, reason, and chat.

The organization endpoints back the dashboard and need a signed-in session — an API key gets 401 session_required there. GET /v1/usage/me is the one to call from inside your application.

Key usage

A lightweight balance check to run from inside your application.

GET https://api.anonalabs.com/v1/usage/me
Authorization: Bearer anona_live_...

curl https://api.anonalabs.com/v1/usage/me \
  -H "Authorization: Bearer anona_live_YOUR_KEY"

usage = client.get_usage()
print(usage["credits_remaining"], usage["rate_limit_per_min"])

const usage = await anona.getUsage();
console.log(usage.credits_remaining, usage.rate_limit_per_min);

{
  "credits_remaining": 1487233,
  "credits_limit": 1500000,
  "credits_used": 12767,
  "rate_limit_per_min": 2000
}

Response headers

Live limits are also returned on every API response, so you can track them without an extra call.

Header	Meaning
`X-RateLimit-Limit`	Requests allowed in the current window.
`X-RateLimit-Remaining`	Requests left in the current window.
`X-RateLimit-Window`	Length of the window.
`X-Credits-Remaining`	Credits left on the organization’s quota.

Organization usage

GET /v1/usage and GET /v1/usage/breakdown both accept a period window and back the usage views in the dashboard.

Memory context

Both also report what memory injection cost your prompts on the drop-in proxy, and how much of it your provider had already seen.

{
  "total_memories_added": 412,
  "total_searches": 1980,
  "total_insights": 37,
  "period_days": 30,
  "series": [ "…" ],
  "memory_context": {
    "calls": 1204,
    "context_tokens": 386400,
    "cache_prefix_tokens": 271900
  }
}

Field	Meaning
`calls`	Proxied chat turns in the period. Direct `retrieve` and `record` calls build no prompt, so they are not counted here.
`context_tokens`	What the injected memory block cost those prompts.
`cache_prefix_tokens`	How much of it was byte-identical to the previous turn’s block for the same space and scope, the part a provider’s prompt cache can match on.

GET /v1/usage/breakdown carries the same two totals per space. Both figures are len/4 estimates, not tokenizer counts. And cache_prefix_tokens is eligibility rather than a saving: an unchanged prefix is what makes a cache hit possible, but whether your provider charged the discounted rate also depends on their minimum cacheable length and their own cache TTL. Raise it with block_order: "stable".

Getting Started

For Agents

API Essentials

Memory (data plane)

LLM Proxy (drop-in)

Account (control plane)

SDKs & MCP

Integrations

Guides

Use Cases

Legal

Changelog

Key usage

Response headers

Organization usage

Memory context

Next steps

Billing

Errors

​Key usage

​Response headers

​Organization usage

​Memory context

​Next steps

Billing

Errors

Key usage

Response headers

Organization usage

Memory context

Next steps