OpenRouter Analytics Schema Discovery
Discover what analytics data is available for querying. The meta endpoint returns live, always-current definitions of metrics, dimensions, filter operators, and granularities.
Prerequisites
Discovery Endpoint
GET https://openrouter.ai/api/v1/analytics/meta
Authorization: Bearer sk-or-v1-...
Or via the openrouter-analytics skill scripts:
cd <openrouter-analytics-skill-path>/scripts && npx tsx discover-schema.ts
Response Shape
{
"data": {
"metrics": [
{ "name": "request_count", "display_label": "Request Count", "is_rate": false, "display_format": "number" }
],
"dimensions": [
{ "name": "model", "display_label": "Model" }
],
"operators": [
{ "name": "eq", "value_type": "scalar" }
],
"granularities": [
{ "name": "day", "display_label": "Day" }
]
}
}
Understanding Metrics
Each metric has:
| Field |
Meaning |
name |
Identifier to use in query requests |
display_label |
Human-readable label |
is_rate |
Whether this is a ratio/rate (averaged, not summed) |
display_format |
How the value should be formatted: number, currency, percent, latency, or throughput |
Time Range Limits
Most volume and cost metrics support time ranges up to 365 days with daily granularity. Latency/throughput metrics and some dimensions (provider, origin, country, finishreason, externaluser, contextlengthbucket, generation_id) are limited to 31-day time ranges. If a query times out, try narrowing the time range or removing latency/throughput metrics and per-generation dimensions.
Metric Categories
Volume metrics (how much):
request_count — number of API requests (up to 365 days)
tokenstotal, tokensprompt, tokens_completion — token counts (up to 365 days)
reasoning_tokens — tokens used for extended thinking (up to 365 days)
cached_tokens — tokens served from cache (up to 365 days)
byokrequestcount — number of BYOK requests (up to 365 days)
guardrailinvokedcount — count of requests that triggered guardrails (31-day limit)
responsecachedcount — count of responses served from cache (31-day limit)
Cost metrics (how much money):
totalusage — total cost in USD, including BYOK inference cost (up to 365 days). Computed as sum(usage) + sum(byokusage_inference) so it reflects true spend for both credits and BYOK users.
byok_usage — BYOK (bring your own key) inference cost in USD (up to 365 days)
credits_usage — all charges billed to OpenRouter credits in USD, including BYOK platform fees (up to 365 days)
openrouter_usage — non-BYOK inference spend in USD; excludes requests made with user-provided keys (31-day limit)
byokfees — BYOK platform fees in USD; the platform fee portion of creditsusage charged on BYOK requests (31-day limit). credits_usage includes both non-BYOK inference charges and these BYOK platform fees.
usage_upstream — provider-side (upstream) cost in USD (up to 365 days)
usage_cache — cache cost component in USD (up to 365 days)
usage_data — data logging cost adjustment in USD; typically negative when a data logging discount applies (up to 365 days)
usage_web — web search cost in USD (up to 365 days)
usageupstreamweb — provider-side web search cost in USD (up to 365 days)
usage_file — file processing cost in USD (31-day limit)
usageupstreamfile — provider-side file processing cost in USD (31-day limit)
usagewebfetch — web fetch cost in USD (31-day limit)
usageupstreamweb_fetch — provider-side web fetch cost in USD (31-day limit)
Performance metrics (how fast):
avglatency, p50latency, p90latency, p99latency — response latency in milliseconds
avgthroughput, p50throughput, p90throughput, p99throughput — tokens per second
Efficiency metrics (how well):
cachehitrate — ratio of cached tokens to prompt tokens (0–1)
guardrailinvokedrate — ratio of requests that triggered guardrails
responsecachedrate — ratio of responses served from cache
Understanding Dimensions
Each dimension has:
| Field |
Meaning |
name |
Identifier to use in query requests |
display_label |
Human-readable label |
Dimensions are what you break down by — "show me spend by model" means dimensions: ["model"].
You can combine up to 2 dimensions in a single query (e.g., ["model", "provider"]).
Label Resolution
Some dimensions have their raw IDs automatically resolved to human-readable labels in query results. Data rows contain the resolved display names directly:
| Dimension |
Resolved to |
apikeyid |
Key name/label |
app |
App title or origin URL |
user |
User name or email address |
workspace |
Workspace name |
All other dimensions (e.g., model, provider, country) are returned as-is without resolution.
Rows with an empty user value represent traffic not attributed to a specific org member (e.g., API keys created at the org level).
Dimension Categories
Available with all time ranges:
model — the OpenRouter model ID (permaslug)
variant — model variant (e.g., standard, extended)
apikeyid — which API key made the request
user — the creator user ID (for org-level queries)
workspace — workspace ID
app — application ID
Limited to 31-day time ranges:
generation_id — unique ID for each generation (use to drill down to individual requests, then inspect via the openrouter-generations skill)
provider — upstream provider name
origin — request origin/source
country — request country
finish_reason — why the generation ended (stop, length, etc.)
external_user — custom user ID passed by the caller
contextlengthbucket — bucketed context length (1K, 10K, 100K, etc.)
Classifier Dimensions
Beyond the standard dimensions above, you can group by classifier dimensions — dynamic labels produced by a user-created classifier (e.g., topic, sentiment, category).
- Use the
classifier_dimensions request field to group by classifier-produced values
- Use the
classifier_filters request field to filter on classifier values
- The classifier must belong to your account (validated server-side)
- Classifier dimensions/filters limit the query time range to 31 days
- See the
openrouter-analytics-query skill for the full request shape
Mapping Questions to Classifier Queries
| Question pattern |
Request fields |
Notes |
| "Spend by topic" |
classifierdimensions: { classifierid, dimensionnames: ["topic"] } + metrics: ["totalusage"] |
Single dimension → column aliased to topic |
| "Only billing-related requests" |
classifierfilters: { classifierid, filters: [{ field: "category", operator: "eq", value: "billing" }] } |
Filters support eq, neq, in, not_in only |
| "Sentiment breakdown including unclassified" |
classifierdimensions: { classifierid, dimensionnames: ["sentiment"], includenulls: true } |
Includes rows without classification |
Understanding Operators
Filter operators for the filters array in query requests:
| Operator |
Value Type |
Meaning |
eq |
scalar |
Equals |
neq |
scalar |
Not equals |
gt |
scalar |
Greater than |
gte |
scalar |
Greater than or equal |
lt |
scalar |
Less than |
lte |
scalar |
Less than or equal |
in |
array |
In list |
not_in |
array |
Not in list |
Understanding Granularities
Time bucketing for time-series queries:
| Granularity |
Use when |
minute |
Last few hours, real-time monitoring |
hour |
Last 1–3 days |
day |
Last week to 3 months |
week |
Last 3–12 months |
month |
Year-scale trends |
When no granularity is set, the query returns aggregate totals without time bucketing.
Mapping Questions to Queries
Use this guide to translate natural-language questions into the right metric/dimension/filter combination:
| Question pattern |
Metrics |
Dimensions |
Notes |
| "How much did I spend?" |
total_usage |
— |
Add granularity for trends |
| "Which models cost the most?" |
total_usage |
model |
Order by total_usage desc |
| "How many requests?" |
request_count |
— |
Add model or apikeyid for breakdown |
| "How many tokens?" |
tokens_total |
— |
Use tokensprompt / tokenscompletion for split |
| "Which provider is fastest?" |
avglatency, p90latency |
provider |
31-day limit |
| "What's my cache hit rate?" |
cachehitrate |
model |
Rate metric — shows per-model caching |
| "Which API key uses the most?" |
requestcount, totalusage |
apikeyid |
— |
| "Usage over time" |
requestcount or totalusage |
— |
Set granularity: "day" |
| "Latency trends" |
p90_latency |
— |
Set granularity: "hour", 31d limit |
| "Usage by country" |
request_count |
country |
31-day limit |
| "How can I save money?" |
totalusage, cachehitrate, tokenstotal |
model |
See cost optimization in openrouter-analytics skill |
| "Show me individual requests" |
totalusage, tokenstotal |
generation_id |
31-day limit. Use returned IDs with openrouter-generations skill for full metadata and content |
| "How much BYOK spend?" |
byok_usage |
model |
Up to 365 days |
| "BYOK vs credits split?" |
byokusage, creditsusage |
— |
Both up to 365 days |
| "BYOK platform fees?" |
byok_fees |
model |
31-day limit |
| "Non-BYOK inference spend?" |
openrouter_usage |
model |
31-day limit |
| "How many guardrail triggers?" |
guardrailinvokedcount, guardrailinvokedrate |
model |
31-day limit |
| "How many cached responses?" |
responsecachedcount, responsecachedrate |
model |
31-day limit |
| "Where does my spend go?" |
usageupstream, usagecache, usage_data |
— |
Full cost breakdown (up to 365 days) |
| "Web search costs?" |
usageweb, usageupstream_web |
model |
Up to 365 days |
| "File processing costs?" |
usagefile, usageupstream_file |
model |
31-day limit |
| "Web fetch costs?" |
usagewebfetch, usageupstreamweb_fetch |
model |
31-day limit |
Filter Value Reference
Several dimensions are label-resolved in query results — the response shows human-readable names, but filters must use the underlying ID. Here's where to find each:
| Dimension |
Filter value |
Where to find it |
apikeyid |
Numeric ID or 64-char SHA-256 hash |
Numeric ID: generation metadata (apikeyid field). Hash: GET /api/v1/keys (key_hash field). Hashes are auto-resolved server-side. If a hash can't be resolved, a sentinel value returns zero rows (no error). |
user |
Clerk user ID (e.g. user_abc123) |
User settings or org member list — not the display name/email shown in results. |
workspace |
Workspace UUID |
Workspace settings page or GET /api/v1/workspaces — not the workspace name shown in results. |
app |
Numeric app ID |
Generation metadata (app_id field) or app settings — not the app title shown in results. |
model |
Permaslug (e.g. openai/gpt-4o) |
Model page URL or GET /api/v1/models — not the display name. |
Other dimensions (provider, origin, country, finishreason, externaluser, etc.) are not enriched — filter values match what's returned in results.
Constraints
- Maximum 2 dimensions per query
- Maximum 20 filters per query
- Maximum 10 classifier dimensions per query
- Maximum 10 classifier filters per query
- Maximum 10,000 rows returned per query (default 1,000)
group_limit (1–10,000): controls max rows per dimension combination. Auto-computed on time-series queries with dimensions to guarantee full time-window coverage. Set explicitly to cap per-group rows (e.g., top N per model per day).
- Most volume/cost metrics: up to 365 days with daily granularity
- Latency/throughput metrics and per-generation dimensions: up to 31 days
- Classifier dimensions/filters: always limited to 31 days
- Minute granularity: only available when the time window is ≤ 3 hours
- Rate-limited to 64 requests per minute