The whole hunk
from line 31, old and new numbered
/
lines
from line 31
3131
3232 - `"1m"`
3333
34- `claude_tag_categories: optional array of "dm" or "engaged" or "monitoring" or 2 more`
35
36 Filter to Claude Tag (Claude in Slack) usage in specific spend categories. Usage with no category never matches. `dm` usage is reported under the user's product rather than `claude-tag`, so combining this filter with `products[]=claude-tag` excludes it. Use `group_by[]=claude_tag_category` to break out per-category values.
37
38 maxItems: 100
39
40 - `"dm"`
41
42 - `"engaged"`
43
44 - `"monitoring"`
45
46 - `"proactive"`
47
48 - `"scheduled"`
49
50- `claude_tag_user_ids: optional array of string`
51
52 Filter to Claude Tag (Claude in Slack) usage attributed to specific Slack users, by Slack user ID (for example `U0123ABCDEF`), not claude.ai user ID. Usage that is not Claude Tag, and Claude Tag usage not attributed to a single user, never matches. Use `group_by[]=claude_tag_user_id` to break out per-user values.
53
54 maxItems: 100
55
3456- `context_windows: optional array of "0-200k" or "200k-1M"`
3557
3658 Filter to specific context-window pricing tiers. Use `group_by[]=context_window` to break out per-tier values.
from line 69
4769
4870 format: date-time
4971
50- `group_by: optional array of "context_window" or "inference_geo" or "model" or 4 more`
72- `group_by: optional array of "claude_tag_category" or "claude_tag_user_id" or "context_window" or 6 more`
5173
5274 Dimensions to break each time bucket out by. Defaults to no grouping (one total per bucket). Each bucket reports at most its top 100 groups; a group beyond that cap has no row in that bucket (there is no remainder row), so grouped buckets are not exhaustive when a dimension has more than 100 distinct values.
5375
5476 maxItems: 100
5577
78 - `"claude_tag_category"`
79
80 - `"claude_tag_user_id"`
81
5682 - `"context_window"`
5783
5884 - `"inference_geo"`
from line 203
177203
178204 The number of input tokens read from the cache.
179205
206 - `claude_tag_category: "dm" or "engaged" or "monitoring" or 2 more or null`
207
208 Claude Tag (Claude in Slack) spend category: `engaged` (a person addressed Claude in a channel or thread), `proactive` (Claude responded without being addressed), `scheduled` (a scheduled routine ran), `monitoring` (Claude watching a channel it was asked to monitor), or `dm` (direct messages with Claude). Populated only when `claude_tag_category` is in `group_by[]`; null for usage that is not Claude Tag. Direct-message usage is billed to the individual user and is reported under that user's product, not under `claude-tag`. New categories may be added over time.
209
210 - `"dm"`
211
212 - `"engaged"`
213
214 - `"monitoring"`
215
216 - `"proactive"`
217
218 - `"scheduled"`
219
220 - `claude_tag_user_id: string or null`
221
222 Slack user ID (for example `U0123ABCDEF`) of the member the Claude Tag (Claude in Slack) usage is attributed to, not a claude.ai user ID. Populated only when `claude_tag_user_id` is in `group_by[]`; null for usage that is not Claude Tag and for Claude Tag usage that is not attributed to a single user (for example `monitoring`, and `proactive` usage Claude initiated), so per-user rows can sum to less than the Claude Tag total. Cannot be combined with `group_by[]=rbac_group_id` or the `rbac_group_ids[]` filter.
223
180224 - `context_window: "0-200k" or "200k-1M" or null`
181225
182226 Context-window pricing tier of the usage or cost. Null unless `context_window` is in `group_by[]`; it can also be null on grouped rows with no context-window tier, such as code execution.
from line 327
283327 "ephemeral_5m_input_tokens": 500
284328 },
285329 "cache_read_input_tokens": 0,
330 "claude_tag_category": "dm",
331 "claude_tag_user_id": "U0123ABCDEF",
286332 "context_window": "0-200k",
287333 "inference_geo": "global",
288334 "model": "claude-opus-5",
from line 386
340386
341387 - `"1m"`
342388
389- `claude_tag_categories: optional array of "dm" or "engaged" or "monitoring" or 2 more`
390
391 Filter to Claude Tag (Claude in Slack) usage in specific spend categories. Usage with no category never matches. `dm` usage is reported under the user's product rather than `claude-tag`, so combining this filter with `products[]=claude-tag` excludes it. Use `group_by[]=claude_tag_category` to break out per-category values.
392
393 maxItems: 100
394
395 - `"dm"`
396
397 - `"engaged"`
398
399 - `"monitoring"`
400
401 - `"proactive"`
402
403 - `"scheduled"`
404
405- `claude_tag_user_ids: optional array of string`
406
407 Filter to Claude Tag (Claude in Slack) usage attributed to specific Slack users, by Slack user ID (for example `U0123ABCDEF`), not claude.ai user ID. Usage that is not Claude Tag, and Claude Tag usage not attributed to a single user, never matches. Use `group_by[]=claude_tag_user_id` to break out per-user values.
408
409 maxItems: 100
410
343411- `context_windows: optional array of "0-200k" or "200k-1M"`
344412
345413 Filter to specific context-window pricing tiers. Use `group_by[]=context_window` to break out per-tier values.
from line 430
362430
363431 default: false
364432
365- `group_by: optional array of "context_window" or "inference_geo" or "model" or 4 more`
433- `group_by: optional array of "claude_tag_category" or "claude_tag_user_id" or "context_window" or 6 more`
366434
367435 Break each actor's row out by the given dimensions. Accepts the same values as the bucketed `/usage_report` endpoint. `limit` bounds (actor × time bucket × dimension) rows — with dimensions or `bucket_width` present, one actor may span several rows.
368436
369437 maxItems: 100
370438
439 - `"claude_tag_category"`
440
441 - `"claude_tag_user_id"`
442
371443 - `"context_window"`
372444
373445 - `"inference_geo"`
from line 602
530602
531603 The number of input tokens read from the cache.
532604
605 - `claude_tag_category: "dm" or "engaged" or "monitoring" or 2 more or null`
606
607 Claude Tag (Claude in Slack) spend category: `engaged` (a person addressed Claude in a channel or thread), `proactive` (Claude responded without being addressed), `scheduled` (a scheduled routine ran), `monitoring` (Claude watching a channel it was asked to monitor), or `dm` (direct messages with Claude). Populated only when `claude_tag_category` is in `group_by[]`; null for usage that is not Claude Tag. Direct-message usage is billed to the individual user and is reported under that user's product, not under `claude-tag`. New categories may be added over time.
608
609 - `"dm"`
610
611 - `"engaged"`
612
613 - `"monitoring"`
614
615 - `"proactive"`
616
617 - `"scheduled"`
618
619 - `claude_tag_user_id: string or null`
620
621 Slack user ID (for example `U0123ABCDEF`) of the member the Claude Tag (Claude in Slack) usage is attributed to, not a claude.ai user ID. Populated only when `claude_tag_user_id` is in `group_by[]`; null for usage that is not Claude Tag and for Claude Tag usage that is not attributed to a single user (for example `monitoring`, and `proactive` usage Claude initiated), so per-user rows can sum to less than the Claude Tag total. Cannot be combined with `group_by[]=rbac_group_id` or the `rbac_group_ids[]` filter.
622
533623 - `context_window: "0-200k" or "200k-1M" or null`
534624
535625 Context-window pricing tier of the usage or cost. Null unless `context_window` is in `group_by[]`; it can also be null on grouped rows with no context-window tier, such as code execution.
from line 740
650740 "ephemeral_5m_input_tokens": 500
651741 },
652742 "cache_read_input_tokens": 3200000,
743 "claude_tag_category": "dm",
744 "claude_tag_user_id": "U0123ABCDEF",
653745 "context_window": "0-200k",
654746 "ending_at": "2019-12-27T18:11:19.117Z",
655747 "inference_geo": "global",
from line 803
711803
712804 The number of input tokens read from the cache.
713805
806 - `claude_tag_category: "dm" or "engaged" or "monitoring" or 2 more or null`
807
808 Claude Tag (Claude in Slack) spend category: `engaged` (a person addressed Claude in a channel or thread), `proactive` (Claude responded without being addressed), `scheduled` (a scheduled routine ran), `monitoring` (Claude watching a channel it was asked to monitor), or `dm` (direct messages with Claude). Populated only when `claude_tag_category` is in `group_by[]`; null for usage that is not Claude Tag. Direct-message usage is billed to the individual user and is reported under that user's product, not under `claude-tag`. New categories may be added over time.
809
810 - `"dm"`
811
812 - `"engaged"`
813
814 - `"monitoring"`
815
816 - `"proactive"`
817
818 - `"scheduled"`
819
820 - `claude_tag_user_id: string or null`
821
822 Slack user ID (for example `U0123ABCDEF`) of the member the Claude Tag (Claude in Slack) usage is attributed to, not a claude.ai user ID. Populated only when `claude_tag_user_id` is in `group_by[]`; null for usage that is not Claude Tag and for Claude Tag usage that is not attributed to a single user (for example `monitoring`, and `proactive` usage Claude initiated), so per-user rows can sum to less than the Claude Tag total. Cannot be combined with `group_by[]=rbac_group_id` or the `rbac_group_ids[]` filter.
823
714824 - `context_window: "0-200k" or "200k-1M" or null`
715825
716826 Context-window pricing tier of the usage or cost. Null unless `context_window` is in `group_by[]`; it can also be null on grouped rows with no context-window tier, such as code execution.
from line 952
842952 - `cache_read_input_tokens: number`
843953
844954 The number of input tokens read from the cache.
955
956 - `claude_tag_category: "dm" or "engaged" or "monitoring" or 2 more or null`
957
958 Claude Tag (Claude in Slack) spend category: `engaged` (a person addressed Claude in a channel or thread), `proactive` (Claude responded without being addressed), `scheduled` (a scheduled routine ran), `monitoring` (Claude watching a channel it was asked to monitor), or `dm` (direct messages with Claude). Populated only when `claude_tag_category` is in `group_by[]`; null for usage that is not Claude Tag. Direct-message usage is billed to the individual user and is reported under that user's product, not under `claude-tag`. New categories may be added over time.
959
960 - `"dm"`
961
962 - `"engaged"`
963
964 - `"monitoring"`
965
966 - `"proactive"`
967
968 - `"scheduled"`
969
970 - `claude_tag_user_id: string or null`
971
972 Slack user ID (for example `U0123ABCDEF`) of the member the Claude Tag (Claude in Slack) usage is attributed to, not a claude.ai user ID. Populated only when `claude_tag_user_id` is in `group_by[]`; null for usage that is not Claude Tag and for Claude Tag usage that is not attributed to a single user (for example `monitoring`, and `proactive` usage Claude initiated), so per-user rows can sum to less than the Claude Tag total. Cannot be combined with `group_by[]=rbac_group_id` or the `rbac_group_ids[]` filter.
845973
846974 - `context_window: "0-200k" or "200k-1M" or null`
847975