Datasets:
id stringlengths 36 36 | models listlengths 1 3 | block_size int64 64 64 | hash_id_scope stringclasses 1
value | requests listlengths 20 2k |
|---|---|---|---|---|
009dfc4e83422be8d3daa41cfda78036b2cd | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":418,"out":20,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.303,"t(...TRUNCATED) |
00ac905ea15e7901d7e2e5e41eb2e8f09684 | [
"claude-haiku-4-5-20251001",
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":54831,"out":185,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10,11,12,13(...TRUNCATED) |
00f4cc77fc2de6713521dad5f0066c6a051a | [
"claude-haiku-4-5-20251001",
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-haiku-4-5-20251001","in":620,"out":15,"hash_ids":[0,1,2,3,4,5,6,7,8,9],"ap(...TRUNCATED) |
0605169f853339123b00578c5fe0204b4a79 | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":419,"out":22,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.243999(...TRUNCATED) |
0af3e551f4b5f408f6f5fd060efc0fda2a02 | [
"claude-haiku-4-5-20251001",
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":55083,"out":205,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10,11,12,13(...TRUNCATED) |
0b1825a4864ed8e4f4a14c43d34b634462ae | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":402,"out":24,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.998,"t(...TRUNCATED) |
0c80f810ee39c9ff7fd1da753062021f61ca | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":50028,"out":295,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10,11,12,13(...TRUNCATED) |
0d16b460e49f5f0a3188ec9cc37bb38bf567 | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":587,"out":25,"hash_ids":[0,1,2,3,4,5,6,7,8,9],"api_time":3.(...TRUNCATED) |
0e3e0d05df4033ad3442ca6a9e1670a1430d | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":441,"out":31,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.321,"t(...TRUNCATED) |
0fbcd81b70613cb62405d69776f6c2932e8f | [
"claude-opus-4-7"
] | 64 | local | [{"t":0.0,"model":"claude-opus-4-7","in":443,"out":26,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.569,"t(...TRUNCATED) |
CC Traces — Weka, With Subagents, v5 only (May 20 2026)
A collection of 219 multi-turn agentic traces drawn from real production
traffic against the Claude Code CLI ≥ 2.1.139. Each trace captures the full
request/response sequence of a single agent session, including per-request
KV block hashes AND the original sub-agent fan-out structure (Task-tool
spawned sub-agents grouped into WekaSubagentEntry blocks).
Use this dataset when you want to:
- Simulate the full agentic-coding workload including parallel Task-tool sub-agent fan-out
- Study sub-agent dispatch patterns, instance counts, durations
- Replay against an inference engine that should see the same concurrent- request structure a real Claude Code session generates
Filters:
- v5 only. Every replayable request in every included session has
trace_version = 5(the latest proxy schema, o200k_base tokenizer). Sessions containing any earlier-format request are excluded entirely. - ≥ 20 main-agent turns. Per-trace main-agent stream (the would-be no-subagents stream) must have at least 20 turns. Sub-agent fan-out is on top of that.
- CC ≥ 2.1.139. Every replayable request in every included session originated from a Claude Code CLI build at version 2.1.139 or newer.
- Non-conversational classifier calls excluded. Claude Code fires
several short auxiliary classifier calls per session ("SUGGESTION
MODE" next-input prediction, conversation-title generation, haiku
intent detection, the "Security Monitor" subagent). They share a
clean request shape —
max_tokens <= 64AND notools— and produced a heavy OSL 5-10 spike (~9k+ rows at exactly OSL=7) that pollutes the published output-length distribution. They are dropped at source by shape, with an additional label/body fallback for the Security Monitor subagent specifically.
- Traces: 219
- Top-level entries: 39,726 (37,732 main turns + 1,994 subagent groups)
- Sub-agent inner requests: 40,367
- Total individual model requests: 78,099
- Models:
claude-opus-4-7(74,293 req),claude-opus-4-6(2,138 req),claude-haiku-4-5-20251001(1,163 req),claude-sonnet-4-6(505 req) - KV block size: 64 tokens
- Hash scope:
local— block hash IDs are only comparable within a single trace; they are not a global content-addressable identity.
Important: tokenizer caveat
The in field on each request and the hash_ids array are both
measured in the proxy's tokenizer (o200k_base, GPT-4o family).
Anthropic typically reports ~60 % of the o200k token count for the same
content. So the ISL numbers below are larger than what the Anthropic
API would have billed for the same prompt — but they're self-consistent
between in and hash_ids, which is what matters for KV-cache replay
simulation.
What's in each trace
Top-level trace fields:
| field | type | description |
|---|---|---|
id |
str | Trace identifier (the proxy session id) |
models |
list[str] | Models used by the trace |
block_size |
int | KV block size used to derive hash_ids (64) |
hash_id_scope |
str | local — hash IDs are per-trace, not global |
requests |
list[object] | Ordered list of per-request records OR WekaSubagentEntry groups |
Each entry in requests is one of two shapes:
Main-agent request (type: "n" or "s")
| field | type | description |
|---|---|---|
t |
float | Seconds since start of trace |
type |
str | n (non-streaming) or s (streaming) |
model |
str | Target model for this request |
in |
int | Effective prompt tokens covered by hash_ids (proxy tokenizer) |
out |
int | Output tokens (Anthropic-reported) |
hash_ids |
list[int] | Per-trace local block-hash IDs for the input, one per 64-token block |
api_time |
float | End-to-end server time for this call (seconds) |
think_time |
float? | Wall-clock gap from previous request's end (seconds) |
ttft |
float? | Time to first token (streaming requests only) |
Sub-agent group (type: "subagent")
| field | type | description |
|---|---|---|
t |
float | Start time (seconds since trace start) |
type |
str | Always "subagent" |
agent_id |
str | Stable per-trace sub-agent instance id (slug + suffix) |
subagent_type |
str | Sub-agent label ("Subagent" for Claude Code ≥ 2.1.139, else the original proxy label) |
duration_ms |
int | Wall-clock span first→last inner request |
total_tokens |
int | Sum of in + out across inner requests |
tool_use_count |
null | Not tracked in the proxy DB |
status |
str | Always "completed" |
requests |
list[object] | Inner main-shape entries (type n — sub-agents are non-streaming) |
models |
list[str] | Distinct models used inside this sub-agent run |
Sub-agent groups are emitted at the position of the first inner request
in the chronological stream. Their inner requests have absolute t
values (not relative to the group start), making sub-agent and main-
agent timelines directly interleavable for replay.
hash_ids make the dataset unusually useful for KV-cache work: the
contiguous common prefix between turn t and turn t − 1 exactly
measures the portion of the input that a local prefix cache would be
able to reuse. The same accounting applies to sub-agent inner requests
within their group, and to the dispatching parent request that
triggered them.
Summary statistics
Across all requests (main + sub-agent inner = 78,099 requests):
| p50 | p75 | p90 | p95 | p99 | mean | |
|---|---|---|---|---|---|---|
| ISL (tokens) | 109,729 | 214,992 | 394,994 | 535,364 | 799,788 | 164,194 |
| OSL (tokens) | 307 | 688 | 1,442 | 2,204 | 6,852 | 694 |
| Top entries/trace | 114 | 219 | 369 | 543 | 1,062 | 181 |
Plots
Main-agent stream
Histograms across all 37,732 main-agent turns (sub-agent groups skipped). Same view as the no-subagents sibling — the two datasets share an identical main-agent stream.
Sub-agent fan-out analysis
Histograms across all 1,994 sub-agent groups (and their 40,367 inner requests). Companion to the main-stream plots — answers questions about how often sub-agents are spawned, how deep their tool-loops go, how long they take, and how much intra-group prefix cache reuse exists.
Six panels:
- Sub-agent groups per trace — distribution of how many distinct sub-agent invocations each session spawns
- Inner requests per group — depth of each sub-agent's tool-use loop
- Group wall-clock duration — first→last inner span (seconds)
- Group total tokens —
Σ(in + out)across each group's inner requests - Inner-request ISL — per-call input length INSIDE sub-agent loops (smaller than main-agent turns because sub-agents work on focused sub-problems with trimmed context)
- Intra-group cache hit rate — for each non-first inner request, fraction of
hash_idsalready seen in earlier inners of the SAME group. Captures how much KV-cache reuse a local prefix cache would get out of a sub-agent's tool-use loop (typically high — sub-agents iterate on a stable prompt)
Model composition
| model | requests (main + subagent inner) |
|---|---|
claude-opus-4-7 |
74,293 |
claude-opus-4-6 |
2,138 |
claude-haiku-4-5-20251001 |
1,163 |
claude-sonnet-4-6 |
505 |
Source
Same proxy → weka pipeline as the
no-subagents sibling,
just without the post-step that strips WekaSubagentEntry blocks.
utils/sample_proxy_traces.py --min-trace-version 5 --min-main-turns 20 --require-cli-min 2.1.139 --privacy-mode anon(Non-conversational classifier-call exclusion —max_tokens <= 64- no
toolsarray — is hardcoded into the query so the 5-10-token OSL spike doesn't leak into the published corpus. A label/body fallback for the Security Monitor subagent is layered on top.)
- no
utils/proxy_to_weka.py(subagent grouping per the dashboard's algorithm)- Concatenate the resulting weka JSONs into
traces.jsonl— one trace per line.
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