semianalysisai/cc-traces-weka-with-subagents-051826

CC Traces — Weka, With Subagents, v5 only (May 18 2026)

A collection of 96 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).

With-subagents, v5-only variant. Companion to cc-traces-weka-no-subagents-051826, which is the same 96 traces with all WekaSubagentEntry blocks stripped.

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

Use the no-subagents sibling when you want a single linear main-agent stream per trace and don't care about the parent / child fan-out.

Same filters as the sibling:

1. 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.
2. ≥ 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.

• Traces: 96
• Top-level entries: 22,184 (21,566 main turns + 618 subagent groups)
• Sub-agent inner requests: 16,200
• Total individual model requests: 37,766
• Models: claude-opus-4-7, claude-haiku-4-5-20251001, claude-opus-4-6, claude-sonnet-4-6
• 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 = 37,766 requests):

	p50	p75	p90	p95	p99	mean
ISL (tokens)	100,902	229,982	443,856	580,438	803,019	172,848
OSL (tokens)	224	478	1,150	1,907	5,461	530
Top entries/trace	115	—	—	678	1,141	231

Plots

Main-agent stream

Histograms across all 21,566 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 618 sub-agent groups (and their 16,200 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:

1. Sub-agent groups per trace — distribution of how many distinct sub-agent invocations each session spawns
2. Inner requests per group — depth of each sub-agent's tool-use loop
3. Group wall-clock duration — first→last inner span (seconds)
4. Group total tokens — Σ(in + out) across each group's inner requests
5. 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)
6. Intra-group cache hit rate — for each non-first inner request, fraction of hash_ids already 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	36,637
claude-haiku-4-5-20251001	702
claude-opus-4-6	343
claude-sonnet-4-6	84

Source

Same proxy → weka pipeline as the no-subagents sibling, just without the post-step that strips WekaSubagentEntry blocks.

1. utils/sample_proxy_traces.py --min-trace-version 5 --min-main-turns 20 --privacy-mode anon
2. utils/proxy_to_weka.py (subagent grouping per the dashboard's algorithm)
3. Concatenate the resulting weka JSONs into traces.jsonl — one trace per line.

The same-96-trace contract with the no-subagents sibling makes the two variants safe to A/B compare for any benchmark that cares about sub-agent fan-out's impact on cache-hit-rate or throughput.