Single-curve variant of f2b — production trace only, no replay overlay
and no uniform reference. Cleaner for boss-meeting/talk slides where the
extra context is noise. The combined three-curve figure is unchanged.
scripts/plot_session_skew_cdf.py: split into plot_combined +
plot_production_solo helpers; one run emits both PNGs.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Pulls 456 (rank%, cum%) sample points from the raw production trace at
dash0:/home/admin/cpfs/wjh/ali-trace/trace-glm5.1-formatted/051315-051317.jsonl,
cached locally so the figure is reproducible without ssh access. Sampled
anchors match the precomputed summary exactly:
top 1% = 46.5%, top 5% = 66.5%, top 10% = 74.6%
plus newly readable points:
top 25% = 87.5%, top 50% = 96.0%
Workload characterization is now consistent with the production
distribution rather than the small replay subset. Replay window CDF kept
as an overlay to show the same hockey-stick shape on the data §5 actually
uses.
- analysis/characterization/data/production_session_skew_cdf.json: cached
sample points (29 KB), so the figure rebuilds locally
- scripts/plot_session_skew_cdf.py: now plots from the cache + replay raw
- MEETING.md / PAPER_OUTLINE.md: revert numbers to production trace,
add top-25%/50% data points
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The previous f2b_session_skew.png was a 3-bar chart (top 1/5/10%) computed
from the production trace summary (which is not present locally, only its
precomputed JSON). The new figure is a continuous CDF of cumulative
input-token mass vs session rank percentile, generated directly from the
replay trace traces/w600_r0.0015_st30.jsonl so any percentile is readable.
Headline numbers update accordingly:
replay trace (n=274 sessions): top 1% = 24.3%, top 5% = 61.9%, top 10% = 75.8%
production trace (n=1.3M): top 1% = 46.5%, top 5% = 66.5%, top 10% = 74.6%
Both show extreme skew well above the y=x uniform reference; the replay
trace is less extreme at top-1% because n=274 makes that bucket only
~3 sessions. We standardize §2/§3 narrative on the replay-trace numbers
so motivation matches §5 evaluation; production numbers kept as a side
note for context.
- scripts/plot_session_skew_cdf.py: reproducible figure generator
- MEETING.md / PAPER_OUTLINE.md: update narrative + caption
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
