Tokens saved is the wrong headline for this feature. Micro-compaction is
not an efficiency optimisation — the same summarization work happens either
way. What it buys is (a) that work amortized across turns instead of one
stall, and (b) a window kept low enough that a session runs much further
before needing a hard compaction at all.
Neither shows up in "net tokens saved". A session can save nothing on paper
and still be a clear win on both counts.
So the telemetry now carries occupancy: tokens_after as a share of the
compaction threshold, plus the threshold and resolved window it was
computed from. That is the number that says whether a session has headroom
left. The report leads with it, and cross-references the batch
`compression_attempt` lines already in the log so it can show how often the
long pause actually fired — ideally never.
Occupancy is read from the cached threshold only. The public
`threshold_tokens` property resolves lazily and can issue a synchronous
/models probe (#32221); telemetry must never be the thing that blocks a
turn, so an unresolved window reports null. In practice a pass has already
resolved it via the tail calculation, so the field is populated. A test
pins the no-forcing behaviour directly against the emitter.
The report is pure ASCII: `scripts/check_subprocess_stdin.py` currently
dies on a cp1252 console before printing its results, and a diagnostic tool
that crashes on the platform it is diagnosing is worse than no tool.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The existing log line reports message counts, which is the least
informative number available here: absorbing one tool-heavy exchange can
drop hundreds of tokens while moving the count by one. There was no way to
answer "is this actually helping?" from a real session.
Emit one content-free JSON line per pass, in the same shape as the batch
compaction telemetry: before/after tokens, the delta, the size of the
absorbed exchange, the rolling summary size, duration, and running
per-session totals so a whole run can be read off the last line. No
transcript content rides along.
Add scripts/micro_compaction_report.py to aggregate those lines into
passes, outcome mix, net tokens saved, mean exchange size and durations,
with an optional per-session breakdown.
Measuring it immediately surfaced something worth documenting: the first
pass in a session normally *costs* tokens. The summary marker carries a
fixed ~400 tokens of scaffolding, paid on pass one against a single
absorbed exchange. From pass two the marker is replaced rather than added,
so the overhead is already paid and each exchange is close to pure saving.
Break-even is typically the second or third pass. Tests cover the
telemetry contract, the cumulative totals, and that first-pass/later-pass
shape so nobody reads a single turn and concludes it made things worse.
The estimator costs ~5 ms at 600 messages and ~20 ms at 1200, taken twice
per pass, post-turn — and only once an exchange is actually in hand, so
turns that no-op early pay nothing.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
`_find_one_exchange`'s docstring described an exchange as "(optional) user
message + assistant message + its tool results", but the walk skips past
user messages and starts at the assistant, so user turns are never absorbed
into the rolling summary.
The code is right and the docstring was wrong. Assistant output is largely
an account of what was done and survives summarising with little loss. The
user's messages are the intent everything else is derived from and cannot be
reconstructed from the work that followed — paraphrasing "use the existing
helper, don't add a new one" into a summary is how an agent ends up doing
the opposite six turns later. They are also cheap: a prompt is normally a
tiny fraction of what one tool result costs.
Correct the docstring, document the property (and its cost — a floor on how
small the middle can get, since user turns accumulate), and add a test so it
stays deliberate.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Covers what it does, the head/tail protection, the cursor and rolling
summary, defrag, how the session DB is kept in step, and the failure
paths. States the tradeoff up front: compression cost is amortized across
turns, at the price of older detail becoming summarized earlier in a
session than batch-only compaction would.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
