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>
Batch compaction pauses a session for one large summarization once the
window fills. Micro-compaction spreads that cost out: after each completed
turn, `finalize_turn` folds the single oldest un-absorbed exchange
(assistant message plus its tool results) into a rolling summary, so the
work happens in small increments during post-turn idle time instead of one
long stall.
Mechanics:
- a cursor tracks the first message not yet absorbed, recovered from the
transcript's last summary marker when in-memory state is unavailable;
- protected head and tail windows are never touched, so the system prompt
and recent turns stay verbatim;
- the absorbed span is replaced by a marker carrying the usual
`_compressed_summary` metadata, so resume, handoff and `/compress`
treat it exactly like a batch summary;
- `archive_and_compact` keeps the session DB in step, otherwise the
append-only flush would leave the original rows active and a resume
would double-load both summary and originals;
- when the rolling summary itself passes a token threshold it is
defragged: re-summarized in one shot and the cursor jumps to the tail;
- an exchange the summarizer can't handle is retried a bounded number of
times, then skipped, so one poison exchange can't stall every turn.
Keep only the newest summary marker. The rolling summary is cumulative, so
each marker already contains everything the previous ones held; leaving them
stacked near-duplicate copies of the same text, each with its own heading and
end-marker scaffolding, and the transcript grew on every turn instead of
shrinking. Measured over six turns on a 12-exchange conversation with tool
output: 4104 -> 4797 tokens before, 4104 -> 2572 after.
Off switch: `compression.micro_compact: false` (default on).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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