Impossible-Guitar Chats

Token audit · 6 sessions · 2026-08-10 to 2026-08-12

Revision 2 · revision 1 overstated most headline numbers

What revision 1 got wrong

confirmed unchanged 6 sessions, 166 idle turns, 42 tool errors, 30 duplicate reads, peak context 997,206.

Input processed is not input paid

Processed and paid differ by a factor of 8.5 here. Any figure quoted as raw processed tokens overstates cost by roughly that much, which is what revision 1 did.

The six sessions

Active hours count only gaps of 5 minutes or less between records, so 13.9 is a floor and 81.6 is an unrelated ceiling.

Finding 1: 13.9 model requests per user prompt

171 user prompts produced 2,372 model requests. Session 81d2b7bf ran 1,050 requests on its own. This is the clearest signature in the data, and it describes the failure better than any token figure: the agent stayed inside local correction loops rather than stopping to consolidate state, freeze a regression fixture, and move to the next falsifiable hypothesis.

152 of those runs are compliance tooling rather than defect work. The fretting cluster (refret_capo 30, test_refret 18, verify_refret 16, refret_gpif 13) is 77 runs of tweak-and-recheck on one subsystem. gp_swap appears in 273 bash calls, 217 of them in 81d2b7bf. Only 11 non-sleep commands in the entire cluster are exact duplicates, so this is the same tool re-run with shifting arguments, which is the expensive shape.

Finding 2: 166 idle turns, 8,564,895 base-equivalent tokens

Every one was a turn whose only action was sleep N; echo waited. That is 7.9% of the cluster's input spend for no analytical work. The /loop was authorized, so no policy was broken. The orchestration failure stands on its own: 42 ScheduleWakeup calls and 166 empty round trips is an agent waiting in a loop instead of ending a turn.

Finding 3: peak context 997,206, and 30.6% of input spend above a 300K working set

At a 200K threshold the excess is 469,237,421 processed, 50.9% of everything read. 300K is a threshold I chose. Nothing in the data measures the minimum context each decision actually required. Accumulated context held real state: the checkpoint, prior findings, regression history. This figure counts excess processing above an assumed bounded working set, and it makes no claim that the money was provably wasted. 81d2b7bf at 997,206 tokens across 30 hours is past arguing about, since 40% of its input spend sat above the threshold.

Finding 4: batching, 318 of 2,394 calls

318 calls went out in messages carrying two or more tool calls. A conservative eligibility test examined adjacent single-call turns where both calls were read-only and the second call's input shared no 8-character token with the first call's result, so no dependency could be proven. Only 23 calls failed that test. Measured over calls provably eligible, batching runs 93.3%. The remaining 2,053 single-call turns are mostly python3 and heredoc bash the test declines to classify, so they are neither proven batchable nor proven serial. The honest statement is that batching is 13.3% of all calls, the provable misses are few, and the 0% accusation was an artifact of the meter.

Outcome

Fixes, ranked

1. Carry a compact state artifact across the context boundary. A fresh session on its own pays less per turn and rediscovers the same facts. The unit is fresh execution context plus a deliberately compressed project state: checkpoint hash, known failure list, regression fixtures, current pipeline order, and the hard gates. Without that package, clearing is a cost saving and an information loss at the same time.
2. Cap the working context near 300K and reset with that artifact. Worth about 30.6% of input spend on this cluster, and the fix for the 997K session.
3. Freeze a regression fixture before the next fix. 77 fretting-subsystem runs and 51 validator runs is the loop to break. One failing fixture, one hypothesis, one run.
4. End the turn instead of sleeping. 166 empty turns and 42 wakeups, at 7.9% of input spend.
5. Trust the repaired meter. analyze.py now dedupes usage and merges tool blocks per message. The batching gate's July figures survive remeasurement, so keep the gate. Credit the improvement to 13.3% that the broken meter was hiding, and read the batching rate off the fixed script from here on.

Provenance

• Source: usage records in ~/.claude/projects/-Users-drwu/*.jsonl, read directly
• Cache multipliers applied: cache read 0.1x, cache creation 1.25x at 5 minutes and 2.0x at 1 hour, uncached input 1.0x
• Idle-turn base-equivalent applies the 1-hour creation multiplier to 99,389 cache-creation tokens, a rounding difference under 1% of that line
• Idle-turn cost and above-threshold excess overlap and must not be added. Most idle turns in 81d2b7bf ran at high context, so their cost sits largely inside that session's 21,554,112 excess figure
• 81d2b7bf and 758ba450 were both live during the audit, so their counts are floors