paper_ai_Qos / analysis /summary_tables.md
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# Analysis summary (generated by scripts/analyze.py from evidence/)
## Timeout (80408) events
- total: **33**, all `reasonForCode: 80408`
- per day: 2026-09-07: 1, 2026-09-08: 4, 2026-09-09: 28
- densest 75-minute block: **20 events** (the resume-button loop)
## Quota/account events
- log lines: 50 → clustered (≤2 s apart): **18 events**
- distinct codes seen: -32603, 100400, 112
- distinct message wordings: 3
- `Access denied, please make sure your account is in good standing. For details, see: https://help.ali`
- `Allocated quota exceeded, please increase your quota limit. For details, see: https://www.alibabaclo`
- `Your token-plan 1-week quota has been exhausted. The quota will reset at 09-08 01:45:00 UTC.`
## chat_finish census
- 245 lines total: 225 `success:200`, 20 error payloads,
**zero attributable to the 33 timeout events** (no chat_finish line exists for them)
## Three largest sessions (transcript entries)
| session | entries | jsonl bytes |
|---|---|---|
| `sess-11` | 626 | 379526 |
| `sess-14` | 280 | 154497 |
| `sess-15` | 208 | 253155 |
## Task lifecycle (`quest.log` — the client's `task` = one conversation)
- 1252 log lines → **524 events** after ≤2 s de-dup (102 events replicated into ≥2 IDE windows, 626 `.skipNonQuestTask` twins dropped)
- statuses: ActionRequired 33, Completed 208, Error 18, Running 258, Stopped 7
- `Running` spans: 257 closed, 1 still open at the extract horizon; median 126 s, 90th percentile 679 s, max 4131 s
- **max simultaneous `Running` tasks: 2** (never 3+; 10 overlapping pairs of conversations), `error.code.task.running.quota.exceeded` fired 0 times, so that ceiling is only bounded ≥2
- `ActionRequired` (banner up, nothing generating): 33 events, 1:1 with the 33 timeout resume lines (largest offset 234 ms)
- conversation-level split of those timeouts, which supersedes the window-level correlation in report §4.2: `sess-03` 23, `sess-04` 4, `sess-11` 5, `sess-16` 1
- watchdog measured off the state machine: **61 s of silence** before the banner (16 of 33 banners at exactly that span; the rest are mid-run stalls after some output), and 155 of 194 *successful* runs ran longer than that span — so it caps inactivity, not total duration
## Per-interaction phase timing (`[ACPProgressStateMachine]`)
- 885 transitions over 9 conversations: 252 prompts sent, 245 answered with a first streamed chunk, 4 rejected before any chunk, 208 generations finished
- **wait for the first chunk** (`prompting` → `streaming`, the UI's 'Thinking…'): median **9.6 s**, 90th percentile 49 s, max 132 s, min 1.2 s
- generation time (`streaming` → `chat_finish:success`): median 105 s, 90th percentile 477 s, max 2310 s; 149 of 208 exceed the 61 s watchdog span
- what suspended a turn: permission_request 37, resume_tool_call 33 (`resume_tool_call` = the 80408 banner, a third stream confirming 33)
- operator hold: banners 32 resumed, median 30 s, total 90.5 min; permission dialogs 37, median 88 s, total 122.0 min
## Request lifecycle (frozen log snapshot; scripts/latency_from_logs.py)
- 308 requests across 10 sessions — S 211, T 71 (timeout 33 / dialog 38), F/U 26
- first-attempt usable (0-retry S) **179/211 (84%)**
- first-chunk wait median 11.3s (n=300); clean-success turn total median 120.0s (n=179); send-to-stall median 305.4s (n=71)
## Incident 2 — collection round of 2026-09-10 (`evidence/incident_20260910/`)
- 62 request episodes (55 distinct submitted prompts) in 3 conversations on the observation day: 53 completed, 5 timeout parks, 2 dialog parks, 2 failed/cancelled
- the five timeouts all sit in one conversation at **490,789 tokens**; the largest context that still completed that day is **452,447 tokens** — a 452,447-versus-490,789 separation on the day (round 1 pooled data does NOT separate cleanly; see report §4.2)
- send-to-stall spanned 125s to 4861s (the upper value is a banner left parked for 81 minutes)
- paired experiment: the same conversation stalled five times at 494,193 tokens, then after the client's context-compaction control reported 117,153 tokens (`Compression API call completed for session compact`) a request carrying 85,115 tokens completed in 10.1 s — report §9
- three negative results from this round: tab visibility (a hidden conversation completed in 2.58 s), server-side cache residency across a 27.7-minute idle gap (17.11 s versus 17.58 s at the same size), and inflating an agent's context by asking it to read files (one such turn added 851 tokens)
Content hash `sha256:2218b3e37e6e4307ff5b1451017d19d5f5c86ac217c803d160d0111a34f5ee77` - generated 2026-09-11 10:17:52 - rerun: `python3 scripts/analyze.py`