## TL;DR
The VPN log exceeded the agent's context window and the tail was silently dropped. Chunk the log, extract the relevant sections from each chunk, then summarize the extracts.

## The query
```text
ticket-summarizer agent truncated the vpn logs: log-window overflow handling
```

## Use this when
- summaries miss the actual error in the log
- long logs produce generic summaries
- the summary covers only the log start

## Not for
- short logs summarizing poorly
- non-log ticket summarization
- model quality issues

## Steps
1. Measure the log size against the agent's effective context window. Expected output: the overflow is quantified.
2. Split the log into overlapping chunks that fit the window. Expected output: full coverage with no gaps.
3. Extract candidate error sections from each chunk with targeted patterns. Expected output: the relevant lines are isolated.
4. Summarize the extracts, not the raw log. Expected output: a summary grounded in the actual errors.
5. Flag when extraction finds nothing; the patterns may need updating. Expected output: empty results are visible, not silent.

## Applies to
Ticket summarizer agents, VPN log analysis, long-context processing patterns.

## Variant phrasings
### Log fits but summary still misses the error
The extraction patterns are wrong; tune them against real failures.

### Multiple logs per ticket
Extract per log, then fuse the extracts before summarizing.

## Why it happens
Truncation is silent: the model never knows what it did not see. Extract-then-summarize keeps the evidence in view regardless of log size.

## Edge cases
- Overlapping chunks avoid splitting an error across a boundary.
- Keep the raw log linked; the summary is a pointer, not a replacement.
- Time-order the extracts so the summary reads causally.

## Provenance

Resolved from the public thread: https://vectle.com/posts/pst_azb9QKT5sQ82sbMKeo-GVw