Allow setting context compaction threshold

### Describe the feature or problem you'd like to solve

Allow setting context compaction threshold which currently fixed

### Proposed solution

# Feature Request: Configurable Auto-Compaction Threshold

## Summary

Allow users to configure the context window percentage at which auto-compaction triggers, via `config.json` or a CLI flag. The current fixed threshold of 95% is too late — research shows LLM quality degrades well before that point.

## Motivation

Recent peer-reviewed research demonstrates that LLM performance degrades significantly as context window utilization increases, and that compacting earlier (around 50–60%) preserves substantially better output quality:

### 1. Positional Biases Shift Beyond 50% Context Fill

**Paper:** "Positional Biases Shift as Inputs Approach Context Window Limits" — Veseli et al., COLM 2025 ([arXiv:2508.07479](https://arxiv.org/abs/2508.07479))

**Key findings:**
- The "Lost in the Middle" (LiM) effect is strongest when inputs occupy **up to 50%** of a model's context window
- **Beyond 50%**, primacy bias weakens — the model progressively loses the ability to reference information from earlier in the context
- At high utilization, only recency bias remains, meaning the model effectively ignores earlier conversation history
- This shift is consistent across models and is measured **relative to each model's context window size**

### 2. The "Lost in the Middle" Problem

**Paper:** "Lost in the Middle: How Language Models Use Long Contexts" — Liu et al., TACL 2023 ([arXiv:2307.03172](https://arxiv.org/abs/2307.03172))

**Key findings:**
- Performance degrades significantly when relevant information is positioned in the middle of long contexts
- Even models explicitly designed for long contexts exhibit this degradation
- Performance is often highest when relevant information occurs at the beginning or end of the input

### Why 60% Is Better Than 95%

| Aspect | Compact at 60% | Compact at 95% |
|--------|----------------|----------------|
| Primacy bias | Still intact — model can reference early context | Weakened — model struggles with early context |
| Lost-in-the-middle effect | At its peak but manageable | Replaced by pure recency bias |
| Information from early turns | Preserved in high-quality summary while model can still "see" it well | Summarized after model was already degraded for ~35% of context |
| Quality of compaction summary | Higher — model has full positional access during summarization | Lower — model may miss important early details during summarization |
| User experience | Proactive — avoids degradation before it's noticed | Reactive — user may already experience worse responses |

## Proposed Implementation

### Option A: Config setting (preferred)
via ~/.copilot/config.json

```json
{
"compactionThreshold": 0.60
}
```

### Option B: CLI flag

```bash
copilot --compaction-threshold 0.60
```

### Option C: Slash command

```
/compact --auto-at 60
```

### Defaults

- **Current default:** 95% (preserve for backward compatibility)
- **Recommended default:** 60% (based on research)
- **Valid range:** 30–95%

## Expected Behavior

1. When context usage reaches the configured threshold, auto-compaction triggers (same as current 95% behavior)
2. The `/context` command should display the configured threshold alongside current usage
3. The setting persists in `config.json` across sessions

## Additional Context

Users working on complex, multi-file coding tasks (e.g., large refactors, architecture changes) are most impacted by late compaction. By the time context reaches 95%, earlier instructions, file contents, and plan details may already be effectively "invisible" to the model due to positional bias shifts. Compacting at 60% ensures the summary is generated while the model still has strong access to all parts of the conversation.

### Example prompts or workflows

_No response_

### Additional context

_No response_