context-compression

name	context-compression
description	Keep sessions productive by compressing completed work while preserving key decisions.

Context Compression — Long Session Management

Keep sessions productive by compressing completed work while preserving key decisions.

Overview

Long sessions (30+ turns) cause context degradation — the AI loses track of earlier work, repeats itself, or forgets decisions. Context compression proactively summarizes completed phases so the context window stays focused on active work.

Token Impact: Recovers 5,000-15,000 tokens in long sessions by replacing verbose tool outputs with semantic summaries.

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When to Compress

Signal	Action
Session has 20+ turns	Consider proactive compression
Agent repeats earlier suggestions	Context is saturated — compress now
User says "we already discussed this"	Compress immediately
Switching to a new phase of work	Compress the completed phase
Large tool output (500+ lines)	Micro-compact the output

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Compression Levels

Level 1: Micro-Compact (Tool Output)

Compress individual tool outputs while retaining semantic content:

❌ Before (raw grep output — 200 lines, ~4,000 tokens):
src/auth/jwt.ts:15: import { verify } from 'jsonwebtoken'
src/auth/jwt.ts:23: export function validateToken(token: string) {
src/auth/jwt.ts:24:   try {
src/auth/jwt.ts:25:     const decoded = verify(token, SECRET)
... (195 more lines)

✅ After (micro-compact — 5 lines, ~100 tokens):
Grep results for "jwt": Found 8 files, 42 matches.
Key files: src/auth/jwt.ts (main JWT logic), src/middleware/auth.ts (middleware),
src/api/login.ts (token creation). Token validation at jwt.ts:23-40.
Error handling at jwt.ts:42-55. Secret loaded from env at jwt.ts:8.

Level 2: Phase Summary

Replace a completed work phase with a summary:

❌ Before (full research transcript — ~3,000 tokens):
[turn 1] Read package.json...
[turn 2] Read src/index.ts...
[turn 3] Grep for "auth"...
[turn 4] Found 8 files related to auth...
[turn 5] Read src/auth/jwt.ts...
... (10 more turns of exploration)

✅ After (phase summary — ~200 tokens):
## Research Phase Complete
- Project: Next.js 15 app with JWT auth
- Auth files: 8 files in src/auth/, src/middleware/, src/api/
- Token flow: login → create JWT → store in httpOnly cookie → validate in middleware
- Bug location: src/auth/jwt.ts:45 — expiry check uses `<` instead of `<=`
- Decision: Fix the comparison operator, add edge case test

Level 3: Session Checkpoint

Full session summary for long-running work:

## Session Checkpoint (Turn 35)

### Completed
- [x] Researched auth system (8 files, JWT flow mapped)
- [x] Fixed token expiry bug in jwt.ts:45
- [x] Added edge case test in jwt.test.ts
- [x] Verified: all 42 tests passing

### In Progress
- [ ] Update API documentation
- [ ] Review related middleware

### Key Decisions
1. Keep httpOnly cookies (not localStorage) for token storage
2. Use `<=` for expiry check to include exact-moment expiry
3. Add 5-minute grace period for clock skew

### Files Modified
- src/auth/jwt.ts (line 45: comparison fix)
- tests/auth/jwt.test.ts (added 3 edge case tests)

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Compression Protocol

Step 1: Identify Completed Phases

What work is DONE and won't be revisited?
→ Research findings already synthesized
→ Implementation already verified
→ Decisions already made and applied

Step 2: Extract Key Information

From the completed phase, preserve:
✅ Decisions made and WHY
✅ File paths and line numbers of changes
✅ Key findings that inform ongoing work
✅ Error messages or test results (summarized)

Discard:
❌ Step-by-step tool invocation details
❌ Full file contents that were read
❌ Exploratory dead-ends that didn't lead anywhere
❌ Verbose error stack traces (keep the message only)

Step 3: Write Summary

Use the Phase Summary format above.
Keep to 100-300 tokens per completed phase.
Include enough detail to resume work without re-reading.

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Best Practices

1. Compress phases, not facts — Individual decisions should stay, full transcripts should go
2. Preserve "why" over "what" — Why a decision was made matters more than the exact commands run
3. Never auto-compress — Always tell the user "I'm summarizing the completed research phase to keep context focused"
4. Keep file references — Always preserve file paths and line numbers in summaries
5. Checkpoint on phase transitions — Natural compression point when switching from research to implementation

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