Claude Code Context Management Best Practices: Memory, Skills, and Agents

Mar 12, 2026

I was in the middle of a complex refactoring task when Claude suddenly lost all context. It forgot the decisions we’d made, the file structure we’d established, and started suggesting changes that contradicted everything we’d done. Again.

I kept adding more to my memory file, thinking more context would help. It didn’t. The context drift got worse, token usage exploded, and I was stuck in an endless loop of re-explaining the same things.

What I Discovered

After diving into community discussions and experimenting, I realized my approach was fundamentally wrong. The problem wasn’t too little context - it was the wrong context.

“If context is a problem, adding more memory just kicks the can down the road. What you need is not more memory. You need a perfectly optimized context, with exactly and only the relevant information for a task.”

And there’s a hard limit I didn’t know about:

“Memory is maximum 200 lines. Everything after that is not read.”

So my 300-line memory file? The last 100 lines were invisible to Claude.

The Solution: Layered Context Management

Claude Code provides three mechanisms for context management, each with different trade-offs:

Layer	Purpose	Token Cost	When to Use
Memory	Current state, decisions	Low (200 line limit)	Dynamic session context
Skills	Task templates	Per-invocation	Repeated workflows
Agents	Parallel execution	High (full context each)	Independent tasks

Understanding when to use each is the key to effective context management.

Memory: The 200-Line Limit

Memory files are for dynamic, session-relevant context. They’re perfect for tracking:

Current sprint goals
Recent decisions
Known issues being investigated
Project-specific gotchas

But they hit a hard limit at 200 lines. Here’s how I structure mine now:

# Current Sprint: Checkout Flow

## Active Work
- Stripe integration in progress (PR #234)
- Cart sync race condition fixed

## Recent Decisions
- 03/12: Use webhooks for payment status updates
- 03/11: Redis cache for cart persistence

## Known Issues
- Payment timeout on slow networks (investigating)

## Gotchas
- Stripe requires raw body for webhook signature verification
- Cart TTL must be longer than session timeout

Daily Logs: Preventing Bloat

The key insight from the community: split your memory into daily logs and a curated main file.

## Session Work
- Fixed race condition in cart sync
- Added error boundary to checkout component
- Discovered: useEffect cleanup needed for cart listener

## Next Session
- Continue payment timeout investigation
- Add retry logic to webhook handler
- Consider exponential backoff

This way, raw notes go into daily logs (which can be long), and only the essential, current context stays in the curated MEMORY.md.

Skills: Reusable Task Templates

Skills are perfect for repeated task patterns. Instead of re-explaining the same process every time, create a skill:

---
name: code-review
description: Review code for quality, security, and best practices
---

## Review Checklist
- [ ] Code is readable and well-named
- [ ] No hardcoded secrets or credentials
- [ ] Error handling is complete
- [ ] All tests pass
- [ ] No mutation (immutable patterns used)

## Process
1. Read the modified files
2. Check against checklist
3. Report CRITICAL, HIGH, MEDIUM issues
4. Suggest specific fixes

Now when I need a code review, I just invoke the skill. Claude gets exactly the context it needs for that specific task.

Agents: Parallel Full-Context Execution

Here’s where it gets powerful. The community insight:

“I have taken to breaking my asks into many smaller tasks and persisting them as actionable TODOs. Then every todo also specifies agents for the tasks within them. The advantage of agents is that they run in parallel at full context with the downside of course that they eat up more tokens.”

Agents run in parallel with full context. This means:

Each agent gets a fresh, full context window
Agents work independently without contaminating each other
The parent orchestrates and merges results

## Main Task: Build Checkout Flow

### Break into TODOs (spawn as agents)
1. [ ] Create checkout page component (agent 1)
2. [ ] Integrate Stripe SDK (agent 2)
3. [ ] Add payment status webhooks (agent 3)
4. [ ] Write checkout tests (agent 4)

### Parent Role (Orchestrator)
- Coordinate agent execution
- Handle dependencies between tasks
- Merge and validate results

The trade-off: Agents cost more tokens because each gets a full context. Use them for:

Independent tasks that don’t need to share state
Complex tasks that benefit from isolation
Parallel work streams

Don’t use agents for:

Trivial tasks (overhead isn’t worth it)
Tightly coupled tasks that need shared state
Sequential operations

Anti-Patterns to Avoid

I learned these the hard way:

Anti-Pattern	Problem	Solution
Bloated memory files	Exceeds 200-line limit, content ignored	Split into daily logs + curated MEMORY.md
Duplicating context	Wastes tokens, creates inconsistency	Choose one mechanism per piece of info
Using agents for trivial tasks	Token overhead without benefit	Use skills or direct commands instead
Not updating memory before compaction	Lost context when session compresses	Update memory at natural breakpoints

Best Practices Summary

Keep memory under 200 lines - This is a hard limit, not a guideline
Use daily logs for raw notes - Keep MEMORY.md curated and essential
Create skills for repeated patterns - Don’t re-explain the same process
Spawn agents for independent tasks - Accept token cost for isolation benefits
Parent orchestrates, agents execute - Don’t try to do everything in one context

Context Window Management in Claude Code:

Sessions have a context window that fills over time
When it fills, Claude compresses context
Memory is included in every request (until the limit)
Skills are loaded on invocation
Agents run with fresh context windows

Token Optimization:

Use haiku for lightweight, frequent tasks
Use sonnet for complex coding
Consider context window limits for long sessions

Summary

Context management isn’t about adding more context - it’s about having relevant context. Keep your memory file under 200 lines with only the essential, current state. Use daily logs for raw notes. Create skills for repeated patterns. Spawn agents when you need parallel execution with full context isolation.

The parent process orchestrates. The agents execute. And your memory stays lean, relevant, and actually readable by Claude.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

👨‍💻 Reddit Discussion: Claude Code Features

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!