| name | Context Manager |
| slug | context-manager |
| description | Manage conversation context and memory for optimal AI performance |
| category | meta |
| complexity | simple |
| version | 1.0.0 |
| author | ID8Labs |
| triggers | manage context, clear context, summarize context, context window, optimize context |
| tags | context-management, memory, optimization |
Context Manager
The Context Manager skill helps you optimize conversation context to maintain Claude's effectiveness throughout long sessions. It tracks context window usage, identifies when to summarize or prune context, and helps you structure conversations to keep relevant information accessible while staying within token limits.
This skill is essential for complex, multi-day projects where conversation history grows large. It helps you decide what to preserve, what to summarize, and what to discard, ensuring Claude maintains awareness of important decisions and project state without hitting context limits.
Use this skill proactively during long development sessions, before starting new major features, or when you notice performance degradation due to context bloat.
Core Workflows
Workflow 1: Monitor Context Health
- Check current context usage:
- Token count
- Percentage of limit
- Recent growth rate
- Analyze context composition:
- How much is code?
- How much is conversation?
- How much is documentation?
- Identify problematic areas:
- Redundant information
- Outdated references
- Irrelevant tangents
- Assess risk level:
- Green: <50% usage, healthy
- Yellow: 50-75% usage, monitor
- Red: >75% usage, take action
- Recommend actions if needed
- Report status to user
Workflow 2: Summarize Long Conversation
- Review conversation history
- Extract key information:
- Decisions made
- Problems solved
- Current project state
- Open questions
- Next steps
- Organize by topic/timeline
- Create concise summary
- Validate with user
- Suggest starting new thread with summary
Workflow 3: Prune Irrelevant Context
- Identify candidates for removal:
- Resolved issues
- Abandoned approaches
- Temporary debugging
- Superseded information
- Categorize by importance:
- Safe to remove
- Could summarize
- Must preserve
- Propose pruning plan to user
- Execute approved removals
- Preserve critical context
- Verify coherence after pruning
Workflow 4: Optimize Context Structure
- Analyze current context organization
- Identify inefficiencies:
- Information scattered across conversation
- Redundant explanations
- Lack of structure
- Restructure for efficiency:
- Group related information
- Create reference sections
- Use concise formats
- Suggest external documentation for:
- Architecture decisions
- API specifications
- Configuration details
- Link to external docs instead of inlining
- Validate improved efficiency
Quick Reference
| Action | Command/Trigger |
|---|---|
| Check context status | "Check context window" or "How's our context?" |
| Summarize conversation | "Summarize this conversation" |
| Start fresh with summary | "Start new thread with summary" |
| Prune old context | "Clear old context" or "Prune conversation" |
| Optimize context structure | "Optimize our context" |
| Preserve key decisions | "Document key decisions" |
| Estimate context usage | "How much context are we using?" |
Best Practices
Monitor Proactively: Don't wait for performance issues
- Check context before starting major features
- Monitor after long debugging sessions
- Review weekly on long-running projects
Summarize Regularly: Compress history at natural breakpoints
- End of feature development
- After resolving major issues
- Before switching contexts (dev → deployment)
Externalize Static Info: Move unchanging content to files
- Architecture docs
- API specifications
- Code style guides
- Reference materials
Use Structured Formats: Make information dense and scannable
- Tables instead of prose
- Bullet points instead of paragraphs
- Code blocks instead of descriptions
Preserve Decisions: Always keep the "why"
- Why this approach was chosen
- Why alternatives were rejected
- What constraints influenced decisions
Discard Aggressively: Be ruthless with temporary content
- Debugging exploration
- Failed experiments
- Resolved issues
- Superseded plans
Start Fresh Strategically: Know when to begin new conversation
- After major milestones
- When switching to unrelated work
- When context is >75% full
- When performance degrades
Document Externally: Use files for persistent knowledge
- PIPELINE_STATUS.md for project state
- DECISIONS.md for architecture choices
- TODO.md for task lists
- README.md for onboarding
Context Optimization Strategies
Strategy 1: Hierarchical Summarization
Long conversation →
Detailed summary (50% reduction) →
Executive summary (80% reduction) →
Key decisions (95% reduction)
Strategy 2: Time-Based Windowing
Keep in context:
- Last 1 hour: Full detail
- Last 4 hours: Summarized
- Last day: Key decisions only
- Older: Link to external docs
Strategy 3: Topic-Based Partitioning
Separate threads for:
- Feature development
- Bug investigation
- Deployment/ops
- Architecture discussion
Link between threads as needed
Strategy 4: Progressive Disclosure
Start with:
- Current task context only
Add on demand:
- Related decisions
- Relevant code
- Background information
Remove when done
Context Health Checklist
Before starting a major task, verify:
- Context usage < 75%
- Recent decisions documented
- Obsolete information removed
- Current project state clear
- Next steps identified
- Relevant files/docs linked
- Debugging traces cleaned up
Warning Signs of Context Issues
Watch for these indicators:
- Responses get slower: Processing large context
- Information ignored: AI misses recent context
- Repetition: AI re-explains known information
- Loss of coherence: AI forgets earlier decisions
- Token limit warnings: Approaching hard limits
- Degraded accuracy: Mistakes in previously solid areas
External Memory Strategies
Move these to files, not context:
| Information Type | Best Storage |
|---|---|
| Project overview | README.md |
| Architecture decisions | ARCHITECTURE.md or ADRs |
| API contracts | OpenAPI spec or schema files |
| Current project state | PIPELINE_STATUS.md or TODO.md |
| Configuration | .env, config files |
| Code style rules | .eslintrc, prettier.config.js |
| Deployment process | DEPLOYMENT.md or CI/CD config |
| Team decisions | DECISIONS.md or meeting notes |
Context Templates
Project State Summary Template
## Project: [Name]
- **Status**: [Current pipeline stage]
- **Current focus**: [What we're working on]
- **Last completed**: [Recent achievement]
- **Next steps**: [Immediate tasks]
- **Blockers**: [What's preventing progress]
- **Key decisions**: [Recent important choices]
Decision Log Template
## Decision: [Topic]
- **Date**: [When]
- **Context**: [Why we needed to decide]
- **Options considered**: [Alternatives]
- **Choice**: [What we decided]
- **Rationale**: [Why this choice]
- **Consequences**: [Trade-offs accepted]
Session Summary Template
## Session Summary: [Date]
- **Duration**: [How long]
- **Accomplished**: [What we built/fixed]
- **Decisions**: [Choices made]
- **Issues found**: [Problems discovered]
- **Next session**: [Where to continue]
Advanced: Context Compression Techniques
For power users:
Use references: Link to code instead of pasting
- "See function
processDatain/src/utils/data.ts" - Instead of: [pasting entire function]
- "See function
Leverage AI memory: Store in knowledge graph
- Key relationships between entities
- Project-specific terminology
- Team member roles and expertise
Create abbreviations: Define once, use everywhere
- "FE" = Frontend, "BE" = Backend
- "MR" = Merge Request, "PR" = Pull Request
- Project-specific acronyms
Use diff format: Show changes, not entire files
- Especially for code reviews
- Before/after comparisons
Batch similar information: Group related items
- All env vars in one block
- All API endpoints in table
- All dependencies in list