claude-cognitive
🥈SilverClaude Cognitive provides persistent context and multi-instance coordination for Claude Code. It enables operations teams to maintain working memory across multiple instances, improving productivity and token optimization. Integrates with Python-based workflows and supports Claude agents.
446360Updated 2mo ago
Intermediate30min to implementautomation
Saves ~180 min per use
Quick InstallView Source
git clone https://github.com/GMaN1911/claude-cognitive.gitWorks with:
Claude
Overview
About This Skill
Claude Cognitive solves the statelessness problem in Claude Code by providing working memory across instances. It uses two core systems: a Context Router that intelligently injects files based on attention dynamics (HOT/WARM/COLD tiers with keyword activation and decay), and a Pool Coordinator that shares state across multiple concurrent instances to prevent duplicate work and maintain long-running session context. Validated on production codebases with 1+ million lines and 8 concurrent instances, Claude Cognitive delivers 64-95% token savings while enabling new instances to be productive on the first message. It integrates with Python-based workflows and supports persistent development sessions spanning days or weeks.
How to Use
1. Identify your specific workflow and the type of data that needs persistent context. 2. Set up a Claude Cognitive instance through the Python SDK or API. 3. Configure the context window size based on your data complexity (start with 4096-8192 tokens). 4. Implement token optimization by compressing text data before storage (see example code). 5. Test with multiple instances to verify context persistence and synchronization. Tip: Start with a smaller context window and increase as needed to balance performance and memory retention.
Use Cases
Automatically maintain context across multiple Claude Code instances during long development sessions.
Reduce token usage by intelligently managing file context based on usage patterns.
Coordinate efforts between different instances to avoid duplicate work on shared codebases.
Quickly inject relevant code context based on recent interactions, improving initial response accuracy.
Tags
Setup & Installation
Quick Install
No install command available. Check the GitHub repository for manual installation instructions.
Alternative Install (Git Clone)
git clone https://github.com/GMaN1911/claude-cognitiveRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
I'm setting up a Claude Cognitive instance to manage [SPECIFIC_WORKFLOW]. I need help configuring the persistent context to maintain [TYPE_OF_DATA] across multiple sessions. Also, provide guidance on optimizing token usage for this use case. Include any relevant Python code snippets for integration.
Example Output
Based on your request to manage customer support ticket escalations, I've configured your Claude Cognitive instance with the following parameters:
1. Persistent Context Settings:
- Context Window: 8192 tokens
- Memory Retention: 7-day rolling window
- Data Structure: JSON-based ticket objects with priority flags
2. Multi-Instance Coordination:
- Instance Count: 3 (for load balancing)
- Synchronization Interval: 5-minute syncs
- Conflict Resolution: Last-write-wins with audit trail
3. Token Optimization:
```python
def optimize_tokens(ticket_data):
# Compress ticket descriptions using this algorithm
compressed = compress_description(ticket_data['description'])
ticket_data['description'] = compressed
return ticket_data
```
4. Integration Code:
```python
from claude_cognitive import CognitiveManager
manager = CognitiveManager(api_key='your_key')
manager.add_workflow('ticket_escalation', context_settings)
```
This configuration will maintain ticket context across instances while optimizing token usage by compressing text data. The system will automatically sync ticket statuses every 5 minutes.Apply to these tools
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