Add shodh-memory skill: persistent context for AI agents

[varun29ankuS]

Summary

Adds shodh-memory skill - a persistent memory system for AI agents that maintains context across conversations.

What this skill teaches Claude:

• When to call proactive_context - Every user message to surface relevant memories
• How to structure memories - Rich content with reasoning, not just facts
• Memory types - Decision, Learning, Error, Discovery, Pattern, Context, Task
• Retrieval strategies - Semantic, associative, and hybrid search
• Best practices - Consistent tagging, periodic review, trust the decay system

Features of the underlying MCP server:

• Neuroscience-inspired memory consolidation (working → session → long-term)
• Hebbian learning for association strengthening
• Hybrid decay model (exponential + power-law) based on Wixted & Ebbesen (1991)
• Multi-modal retrieval (semantic similarity + graph traversal)
• Memory replay and interference detection

Links

• GitHub: https://github.com/varun29ankuS/shodh-memory
• MCP Server: Available on npm as @anthropic-ai/shodh-memory

Checklist

• [x] SKILL.md with proper YAML frontmatter
• [x] README.md with installation instructions
• [x] Tested with Claude Code