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arib-memory-search

Search project memory files for historical decisions using semantic and lexical methods.

2|Updated Apr 19, 2026
Search Tags:#architecture#documentation#search#mcp#memory#knowledge
One-click install
npx skills add https://github.com/AribSudia/claude-code-methodology --skill arib-memory-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: arib-memory-search
Source: https://github.com/AribSudia/claude-code-methodology/tree/main/.claude/skills/arib-memory-search
Command: npx skills add https://github.com/AribSudia/claude-code-methodology --skill arib-memory-search

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of fragmented project knowledge by providing a unified interface to query past decisions, discoveries, and documentation stored across the project's persistent memory.

Core Features & Use Cases

  • Hybrid Search: Combines semantic vector search (via claude-mem MCP) with robust lexical grep fallback to ensure no record is missed.
  • Cross-Referencing: Automatically reconciles results from both layers to provide a single, cited answer.
  • Use Case: Use this when you need to verify why a specific architectural decision was made months ago or to find technical constraints that were recorded in a past session but are not in the main documentation.

Quick Start

Use the arib-memory-search skill to find all recorded decisions regarding the authentication token rotation strategy.

Frequently Asked Questions about arib-memory-search

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search past project decisions and historical architecture context?▼

To search past project decisions, perform a hybrid semantic and lexical search across markdown memory files to retrieve historical decisions and technical context. This approach queries persistent memory to find recorded architectural constraints.

What is hybrid semantic and lexical search for project memory?▼

Hybrid search for project memory combines semantic vector search via claude-mem MCP with standard grep lexical fallback. It cross-references both layers to provide a single cited answer for past technical discoveries.

Does semantic recall for project memory require specific dependencies?▼

Yes, semantic recall requires integration with the claude-mem MCP, while the lexical fallback relies on standard grep utilities. Both are necessary to perform comprehensive searches across architectural and bug-fix records.

How do I find technical constraints recorded in a past session but not in main documentation?▼

You can find undocumented technical constraints by querying persistent memory files stored in markdown format. The search targets architectural and bug-fix records from past sessions that bypass main documentation.

What is the best way to verify why a specific architectural decision was made?▼

The best way to verify past architectural decisions is querying persistent memory using hybrid search. It cross-references semantic vector results with lexical grep fallback to retrieve and cite the original reasoning.

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