search-interceptor

Name: search-interceptor
Availability: InStock
Author: MadAppGang

Intercept bulk file operations to recommend semantic search before execution.

278|29|Updated Nov 4, 2025

Search Tags:#code-analysis #semantic-search #token-efficiency #claudemem #interception

Ready to run

npx skills add https://github.com/MadAppGang/claude-code --skill search-interceptor-madappgang

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: search-interceptor
Source: https://github.com/MadAppGang/claude-code/tree/main/plugins/code-analysis/skills/search-interceptor
Command: npx skills add https://github.com/MadAppGang/claude-code --skill search-interceptor-madappgang

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill intercepts bulk file operations before they execute, validating whether semantic search would be more efficient and reduce token waste.

Core Features & Use Cases

Interception Triggers: multiple file reads, broad globs, and sequential reads
Decision Matrix: choose semantic search over bulk reads when indexing is available
Interception Protocol: pause, evaluate, and execute a better alternative

Quick Start

When about to read 3+ files, run claudemem search "concept X" to fetch ranked results instead.

Frequently Asked Questions about search-interceptor

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

FAQPage Schema

How do I reduce token usage when reading multiple files in a codebase?▼

Semantic search reduces token waste by fetching ranked results instead of bulk reads. Before reading 3+ files, pause and run claudemem search to get targeted matches, then read only what's needed.

When should I use semantic search instead of reading files with glob patterns?▼

Semantic search is more efficient than broad globs like **/*.ts or **/*.py when claudemem indexing is available. It ranks results by relevance, cutting unnecessary file reads and token consumption.

How does interception work to optimize file read workflows?▼

Interception pauses bulk file operations before execution, evaluates whether claudemem indexing exists, and recommends semantic search as an alternative. This decision matrix prevents wasteful sequential reads.

Can I use semantic search to replace multiple file reads in AI agent operations?▼

Yes. Semantic search intercepts bulk reads in agent workflows, applying to code-analysis tasks, parallelization scenarios, and prompts mentioning file paths. It delivers ranked results with lower token cost.

What's the difference between reading files and using semantic search for code analysis?▼

Semantic search ranks results by relevance and reduces token overhead, while bulk reads process all matches sequentially. Interception evaluates indexing availability to choose the more efficient path automatically.

Do I need claudemem indexing to use semantic search interception?▼

Yes. The interception protocol evaluates claudemem indexing before recommending semantic search. Without indexing, bulk file reads proceed as normal.