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Tool Search

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oimiragieo·vlatest·agents

Quickly finds relevant tools from oimiragieo's catalog based on a task description to enhance capabilities.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add oimiragieo/agent-studio --skill tool-search -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

oimiragieo

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 73 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as oimiragieo/agent-studio.
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

The Tool Search skill enables AI agents to efficiently discover and load relevant tools from a catalog, scaling beyond traditional limitations. Instead of loading all tools upfront (which consumes significant tokens), this skill uses embeddings for semantic matching to identify only the necessary tools based on the agent's task context. This approach reduces token consumption by up to 85% compared to traditional methods, allowing for larger tool libraries and improved accuracy in tool selection.

When to use it

  • When tool definitions are consuming more than 10K tokens.
  • When a tool library contains 10 or more tools.
  • When experiencing issues with the accuracy of tool selection.
  • When building MCP-powered systems that utilize multiple servers (e.g., repo, github).

Key capabilities

  • Semantic Tool Search: Finds relevant tools based on task context using embeddings.
  • Embedding-Based Matching: Uses embeddings for accurate tool discovery.
  • On-Demand Loading: Loads tools only when needed, minimizing token consumption.
  • Context Efficiency: Reduces tool definition tokens by 90%+.

Example prompts

  • "Create a pull request for my changes." (The agent will search for "github pull request creation")
  • "Search customer orders by date range."
  • "I need to read a file from disk."

Tips & gotchas

  • Configuration Required: Requires MCP configuration with betaFeatures and toolSearch settings enabled.
  • Clear Tool Descriptions: Ensure tools have clear names and descriptions for effective semantic matching.
  • Always Load Critical Tools: Consider always loading essential tools like read_file, write_file, search_code, create_pull_request, or get_issue to ensure availability when needed.