Are AI agents choosing
your tools?
97% of MCP tool descriptions have quality defects. Optimized tools get selected 3.6x more. ToolRank scores and fixes your tool definitions so agents pick you first.
SEO got you found. LLMO got you cited.
ATO gets you used.
SEO
Human searches Google. Your page appears.
Result: a clickLLMO
Human asks AI. Your brand is mentioned.
Result: a mentionATO
Agent autonomously acts. Your API is called.
Result: a transactionFour dimensions of agent-readiness
ToolRank Score measures each dimension so you know exactly what to fix.
Can agents discover you? Registry presence, tags, llms.txt.
Can agents understand you? Description quality, purpose, context.
Is your interface precise? Schema types, enums, error handling.
Are you token-efficient? Context cost, tool count, modularity.
Sources: arXiv 2602.14878, arXiv 2602.18914
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Score your tools — freeFrequently asked questions
What is ATO (Agent Tool Optimization)?
ATO is the practice of optimizing your tools, APIs, and services so AI agents can discover, select, and execute them autonomously. LLMO covers only Stage 1. ATO is the complete picture.
How is ATO different from LLMO?
LLMO optimizes for mentions. ATO optimizes for execution — getting your API actually called by agents. The difference is between advertising and transactions.
What is ToolRank Score?
A 0-100 metric measuring how likely AI agents are to discover and select your MCP tools. Four dimensions: Findability, Clarity, Precision, Efficiency. Optimized tools achieve 72% selection probability versus 20% baseline.
Is ToolRank free?
Yes. Score diagnosis is free. The ATO framework and scoring logic are open source.