Get current CPI and rent inflation data from the Federal Reserve. Returns overall inflation, shelter inflation, and rent-specific CPI with YoY changes. Use this to calibrate rent growth assumptions in your DCF model — don't guess.
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Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It implies a read-only operation by describing returned data, but does not disclose potential latency, data source limitations, or any side effects. Adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, zero wasted words. Front-loaded with purpose, then specifics, then use case. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and presence of an output schema, the description fully covers what the tool does and why to use it. No missing information for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100%. The description adds no parameter information, which is appropriate. Baseline of 4 for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Get', specific resource 'CPI and rent inflation data from the Federal Reserve', and explicit outputs (overall inflation, shelter inflation, rent-specific CPI with YoY changes). Distinguishes from siblings like get_cre_market_data by focusing on inflation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit recommendation to use for calibrating rent growth assumptions in DCF models, with a strong directive 'don't guess'. While it doesn't list alternatives or exclusions, the context is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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