Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It usefully adds cost ($0.01/call via x402), freshness, and source/freshness evidence. But it omits rate limits, authentication requirements, error behavior, and output structure, which are material for a paid market-data tool.

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?

A single front-loaded sentence communicates the core action, scope, optionality, and cost with no filler. Every part 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 output schema and no annotations, the description should cover more of the invocation context. It leaves interval/lookback semantics underspecified, does not describe what the returned 'source/freshness evidence' looks like, and gives no failure-mode guidance. The tool is usable but not fully self-sufficient.

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?

Schema description coverage is only 25%, so the description must compensate. It clarifies ticker scope and mentions that indicators are optional, but it does not explain the semantics of 'interval' or 'lookback'—notably whether lookback is measured in days or candles. This leaves a meaningful gap.

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?

The description uses a specific verb ('Fetch') and names the exact resource ('fresh OHLCV candles for one US ticker'), plus optional technical indicators and source/freshness evidence. This clearly distinguishes it from crypto-focused or general market sibling tools.

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?

The intended use case is clear: requesting fresh candle data for a single US equity. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.