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

Annotations already declare safe read semantics (readOnly, idempotent, closed-world, non-destructive). The description adds genuine data semantics beyond that: percentiles are positions in a post-2020-04 distribution, coverage is market-cap weight, and the macro 'last change' value reflects the prior close rather than that day's move. This is exactly the kind of context annotations cannot carry.

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?

Front-loads the payload (index/breadth/valuation/macro) then layers the caveats that would otherwise cause misreading. Slightly dense with multiple caveat sentences, but each one prevents a concrete error an agent could make.

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?

With no output schema, the description usefully explains the response shape's first line and the meaning of percentile/coverage/macro fields. For a two-parameter read tool, this is close to complete, though it could say a bit more about the response structure beyond the base date.

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 coverage is 100% with both parameters (date default, format enum) fully documented in the schema, so the baseline applies. The description adds no additional parameter semantics, but none is needed.

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 names concrete resources — index, market breadth, valuation, macro — tied to a base date, so the agent knows what bundle of data comes back. It does not differentiate itself from siblings such as maedong_regime or maedong_signals, leaving the agent to infer which market-view tool to pick.

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?

It gives one explicit when-not ('do not use to generate buy/sell decisions for a specific stock') and a handling rule (quote the base date, don't call it 'today'), which is real guidance. However it never states when to prefer this over maedong_regime or the signals tools, so routing among siblings is left to inference.

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