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

With no annotations at all, the description fully carries the behavioral burden. It honestly discloses API credit cost per day returned, reverse-chronological ordering, currency conventions per asset class (crypto in GBP, FX raw exchange rates, everything else USD), and explicitly states there is no currency conversion. This goes well beyond the structured schema.

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?

Every sentence delivers essential information: function, cost, ordering, and currency rules. The primary purpose is front-loaded, and the additional behavioral details are compact and non-redundant. No filler or repetition exists.

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?

An output schema exists, so the description rightly doesn't repeat return-value structure. It covers cost, ordering, and currency nuances, which are the critical non-obvious details. It could add prerequisites like checking list_tickers for valid identifiers or note limitations on data availability, but the description is sufficiently complete for a tool of this complexity.

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 0%, so the description is the only source of parameter meaning. It clearly explains both parameters: `ticker` is the instrument whose prices are returned, and `days` defines the lookback window. It stops short of documenting constraints like valid ticker formats, maximum days, or the default behavior, but the core semantics are present.

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 opens with a specific verb and resource: 'Return daily close prices for ticker over the last days'. It also adds a key distinguishing detail ('in the ticker's native currency') and a reference to the response's `currency` field, making the tool's function unambiguous and distinct from sibling tools like get_summary or get_sentiment.

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 is strongly implied: use this tool when you need historical daily closing prices for a ticker. However, it never explicitly says when to prefer this over sibling tools, nor does it mention exclusions such as needing intraday data or non-price metrics. The guidance is implicit rather than explicit.

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