APIbase

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

With no annotations provided, the description carries the full burden. It adds valuable context by identifying the data source (Finnhub) and explaining the OHLCV structure, but omits behavioral details like rate limits, data retention windows, or pagination that would be critical for a financial data API.

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?

Two tightly written sentences with zero waste: the first defines the resource and capabilities, the second specifies the use case and data source. Information is front-loaded effectively.

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 the simple parameter structure (4 flat parameters, 100% schema coverage) and lack of output schema, the description adequately covers the tool's purpose and data structure. It could improve by noting that this is a read-only operation (absent annotations) or describing the return format.

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 100%, establishing a baseline of 3. The description adds marginal value by summarizing the resolution range ('1min to monthly') in the main text, but does not elaborate on parameter interactions or date formatting beyond the schema definitions.

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 explicitly states the tool provides 'Historical OHLCV candlestick data' and defines the acronym (open, high, low, close, volume), clearly distinguishing it from sibling tools like stocks.market.quote (likely current data) and stocks.market.news.

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 description specifies the use case ('Use for charting and technical analysis'), providing implied context for when to use historical vs. real-time data, but lacks explicit guidance on when to choose this over stocks.market.quote or other siblings.

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