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

The readOnlyHint annotation already indicates this is a safe read operation. The description adds that it returns download instructions rather than data, and requires authentication. This provides useful context beyond annotations, but is not extensive.

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?

The description is three sentences long, each providing essential information: purpose and scope, delivery mechanism, and authentication requirement. No superfluous words or repetition.

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 tool has 4 parameters and no output schema, the description should cover what is returned (a download link) and explain all parameter options. It omits details on 'quality' and 'version' datasets, and the exact return format is implicit ('instructions'). This leaves gaps for an agent to fully understand tool behavior.

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 50% (descriptions for format and ticker only). The description adds context for dataset ('bars or the 25 pre-computed academic variables') and format ('parquet or csv'), but does not explain the 'quality' dataset option or the 'version' parameter (clean vs. raw). Thus it partially compensates for the schema's gaps.

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 clearly states the tool provides authenticated download instructions for specific datasets (1-minute OHLCV bars or pre-computed academic variables), including scope and format options. This distinguishes it from sibling tools like get_hf_variables_dictionary, which likely returns metadata.

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 gives clear context on when to use the tool (to obtain download links for full-history data) and mentions that files are fetched by user code, implying this is not for inline data. However, it does not explicitly exclude alternatives or state when not to use it.

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