get_ohlc

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

No annotations are provided, so the description carries full burden. It mentions 'Starter tier' but does not explain implications (e.g., rate limits, data freshness). No disclosure of side effects, authentication needs, or output format.

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 sentences, front-loaded with purpose and followed by use case. Every sentence adds value with no waste.

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?

For a simple data retrieval tool without output schema, the description is minimally adequate. However, it lacks details on data format, pagination, or 'Starter tier' limitations, especially given the large set of sibling tools requiring differentiation.

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 67% (2 of 3 parameters described). The description does not add meaning beyond the schema: the undocumented 'vs' parameter is not explained. The tool description does not compensate for the coverage 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 clearly states 'OHLC candlestick history for a token', which is a specific verb-resource combination. It distinguishes from sibling tools like get_price (spot price) and get_pair_data (more comprehensive data).

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 says 'Useful for technical-setup agents and backtesting', which implies appropriate use cases but does not explicitly state when not to use it or compare with alternatives. The guidance is implicit rather than directive.

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