HTX Get Technical Indicators

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds meaningful behavioral details: deterministic calculation from completed candles, display rounding behavior, and the default exclusion of the current candle to avoid repainting. These enrich the agent's understanding of side effects and output semantics.

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 concise, front-loaded with the core purpose, and structured to communicate key constraints (rounding, completed candles) without verbosity. Every sentence serves a distinct informative purpose.

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?

The description is complete for the tool's scope: it explains the output type, calculation basis, defaults, and the availability of raw data elsewhere. With an output schema present, no further return-value explanation is necessary.

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?

The schema descriptions already cover all parameters with detailed formats, enumerations, and examples. The tool description itself adds no additional parameter meaning, so it does not exceed the baseline for full schema coverage.

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 returns requested technical indicators, specifying that the model chooses indicators and the tool calculates them. It is distinct from raw market data tools and establishes a clear resource and action.

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 implies when to use the tool ('Return only the requested indicators', 'never calculates them itself') and contrasts with raw K-line availability, though it does not explicitly name sibling alternatives. This is clear but not fully explicit about when not to use it in favor of other tools.

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