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

With no annotations provided, the description fully discloses behavior: it computes specific indicators, conditionally includes AI-written outlook based on LLM configuration, returns ai_available to indicate live narrative, and charges a fee. This goes beyond typical transparency and could not be inferred from annotations or 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?

The description is dense but every sentence serves a purpose: purpose, indicators, AI condition, parameter explanation, disclaimers, price, and feedback alternative. It is slightly long but well-structured and front-loaded with the core 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?

No output schema exists, but the description enumerates the result components (indicators, plain-language assessment, AI outlook, counter-argument, ai_available). It also provides pricing, feedback path, and risk disclaimers, making it sufficiently complete for an agent to select and invoke the tool.

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 must compensate. It explains the interval values (5|15|60|240|D|W) and what bars means (number of candles). Issuer and currency are not explicitly detailed but are self-explanatory for an XRPL token context, so the description adds meaningful semantics beyond the schema.

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 identifies the tool as a technical analysis of an XRPL token, listing specific indicators (EMA, RSI, support/resistance) and explicitly distinguishing it from raw data tools like get_token_ohlc. The verb 'analyze' plus the target 'token trend' are unambiguous.

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 states the tool provides an 'informational signal' and includes a disclaimer against financial advice, implying appropriate usage. It does not explicitly compare with alternatives like get_token_ohlc or check_xrpl_token, but the context is clear enough. A brief 'when to use this vs. others' would elevate it to a 5.

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