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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states the operation is read-only via 'get', specifies the output is a JSON string, and lists the exact returned keys, including a timestamp and per-component breakdown. It could add more about potential rate limits or error conditions, but for a zero-parameter read endpoint this is strong disclosure.

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 two sentences, front-loads the key purpose and cost signal, and then provides the output format in a compact, scannable list. Every sentence adds useful information without redundancy.

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 zero input parameters, an output schema, and a clear list of returned fields, the description gives an agent everything needed to invoke the tool correctly. The live-price and spread details further clarify what kind of snapshot this endpoint provides, making the context complete for its simplicity.

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 tool has zero parameters, so there are no parameter semantics to document. The description appropriately focuses on output semantics, which is all the agent needs to understand the call. This matches the baseline for a parameterless tool.

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 a composite XLM market sentiment score in [-1, 1], identifies the bullish interpretation, and lists additional outputs like per-component breakdown, live price, and spread. This distinguishes it from sibling tools such as history or report variants by emphasizing current composite sentiment plus market 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 implies the tool is for retrieving a current XLM sentiment snapshot, especially with 'live XLM price' and a timestamp field. However, it does not explicitly state when to prefer this over alternatives like get_xlm_sentiment_history or get_xlm_sentiment_report, nor does it provide any exclusion criteria.

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