get_trend

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

With no annotations, the description carries the full burden. It transparently discloses the conditional behavior (P&L only when transactions are imported) and the full set of returned metrics. It does not mention error handling or side effects, but for a read-only getter, the disclosure is effective.

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-loaded with the primary purpose, and every phrase adds value. The first sentence covers the core trend data; the second adds the conditional P&L 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 the tool's simplicity (one parameter, no output schema), the description covers the main output contents and the conditional logic. The only notable gap is the lack of parameter format guidance, but overall it is sufficiently complete for an agent to invoke it.

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 coverage is 0% and the description does not define the 'market' parameter beyond using it as a subject. It does not specify expected format (e.g., 'BTC-USD' vs 'BTCUSD') or examples, so the description insufficiently compensates for the lack of schema documentation.

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's purpose: a multi-period trend digest for a market with specific percentage changes and high/low values. It also adds a conditional P&L comparison feature. This distinguishes it from siblings like get_ticker (single price) and get_candles (raw 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 provides clear context on what data the tool returns, making the use case apparent (e.g., obtain trend percentages over multiple periods). However, it does not explicitly name alternatives or exclusion conditions, so it falls short of a 5.

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